A Methodology to Identify Root Cause of Drill Bit Failure from ...

Copyright

by

Ysabel Josephine Katharina Witt-Doerring

2021

The Thesis Committee for


Certifies that this is the approved version of the following Thesis:

A Methodology to Identify Root Cause of Drill Bit Failure from

Surface Drilling Data and Bit Images

APPROVED BY

SUPERVISING COMMITTEE:

Eric van Oort, Supervisor

Pradeepkumar Ashok, Co-Supervisor

A Methodology to Identify Root Cause of Drill Bit Failure from Surface

Drilling Data and Bit Images

by


Thesis

Presented to the Faculty of the Graduate School of

The University of Texas at Austin

in Partial Fulfillment

of the Requirements

for the Degree of

Master of Science in Engineering

The University of Texas at Austin

May 2021

Dedication

Dedicated to everyone who was crazy enough to take a chance on me and to my family

and friends for their unwavering support and love.

v

Acknowledgements

I would like to acknowledge the continuous patience, guidance, support and good

humor shown by Dr. Eric van Oort, without whom none of this would have been possible.

Thank you for everything. I am extremely grateful to Paul Pastusek, whom after a

serendipitous encounter took it upon himself to become my mentor and teach me

everything he could about drill bits. Thank you for your kindness, humility and the

countless hours you invested into my professional development. Thanks also to

Pradeepkumar Ashok for his continuous feedback and support, and for keeping the wheels

turning in the background. To all the members of our research group whose help cannot be

overestimated, thank you for your friendship, especially Tesse Smitherman. I am

particularly grateful for the coding assistance and endless encouragement given by Oney

Erge. I would also like to acknowledge and thank XTO for providing the data for this

research. Finally, thank you to all the subject matter experts from NOV, Halliburton, Baker

Hughes, Ulterra, Schlumberger, E6, US Synthetic and IDS for investing hours into my

education and understanding of PDC cutter damage and failure.

vi

Abstract

A Methodology to Identify Root Cause of Drill Bit Failure from Surface

Drilling Data and Bit Images

Ysabel Josephine Katharina Witt-Doerring, M.S.E

The University of Texas at Austin, 2021

Supervisors: Eric van Oort and Pradeepkumar Ashok

Polycrystalline diamond compact (PDC) drill bits are exposed during drilling operations to

various downhole conditions, ranging from benign (normal) conditions to various states of

dysfunction. These include stick slip, whirl, bit bounce, and structural overload when

drilling heterogeneous formations. It is well-known that these conditions can lead to PDC

damage and eventual failure. However, little work has been published describing PDC

damage modes and their origins.

A workflow is introduced in this thesis to locate the point of “bit failure” from an

analysis of relevant surface data, with key information provided by the PDC dull images.

The root cause of the failure is then inferred from this analysis. This information can be

used during well planning for optimized bit selection and BHA design, and for drilling

parameter and tool selection guidance. It can also be used to optimize future bit runs,

improving ROP and extending bit life, through observation of suitable drilling parameters.

vii

Table of Contents

List of Tables .................................................................................................................... xii

List of Figures .................................................................................................................. xiii

List of Illustrations ........................................................................................................... xix

1. INTRODUCTION ..............................................................................................................1

2. LITERATURE REVIEW ...................................................................................................3

2.1 Genesis of PDC Damage ...............................................................................................3

2.2 Bit Wear Models ............................................................................................................8

2.3 Summary ......................................................................................................................11

3. UNDERSTANDING PDC DAMAGE ................................................................................12

3.1 Modes of PDC Damage ...............................................................................................12

3.1.1 Smooth Wear ..........................................................................................13

3.1.2 Understanding Cutter Loading and Fracture Damage ............................15

3.1.3 Normal Fracture ......................................................................................17

3.1.4 Tangential Fracture .................................................................................19

3.1.5 Thermal Damage .....................................................................................22

3.1.5.1 Transitional and Thermal Mechanical Wear ..................................22

3.1.5.2 Spalling ..........................................................................................23

3.1.5.3 Heat Checking ................................................................................28

3.1.6 Corrosion.................................................................................................29

3.1.7 Erosion ....................................................................................................31

viii

3.2 Damage and Wear Progression ....................................................................................33

4. WORKFLOW DEVELOPMENT ......................................................................................37

4.1 Workflow Implementation ...........................................................................................42

5. RESULTS AND DISCUSSION ..........................................................................................45

5.1 Results ..........................................................................................................................45

5.2 Discussion ....................................................................................................................55

5.3 Additional Observations ..............................................................................................65

5.3.1 Characterizing Whirl Damage ................................................................65

5.3.2 Implications of Well Orientation ............................................................68

6. CONCLUSIONS AND FUTURE WORK ............................................................................69

6.1 Future Work .................................................................................................................70

6.1.1 Drilling Strength .....................................................................................70

6.1.2 Downhole Sensors ..................................................................................71

6.1.3 Real Time Analysis .................................................................................71

6.1.4 IADC Dull Grading.................................................................................72

7. APPENDICES .................................................................................................................74

7.1 Appendix A – Well orientations, locations and motor speeds .....................................74

7.2 Appendix B – Well 1: Dull Photos and Grading .........................................................75

7.2.1 Run 1 .......................................................................................................75

7.2.2 Run 2 .....................................................................................................76

7.2.3 Run 3 ......................................................................................................77

7.2.4 Run 4 ......................................................................................................78

ix

7.3 Appendix C – Well 2: Dull Photos and Grading .........................................................79

7.3.1 Run 1 .......................................................................................................79

7.3.2 Run 2 .......................................................................................................80

7.3.3 Run 3 .......................................................................................................81

7.3.4 Run 4 ......................................................................................................82

7.3.5 Run 5 ......................................................................................................83

7.3.6 Run 6 ......................................................................................................84

7.3.7 Run 7 ......................................................................................................85

7.3.8 Run 8 ......................................................................................................86

7.4 Appendix D – Well 3: Dull Photos and Grading .........................................................87

7.4.1 Run 1 .......................................................................................................87

7.4.2 Run 2 .......................................................................................................88

7.5 Appendix E – Well 4: Dull Photos and Grading..........................................................89

7.5.1 Run 1 .......................................................................................................89

7.5.2 Run 2 ......................................................................................................90

7.5.3 Run 3 ......................................................................................................91

7.5.4 Run 4 .......................................................................................................92

7.5.5 Run 5 ......................................................................................................93

7.5.6 Run 6 .......................................................................................................94

7.5.7 Run 7 ......................................................................................................95

7.5.8 Run 8 ......................................................................................................96

7.6 Appendix F – Well 5: Dull Photos and Grading ..........................................................97

7.6.1 Run 1 .......................................................................................................97

x

7.6.2 Run 2 .......................................................................................................98

7.7 Appendix G – Well 6: Dull Photos and Grading .........................................................99

7.7.1 Run 1 .......................................................................................................99

7.7.2 Run 2 .....................................................................................................100

7.7.3 Run 3 .....................................................................................................101

7.7.4 Run 4 .....................................................................................................102

7.7.5 Run 5 .....................................................................................................103

7.7.6 Run 6 .....................................................................................................104

7.7.7 Run 7 .....................................................................................................105

7.7.8 Run 8 .....................................................................................................106

7.7.9 Run 9 .....................................................................................................107

7.8 Appendix G – Well 7: Dull Photos and Grading .......................................................107

7.8.1 Run 1 .....................................................................................................108

7.8.2 Run 2 ....................................................................................................109

7.8.3 Run 3 ....................................................................................................110

7.8.4 Run 4 ....................................................................................................111

7.8.5 Run 5 .....................................................................................................112

7.8.6 Run 6 ....................................................................................................113

7.8.7 Run 7 ....................................................................................................114

7.8.8 Run 8 ....................................................................................................115

7.8.9 Run 9 .....................................................................................................116

7.9 Appendix H – Well 8: Dull Photos and Grading .......................................................117

7.9.1 Run 1 .....................................................................................................117

xi

7.9.2 Run 2 ....................................................................................................118

7.9.3 Run 3 ....................................................................................................119

7.9.4 Run 4 ....................................................................................................120

7.10 Appendix I – Well 9: Dull Photos and Grading................................................121

7.10.1 Run 1 .....................................................................................................121

7.10.2 Run 2 .....................................................................................................122

7.10.3 Run 3 .....................................................................................................123

7.10.4 Run 4 .....................................................................................................124

8. REFERENCES ..............................................................................................................125

xii

List of Tables

Table 1 - Pull criteria for the given 8.75” PDC design ......................................................57

Table 2 - Drilling efficiencies seen on runs after RO as well as after only

mild/moderate wear ......................................................................................61

Table 3 - Well names, orientations, locations and motor speeds .......................................74

xiii

List of Figures

Figure 1 - PDC bit market adoption curve from 1980 projected to 2016 (Bellin et al.,

2010) ...............................................................................................................3

Figure 2 - Smooth wear (Image courtesy of P. Pastusek, ExxonMobil) ............................15

Figure 3 - Forces on a PDC cutter. Ft is the tangential force and Fa the normal (axial)

force (Liang et al., 2014)...............................................................................16

Figure 4 - Normal load is approximately normal to cutting edge (Pastusek, 2019) ..........16

Figure 5 - Load needed to reach the same stress level in the cutter normalized per load

orientation (Rahmani et al., 2020) ................................................................17

Figure 6 - Detecting load direction from spalling (Pastusek, 2018) ..................................18

Figure 7 - Examples of interfacial delamination (Image courtesy of P. Pastusek,

ExxonMobil) .................................................................................................18

Figure 8 - Load Ft tangential to cutter edge (Pastusek, 2019) ...........................................19

Figure 9 - Examples of thumbnail cracks (Image courtesy of P. Pastusek,

ExxonMobil) .................................................................................................19

Figure 10 - Examples of tangential fractures, high energy (left) and single cleaved

plane with plastic hinge (right) (Image courtesy of P. Pastusek,

ExxonMobil) .................................................................................................21

Figure 11 - Schematic showing formation of plastic hinge (Pastusek, 2019) ...................21

Figure 12 - (a) Micro-spalls along wear flats and, (b) Spalling, due to thermal stresses

(Image courtesy of P. Pastusek, ExxonMobil)..............................................23

Figure 13 - Diamond table flaking away from primary wear flat (Image courtesy of

P. Pastusek, ExxonMobil) .............................................................................24

xiv

Figure 14 - (a) Micro-spalls along wear flats; (b) Spalling of thermal origin; (c) Green

cutters surrounding a deep spall, suggests mechanical failure due to

overload in the normal direction (Images courtesy of P. Pastusek,

ExxonMobil and Santos Ltd.) .......................................................................25

Figure 15 - Cat eye cracks radiating from wear flats (Image courtesy of Konstantin

Morozov).......................................................................................................27

Figure 16 - Heat checking on a cutter (Image courtesy of P. Pastusek, ExxonMobil) ......28

Figure 17 - Stress induced corrosion/erosion (Image courtesy of P. Pastusek,

ExxonMobil) .................................................................................................30

Figure 18 - Corrosion due to substrate oxidation (Image courtesy of P. Pastusek,

ExxonMobil) .................................................................................................30

Figure 19 - Examples of substrate, matrix and steel erosion (far right) (Images

courtesy of P. Pastusek, ExxonMobil) ..........................................................31

Figure 20 - Contact area of a typical cutter, on center rotation with no vibration. The

contact load on the cutter face is a function of the formations confined

compressive strength (Pastusek et al., 2018) ................................................34

Figure 21 - Examples of PDC ring out on the shoulder (left) and nose (right) .................36

Figure 22 - Examples of two and three blade core out (Left image courtesy of

Marathon Oil)................................................................................................36

Figure 23 - Frame designs used in this study .....................................................................43

Figure 24 - Well 1: Median wear metric value for each stand vs. measured hole depth

and PDC bit dull description .........................................................................46



xv




and PDC bit dulls showing inefficient nozzle placement (left), and

suspected stick slip/whirl damage (right) .....................................................49











Figure 33 - Graph comparing wear metric and ROP for two runs from Well 7, as well

as corresponding dull grades .........................................................................55

Figure 34 - Four buckets used to capture the various stages of PDC wear .......................57

Figure 35 - Surface EDR data from 7th stand of Run 7 from Well 4 showing instances

of erratic torque .............................................................................................62

Figure 36 - Snapshot from surface EDR data from 7th stand of Run 7 from Well 4

showing possible stick slip event ..................................................................63

Figure 37 – Suspected whirl damage on gauge cutters from Well 4, Run 8......................64

Figure 38 - Example of gauge and number one cutter damage .........................................65

Figure 39 - Low versus high angle back rack on gauge cutters .........................................66

xvi

Figure 40 - Schematic showing normal/strike-slip faulting regime (Ma and Zoback,

2017) .............................................................................................................68

Figure 41 - Well 1, Run 1: Dull photos and grading .........................................................75























xvii



Figure 66 - Well 6, Run 2: Dull photos and grading .......................................................100























xviii


xix

List of Illustrations

Illustration 1 - Flowchart showing basic relationship between drilling and cutter

damage ....................................................................................................13

Illustration 2 - High level PDC wear progression from damaged cutter to bit failure.......33

Illustration 3 - Genesis of PDC ring out in hard formation followed by structural

overload of nose cutters upon reentry .....................................................59

1

1. INTRODUCTION

Polycrystalline Diamond Compact (PDC) drill bits account for approximately 90+% of the

global footage drilled, and are widely used across all of the North American land operations (Scott,

2015). PDC bit and cutter manufactures observe dull grades post run to determine and evaluate the

effectiveness of certain cutters and design features, but most operators still treat bit grading and

forensics as an afterthought. More often than not, the decision of which bit to run next has already

been made prior to the previous being pulled. This is often done with minimal quantitative or

qualitative analysis performed on the damage incurred in previous bit runs.

Drilling optimization to minimize drilling time and cost is becoming more important as

drilling activity focuses increasingly on low-cost land environments such as unconventional shale

plays. There exist numerous indicators to gauge drilling efficiency and dysfunction (including

mechanical specific energy (MSE), bit aggressiveness (μ), stick slip alarm, etc.…) to a limited

degree from surface data. As downhole sensors and technology improve (Pastusek, Sullivan and

Harris, 2007) companies have been able to use them to better identify drilling limiters, adjust

drilling parameters and develop better drilling roadmaps. This has improved drilling time (per hole

section) and reduced trips and tool/bit damage (Giltner et al., 2019, Teelken et al., 2016). However,

this technology is expensive. For example, the incremental cost of implementing a wired pipe

system is estimated at ~ US $1.68M (Hennessy, 2016). In the absence of widespread adoption to

lower these costs, wired pipe and other downhole telemetry systems are prohibitively expensive

for the standard low-cost operator.

The role downhole dysfunction and hard/interbedded formations play in reduced rate of

penetration (ROP) due to drilling inefficiencies is well-known. It is also known that these

2

conditions will damage bits. Surprisingly, there has only been limited work done to correlate these

conditions directly to PDC wear/damage. Aside from the remark “damaged beyond repair” or the

use of the highly subjective International Association of Drilling Contractors (IADC) dull grading

codes, in-depth descriptions of the damage modes that have occurred in conjunction with the

downhole conditions are often neglected.

A low-cost method to perform PDC root cause analysis using surface sensor data and PDC

dull photos is presented in this thesis. The subsequent data analysis reinforced many of the existing

notions around PDC wear and failure, whilst emphasizing the importance of clear and

comprehensive pull criteria within hard, abrasive formations.

This thesis is organized as follows. Chapter 2 is a literature review that covers the

relationship between various drilling environments and PDC damage, as well as existing bit wear

models. Chapter 3 discusses the common modes of PDC damage and their origins. It then steps

through how PDC damage progresses and discusses the common bit failures encountered. Chapter

4 focuses on the workflow and how it was implemented to conduct root cause analysis. Chapter 5

discusses the results and how the wear factor was able to identify downhole issues and associated

PDC damage. Chapter 6 contains conclusions and includes suggestions for future research that

should be conducted to further validate observations made during the course of this work.

3

2. LITERATURE REVIEW

2.1 Genesis of PDC Damage

The first carbide-supported PDC was invented by GE in 1971, and over the subsequent

years multiple trials and tests were run to further develop the technology. 1977 was the first full

year of commercial PDC use, but by the end of the 1980’s Baker Hughes estimated that PDC’s

still only “accounted for less than 2% of footage drilled” (Scott, 2006). Early success was seen

drilling evaporates, but shale and abrasive streaks continued to be a problem limited PDC

technology uptake. As issues surrounding blazing as well as fluid dynamics were addressed, the

market share of PDC’s continued to grow throughout the 80’s (Figure 1). As the use of PDC’s

became more prevalent, corresponding research into PDC cutter performance and damage grew.

Figure 1 - PDC bit market adoption curve from 1980 projected to 2016 (Bellin et al., 2010)

4

Throughout the 1980’s, the majority of literature on PDC damage was focused on thermal

degradation and abrasive wear of the cutters. It was widely understood that at increased

temperatures, the wear rate of a PDC cutter would increase (Glowka and Stone, 1986). In the

absence of thermal physical/chemical failure, mechanical cutter failure was attributed to

microscopic chipping caused by fatigue of the diamond-to-diamond bonds as a result of cyclical

loading (Sneddon and Hall, 1988). Drag cutter models were created that investigated the

relationship between wear flat temperature and area (Glowka, 1985) as well as between ROP and

wear (Hareland and Rampersad, 1994).

By the start of 1990’s it was being recognized that impact damage was more likely to cause

PDC cutter damage and premature failure than wear alone (Warren et al., 1990). Brett et al. (1990)

were the first to report bit whirl, specifically backward whirl, of PDC bits. Whirl and the associated

lateral vibrations were flagged as the cause of impact damage observed on cutters. They observed

that PDC cutters were significantly chipped after drilling a single hard streak (16-17k psi UCS).

These chips were then developing into wear flats, indistinguishable from a wear flat caused purely

by abrasion or thermal effects. Accelerated wear was seen in chipped cutters, due to increased

thermal loads but also due to the fact that once the diamond table was lost, the much softer

tungsten-carbide substrate would wear very quickly (Warren et al., 1990).

Following the identification of bit whirl as a performance limiter, subsequent work

throughout the early 90’s was focused on the development of “anti-whirl” bits and the evaluation

of their performance (Warren et al., 1990; Cooley et al., 1992; Sinor and Warren, 1993). Warren

et al. (1990) discovered that bit whirl could be eliminated by directing the net imbalance cutter

force to a low friction gauge pad (as opposed to more aggressive gauge cutters). As a result, the

5

bit would slide instead of “walk” along the borehole wall and the majority of subsequent research

built on this notion.

As whirl was mitigated through updated PDC design and cutter technology improved,

harder formations were now being successfully drilled and higher weight on bit (WOB) was

applied to improve drilling efficiency. The result was increased incidence of stick/slip. Fear et al.

(1997) reported on PDC damage caused by stick-slip. In larger gauge holes (> 17-1/2 in.) whilst

using non-anti-whirl bits, they observed flattened noses, nose ring out, as well as cutter breakage

and loss outside of the nose ring-out. It was speculated, although unproven, that bit whirl was

triggering the initial torque disturbance instigating stick-slip. Pastusek et al. (2007) discussed the

various cutter loading directions that could be seen by a cutter during stick slip events and their

detrimental effects in hard formations. During the ‘slip’ stage of stick slip, the cutters are loaded

on the front face (being the tangential direction). Small fluctuations in revolutions per minute

(RPM) around the average value were observed to have minimal impact on PDC performance.

However, it was noted that it was possible for large fluctuations in RPM, to transition into whirl,

thus resulting in impact damage as discussed previously. More interestingly, during the stick stage,

where the bit is stationary, the resultant load on the cutters approaches vertical, in other words an

axial load (load normal to the cutting face) is applied to the cutter which can result in spalling.

Reverse rotation was also seen to be possible during the slip stage of stick slip due to overrotation.

Reverse loading on the cutters resulted in diamond tables being pulled off the substrates in tension,

causing spalling. This phenomenon was observed throughout the 1990’s and 2000’s. However, as

cutter technology continued to improve, incidents of this type of damage is uncommon today.

Through the use of downhole sensors, Ledgerwood et al. (2013) were able to show that lateral

vibrations during the slip stage of stick slip were causing significant PDC damage. These lateral

6

vibrations sometimes resulted in backward whirl, but in many cases they did not: instead,

nonsynchronous forward whirl was being observed. Damage associated with lateral vibrations

coupled with stick slip manifested itself primarily as spalling on the ground flats and on the gauge

cutters, after which it would spread to the cutter face. More importantly, Ledgerwood et al. (2013)

noted that PDC dull condition was not observed to be a function of on-bottom time but rather a

function of maximum lateral vibration recorded during the run. This firmly cemented the notion

that PDC damage and subsequent accelerated wear was being caused by dysfunction.

Despite the understanding that drilling dysfunction was causing PDC damage and

accelerated failure within hard formations, and that dysfunction needed to be mitigated to extend

bit life, hard interbedded formations were still proving troublesome to drill. Mann et. al (2016)

discussed the issues surrounding drilling dysfunction in laminated formations. For these they

showed that despite the occurrence of stick-slip, it was not the primary cause of damage. Rather,

they identified that simple speed oscillations, caused by rotating the drill pipe at its resonant

frequency, were triggering high lateral vibrations. These synchronous torsional oscillations (STO),

first identified by Ertas et al. (2014), were thought to be causing a reduction in penetration rate per

revolution (ROP/RPM), often referred to as the depth of cut (DOC), which in turn was triggering

the high lateral vibrations. The result of this dysfunction was significant impact damage to the

outer 2- 3 rows of the shoulder cutters (towards the gauge), which is commonly associated with

whirl. The bottom edges of the cutters also showed signs of heat checking and thermal stress

failure, which the authors attributed to the high velocities coupled with poor cooling during the

slip phase of stick-slip.

To date, the majority of work surrounding cutter damage has been focused on wear and

impact damage. Pastusek et al. (2018) were the first to discuss tangential fracture damage due to

7

structural overload, observed when drilling interbedded formations. They identified that drilling

through interbedded formations was damaging the nose and surrounding cutters on the PDC

profile. This tangential damage was significantly different from impact damage caused by whirl

and lateral vibrations that had been presenting itself as chipping and spalling on the gauge. Unlike

spalling which occurs parallel to the cutter face, tangential fractures presented themselves as a

shear plane through the diamond and substrate. Pastusek et al. (2018) proposed drilling with depth

of cut (DOC) control as opposed to WOB control through interbedded (soft-to-hard) formations.

In doing this (alongside PDC design changes), it would avoid structurally overloading the nose

cutters when first engaging the “hard” formation, while the rest of the bit profile still remained in

the “softer” formation. Dupriest et al. (2020) built on this research and concluded that tangential

fracture of shoulder cutters was also happening when exiting hard formations into soft. Here the

nose cutters would engage the softer formation first followed by the shoulder cutters, still in the

harder formation, would be structurally overloaded and fail. They discussed the need to determine

a survival “WOB” that controlled DOC, avoiding structural overload but was high enough to

mitigate lateral vibrations and associated impact damage.

8

2.2 Bit Wear Models

In order to predict and track PDC performance and wear, various models that relate drilling

parameters, and rock/bit properties have been developed.

Whilst investigating the thermal effects on PDC cutter wear, Glowka and Stone (1986)

derived an equation for mean temperature across a wear flat. It showed how the cutter wear rate

per unit weight increased with increasing wear flat temperature. Thermal effects were seen to

reduce the mechanical strength and increase the thermal stresses seen by the cutters thus

accelerating wear.

Warren and Sinor (1989) created a PDC model that integrated the forces seen by each

individual cutter on the bit. By inputting specific cutter geometry, formation properties, ROP and

RPM they were able to calculate the volume of rock removed by each cutter, total WOB, torque,

bit imbalance force and total wear flat area. They were able to identify cutter and imbalance forces

when drilling from soft-to-hard and hard-to-soft formations. They observed that when drilling from

soft-to -hard formations, significant impact loading occurred. This load was enough to severely

chip cutters, or break them away from the bit body. Similar damage was recorded later by Pastusek

et al. (2018.) Furthermore, when transitioning from hard-to-soft, they calculated a very large and

prolonged imbalanced force. This force damaged the “middle” cutter on the blade, rather than

gauge or nose. This observation potentially supports the work of Dupriest et al. (2020). Regardless

of the results the methods required to determine the cutter geometry and position, inputs for the

model, are tedious and these values are not easily obtained. Furthermore, the relationship they used

to calculate cutter wear rate was based on an empirical relationship between wear rate in “Jack

Fork” sandstone and cutter temperature. The model itself was not straightforward to implement or

relevant for everyday drilling evaluation and optimization.

9

Hareland and Rampersand (1994) identified the limitations of the Warren and Sinor (1989)

model, and instead created a model that could predict ROP for a given set of operating conditions,

formations and bit design. In terms of bit design input, the model only required a simple

geometrical description of the cutters. They modelled cutter wear as a function of the rock uniaxial

compressive strength (UCS), rock abrasiveness co-efficient, diamond grit size and drilling

parameters. Cutter wear was then inputted into a model for ROP and volume of rock removed per

revolution. The result was a “simpler” model that could be used for drilling optimization and

improved bit selection and design.

Work completed by Motahhari et al. (2010), Rahimzadeh et al. (2010), Rashidi et al. (2010)

continued to present various models for ROP as well as PDC wear. As with previous models they

acknowledge that wear was a function of WOB, RPM, rock strength and abrasiveness. In all cases

the models contained various “bit wear co-efficients’, “bit constants” and “model constants”.

Although these models were relatively straight forward, without large amounts of data to validate

the models, real-world applications become troublesome.

Liu et al. (2014) presented a “simple analytical PDC bit wear” model that did not require

WOB or RPM data, allowing it to be used for preplanning and predicting ROP’s in the absence of

surface data. The model used bit and rock properties as well as model constants to predict wear

and required accurate gamma ray data to predict quartz content and thus rock abrasiveness. This

model was no less simple than those previously discussed and still required a large amount of

accurate formation data to be implemented.

10

Using data analytics and machine learning Liu et al. (2018) combined physical drilling

mechanics modelling with machine learning. They implemented real time surface monitoring of

bit wear using the following relationship:

𝑊𝑒𝑎𝑟 𝑓𝑎𝑐𝑡𝑜𝑟 = 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡 ∙

𝑊𝑂𝐵

(𝑅𝑂𝑃

𝑅𝑃𝑀𝑏𝑖𝑡)

(1)

By training a model with a set of IADC dull grades, associated bottom hours and calculated

wear factors they were able to predict low, median and high wear conditions of drill bits in real

time. They also noted that when compared with other mechanics-based metrics such as bit

aggressiveness and mechanical specific energy, the wear factor was the most sensitive metric to

changes in cutter wear and thus a superior predictor of PDC damage.

11

2.3 Summary

It is well understood that drilling dysfunction causes PDC damage, especially within hard

formations. Different types of dysfunction will result in varied modes of damage. Although there

are multiple papers presenting various case studies, what is lacking in the literature is a concise

understanding of the modes of PDC damage and associated forensics. Similarly, the majority of

existing bit wear models were focused primarily on predicting ROP performance to assess bit

performance and life for preplanning. With the exception of the workflow presented by Liu et al.

(2018), the models were not used to determine PDC condition in real time.

Liu et al. (2018) were the first to use their bit wear model to assess bit performance in real

time to improve drilling surveillance and to streamline decision-making processes related to bit

trips. The wear factor used by Liu et al. is an apt tool for predicting the IADC dull condition.

However, there are issues with the workflow presented. The machine learning algorithm they used

to predict dull condition relied heavily on on-bottom time, which as previously discussed was

shown by Ledgerwood et al. (1993) to be a poor predictor of dull condition. Furthermore, the

IADC dull condition (the failures of which are discussed in Section 6.1.4), although it may help

determine pull criteria, does little to help identify root cause of drill bit failure. No focus was given

to PDC forensics and understanding the failure mechanisms surrounding PDC damage.

The following chapters will identify and discuss the different damage modes that need to be

considered when performing PDC forensics and root cause analysis.

12

3. UNDERSTANDING PDC DAMAGE

3.1 Modes of PDC Damage

In order to conduct root cause analysis of PDC drill bits it is important to understand how

PDC cutters can be damaged and what that damage looks like. PDC drill bits are exposed to

downhole conditions ranging from benign smooth rotation to various states of dysfunction such

as; stick slip, whirl, bit bounce, and structural overload. Understanding the root cause of cutter

damage at the rig site can help optimize drilling parameters as well as selection of the next bit to

be run. This can also be used for changes in bit design, BHA configuration, tool selection, and

parameter guidance in planning future wells. Finally, it can be used to define and measure the

performance of longer-term research and new product development.

Six modes of damage most commonly encountered:

1. Smooth wear

2. Normal fracture (aka. spalling and delamination, normal to the profile)

3. Tangential fracture (fracture in the cutting direction)

4. Thermal damage

5. Erosion

6. Corrosion

Each of these damage modes can be characterized by various visual attributes and tend to have

different origins; thermal, mechanical and chemical (Illustration 1). More often than not, an

individual PDC cutter may show signs of multiple damage modes. Smooth wear, for example, can

lead to thermal damage as wear flats grow larger and over time corrosion and erosion can occur

together. The question for root cause analysis is “What was the initiation or primary event?”

13

Because cutters are highly stressed and exposed to all the formations drilled, drilling optimization,

bit selection, and failure analysis relies on understanding of the nuances of cutter damage and

associated causes.

In addition to the typical cutter damage categories listed above, there can be bit damage due to

lost nozzles, balling, broken blades, junk damage, etc. These other causes of failure can also be

rectified if they are separately identified and not assumed to be due the normal drilling process.

3.1.1 SMOOTH WEAR

The mechanisms that drive smooth cutter wear (also known as abrasive wear) are the micro

fracture of the diamond grains and grain pull out from the bulk of the cutter (this is temperature

dependent). Smooth wear occurs in the absence of drilling dysfunction/interfacial severity and is

a function of:

- Rock hardness – this controls the interface pressure on the wear flat

DAMAGED CUTTER

THERMAL

MECHANICAL

CHEMICAL

DRILLING

SMOOTH/BENIGN

DYSFUNCTION

INTERFACIAL SEVERITY

Possible relationship

Direct relationship

Illustration 1 - Flowchart showing basic relationship between drilling and cutter damage

14

- Abrasiveness – the rock matrix strength, and the angularity, hardness, size of the grains all

affect the abrasiveness of the formation

- Sliding distance – wear is a function of sliding distance, more so than the load on the

individual cutters. The load per cutter is highest in the cone, but the greatest wear typically

occurs on the shoulder where the sliding distance is higher.

During drilling operations the drilled material acts as an abrasive between the cutter wear flat

and formation. The greater the distance travelled by the cutter the greater the volume of material

that flows beneath it, and the more wear it experiences. More bit revolutions used to drill a certain

footage requires larger sliding distance of the cutter. Thus there is less smooth cutter wear with

higher penetration per revolution of the bit. This is usually accomplished with higher weight on

bit. Somewhat counter intuitively, higher WOB leads to higher penetration per revolution (DOC)

and thus less wear; as long as the cutters do not fracture. Smooth wear tends to be the greatest on

the shoulder, as these cutters travel more distance per revolution than the cone cutters. The

shoulder cutters also do more work and experience higher temperatures than the gauge trimmers

for the same sliding distance. Thus there is typically more wear on the shoulder than the gauge

cutters even though their sliding distances are similar. This is thought to be due to temperature

effects.

Wear itself goes through multiple stages that are both mechanical and thermal mechanical in

origin; smooth wear, transitional wear and thermal mechanical wear (“Application specific

design and PDC failure modes”, 2020). Each stage is characterized by specific mechanical/thermal

changes within the diamond and carbide. Smooth wear is simple mechanical wear that results from

the loss of individual diamond grains from the diamond table. During early stages of wear, the

diamond grains are worn or are pulled out. The diamond grain size will dictate how fast wear

15

progresses. Smaller feeds result in a smaller loss of material per grain lost and have better diamond-

diamond bonding, and thus lower wear rates than coarser feeds. Smooth wear is visually

characterized by a straight/relatively flat wear surface seen in Figure 2.

3.1.2 UNDERSTANDING CUTTER LOADING AND FRACTURE DAMAGE

Before discussing fracture damage it is important to understand that the direction of cutter

loading will affect how quickly they fracture. Cutters are loaded tangentially (in the direction of

rotation), normally (normal to the bit profile, along the cutter edge) (Figure 3 and Figure 4). As

noted above, they are also loaded thermally due to differential expansion of the diamond table,

carbide backing, and cobalt.

Figure 2 - Smooth wear (Image courtesy of P. Pastusek, ExxonMobil)

16

Figure 5 shows the loads required reach the same maximum principle stress within the

diamond table for various load directions. These loads are normalized in reference to the yellow

arrow which represents the load experienced during standard drilling operations. If the diamond

table is in compression it can withstand very high forces in both tangential and normal direction.

However, if one component dominates over the other it can create tension in the diamond table,

and damage will occur at much lower loads, as shown in Figure 5.

Figure 4 - Normal load is approximately normal to cutting edge (Pastusek, 2019)

Figure 3 - Forces on a PDC cutter. Ft is the tangential force and Fa the normal (axial)

force (Liang et al., 2014)

17

Figure 5 - Load needed to reach the same stress level in the cutter normalized per

load orientation (Rahmani et al., 2020)

3.1.3 NORMAL FRACTURE

High forces normal to the cutting edge (in the absence of a balancing tangential force) will

result in chipping, spalling and delamination of the diamond table. Chipping is the loss of the tip

of the diamond table. It extends along the face of the cutter and is the result of mechanical loading.

Thermal stresses and load direction can lower the load at which this occurs.

Spalling refers to the flake or loss of diamond material parallel to the face of the cutter and

is larger than chipping. Spalling can be shallow or deep within the diamond table, it does not

extend to the carbide. When observing a spall, the center of the concentric rings on the cutter face

that make up the spall reflect the fracture initiation location and direction of loading (Figure 6).

18

Figure 6 - Detecting load direction from spalling (Pastusek, 2018)

If spalling extends to the carbide, it is known as delamination (US Synthetic), although some

companies required a “clean” interface, with almost no finished diamond remaining (Halliburton)

before classifying a delamination. Interfacial delamination is a total loss of diamond table that

exposes the non-planar interface (NPI) (Figure 7). This is usually associated with a sintering

process issue, a NPI that is prone to this type of failure, or from over leaching/acid damage.

Figure 7 - Examples of interfacial delamination (Image courtesy of P. Pastusek, ExxonMobil)

19

3.1.4 TANGENTIAL FRACTURE

Tangential fractures are caused by excessive tangential force (front face loading), with less

normal force. The tangential force acts in the direction opposite to the motion of the cutter (Figure

8). When the tensile stress in the cutter due to the tangential force exceeds the diamond-to-diamond

bond strength the cutter will crack. Tangential fractures are characterized by a crack through the

diamond table toward the carbide substrate with the loss of material perpendicular to the face

of the cutter.

Tangential fractures that do not propagate through the carbide are commonly described as

thumbnail cracks (Figure 9). The crack can start at an edge or interface and extend across the face

of the cutter. The load required to initiate fracture is the strength of the cutter. Fracture toughness

Figure 9 - Examples of thumbnail cracks (Image courtesy of P. Pastusek, ExxonMobil)

Figure 8 - Load Ft tangential to cutter edge (Pastusek, 2019)

20

determines how fast the crack will propagate and will determine whether partial, or full failure of

the cutter will occur.

Cutter strength is defined by the load required to initiate a facture or crack. Fracture

toughness is the energy required to propagate this fracture though the diamond and carbide and

measures the ability of the cutter to resist fracture growth/propagation. A coarser diamond feed

will result in weaker diamond that is tougher, whereas as a fine feed will create a stronger diamond,

that is less tough (more brittle). There is open debate in the industry if fracture toughness or fracture

initiation dominates in the cutter damage seen. For drilling operations it is most important to know

that this load direction is different than that for spalling and thus the corrective actions will be

different.

Tangential fractures are a result of Hertzian cracks. The initial crack that can lead to a

tangential fracture will form outside the loading region. If the fracture is “clean”, a single cleaved

plane (Figure 10) is created. The plastic hinge (Figure 11) that remains is indicative of the load

direction. Fractures don’t always occur in one fell swoop and often the fracture surface will be

jagged. Anecdotal evidence suggests a jagged fracture plane (Figure 10) is more likely a result of

some high energy event such as junk damage, drilling chert, pyrite, or rotating inside casing etc.

21

Figure 10 - Examples of tangential fractures, high energy (left) and single cleaved plane

with plastic hinge (right) (Image courtesy of P. Pastusek, ExxonMobil)

Plastic hinge

Figure 11 - Schematic showing formation of plastic hinge (Pastusek, 2019)

22

3.1.5 THERMAL DAMAGE

Thermal stresses can add to the damage discussed in prior sections. However, cutter

damage can also be primarily thermal in origin. There are two mechanisms involved in the thermal

degradation of PDC cutters, both are due to the interstitial cobalt that remains between the diamond

grains:

- Thermal-Physical: A mismatch in the coefficient of expansion (COE) between the

residual cobalt and surrounding diamond matter as the cutter heats up (during

drilling/dysfunction).

- Thermal-Chemical: The regraphitization of the diamond due to high temperatures

(1200°C) without the associated pressure, as well as oxidation (875°C) if there is oxygen

present (Sneddon 1988).

Thermal-physical failure occurs when the cobalt expands and puts tensile stress on the

diamond bonds, inducing small stress fractures within the diamond face. Regraphitization weakens

the diamond-diamond bonds. It is also worth noting that leached cutters tend to be weaker, in terms

of initial crack formation due to mechanical stress, when compared to unleached cutters. The

removal of the cobalt, results in less “support” for the brittle diamond, increasing its propensity to

crack. However, the removal of the cobalt also reduces the thermally induced stresses.

3.1.5.1 Transitional and Thermal Mechanical Wear

As mentioned in Section 3.1.1, cutter wear goes through three distinct stages; smooth wear,

transitional wear and thermal mechanical wear. Transitional wear is the point at which the

diamond starts to regraphitize and oxidize due to increased thermal load. Thermal-mechanical

23

wear is the point at which the diamond to diamonds bonds break. Accelerated grain pull out will

be observed, leading to crack formation, and then chipping and spalling. See Figure 12.

Diamond wear is also influenced by the drilling fluid used. Anecdotal evidence suggests

more accelerated wear with synthetic based muds (SBM) compared to water-based muds (WBM).

This has been attributed to the higher thermal capacity of water muds that keeps the cutters cooler.

3.1.5.2 Spalling

Although spalling can be mechanical in origin (normal damage), it has been shown through

laboratory tests that a spall crack almost always initiates at the leach boundary. This is the interface

between the leached and unleached diamond (“Technical Summary: Drill Bit Dull Grading”,

2020). Under thermal loads, the unleached layer will start to crack first, as it is less thermally stable

(due to higher concentrations of interstitial cobalt.) The micro-fractures that form then consolidate,

and propagate into the mechanically “weaker” leached layer, causing a spall. Thermal spalling will

(a) (b) Figure 12 - (a) Micro-spalls along wear flats and, (b) Spalling, due to thermal stresses

(Image courtesy of P. Pastusek, ExxonMobil)

24

typically occur along the edge of a wear scar and be surrounded by similarly damaged cutters.

However, if flaking of the diamond table (spalling) is observed away from the wear flat, it is likely

that there has been subsurface crack growth (Figure 13). Both spalling and delamination can have

thermal or mechanical origins and it can be difficult to determine which of these stresses is the

primary cause of failure. It is essential therefore to observe the surrounding cutters in order to

determine the initial cause of failure.

Figure 13 - Diamond table flaking away from primary wear flat

(Image courtesy of P. Pastusek, ExxonMobil)

25

A cutter with a deep spall showing little wear would suggest mechanical failure due to

excessive normal load (Figure 14c). Also, mechanical damage tends to generate larger spall flakes

whereas thermal damage tends to generate smaller spalls close to the wear flat. A spalled cutter

with a wear flat, surrounded by other similarly damaged cutters, suggest a failure due to thermal

load (Figure 14b). As wear flats develop, thermal loads on the cutters increase. Regraphitization

will also cause accelerated wear and the damage becomes a self-perpetuating cycle. As a result

micro-spalling/chipping (Figure 14 a) can occur once a significant wear flat has developed (half

of a cutter). This is different from traditional larger spalling due to normal loads that can occur

with little wear.

(b) (c) (a)

Figure 14 - (a) Micro-spalls along wear flats; (b) Spalling of thermal origin; (c) Green cutters

surrounding a deep spall, suggests mechanical failure due to overload in the normal

direction (Images courtesy of P. Pastusek, ExxonMobil and Santos Ltd.)

26

Residual stresses the exist in the cutter post sintering can also lead to diamond table fracture

when cutters are exposed to high thermal loads (due to wear flats). These residual stresses can also

influence the direction the fracture propagates through the cutter.

During sintering, PDC’s are exposed to extremely high pressures and temperatures (~0.8 –

1.2 million psi and ~2600oF) (Bellin et al., 2010). Diamond powder of varying grain sizes is packed

against a tungsten carbide (WC-Co) substrate. Pressure is first applied followed by temperature.

The cobalt in the substrate melts and is squeezed into the pore space within the compacted

diamond/graphite powder mix. Here, the cobalt acts as a solvent to dissolve the graphite and

diamonds which then precipitate as polycrystalline diamond with diamond-to-diamond bonds.

Once the diamond table is fully sintered, the cutter is first cooled, then depressurized (to avoid

regraphitization).

Sintering introduces residual stresses into the system. As the cutter is cooled and pressure

is released post sintering there is a mismatch between the thermal expansion of the diamond table

and substrate. With cooling the carbide shrinks more than the diamond table. This leads to the

creation of a compressive residual stress in the diamond table and tensile stress in the substrate.

The compression on the diamond is beneficial for increasing cutter toughness (Bertagnolli and

Vale, 2000). However, the outside edge of the cutter is in tension, weakening this region of the

cutter. These stresses can be modified based on the pressures, temperatures, and ramp rates used

during production. Also, extensive FEA modelling and research is done to alter these local residual

stresses by optimizing NPI designs (Bertagnolli and Vale, 2000).

27

Understanding that residual stresses exist in cutters can help decipher the root cause of

observed thermal damage. The deep spalling and “cat eye” cracks shown in Figure 15 are the result

of high residual stresses. These cracks are associated with thermal loading, and are seen radiating

away from the wear flats, following the direction of the residual stresses. The direction in which

the crack travels is a function of the residual stresses, which can be affected by different NPIs

(design, height of NPI features, etc.). Often they will follow the circumference of the cutter just a

few millimeters away from the chamfer.

Figure 15 - Cat eye cracks radiating from wear flats (Image courtesy of Konstantin Morozov)

28

3.1.5.3 Heat Checking

Another common, easily recognizable form of thermal damage is heat checking. Heat

checking is a result of repeated heating (due to rubbing) and quenching of the cutter (by the drilling

fluid). When quenched, the surface contracts while the remaining substrate is still hot. As the cutter

is repeatedly heated and quenched, the surface shrinks faster than the bulk substrate underneath

and a shallow (~0.010 inch deep) hexagonal pattern of surface cracks form (Figure 16). This most

commonly occurs in hard, small grained, nonabrasive formations such as shale and limestone. Due

to their hardness without abrasiveness, these formations generate heat that is not carried away in

the wear particles. When drilling abrasive formations, the carbide wears and the particles generated

are able to dissipate and “carry” away the generated heat and thus heat checking is less likely to

occur. The cracks themselves can be more pronounced perpendicular to the direction of sliding

due to the frictional loading “pulling” the cracks apart perpendicular to the direction of motion.

Figure 16 - Heat checking on a cutter (Image courtesy of P. Pastusek, ExxonMobil)

29

3.1.6 CORROSION

Cutter damage due to corrosion is a result of stresses and chemical reactions within the

cutter substrate. There are multiple causes of corrosion and both relate to the cobalt within the

tungsten carbide substrate.

During sintering cobalt sweeps into the diamond creating a cobalt deficient zone, or

denuded zone, directly behind the diamond table (usually ~1 mm). The cobalt content of this region

can drop from ~13% to ~9%. This increases the residual stresses in the region. The highest residual

stresses are seen directly behind the diamond table where the substrate is in tension (Bertagnolli

and Vale, 2000). As a result, stress induced corrosion (the higher the stress, the faster the corrosion)

can cause preferential degradation in this region (Figure 17).

Severe corrosion weakens the substrate that supports the diamond table. Once there has be

sufficient carbide loss diamond breakage and further cutter damage can occur. Corrosion alone is

usually not a life limiting event for PDC cutters. However, the corrosion zone is more susceptible

to fluid erosion which can then reduce the diamond table support and thus making it more

susceptible to breakage.

Evidence of corrosion on cutters should also be used as a diagnostic for all elements in the

hole at the same time. If it is seen on the cutters it is likely also occurring on the drill pipe, BHA,

motor rotors and other components. This can significantly reduce their life.

Furthermore, the remaining cobalt in the tungsten carbide substrate can oxidize in low PH

environments. This is most commonly seen in wells with high H2S and CO2, and oxygen rich muds.

The effects of corrosion due to mud conditions (Figure 18) can be countered by sufficient amounts

of oxygen scavenger as well as corrosion inhibitor.

30

Figure 18 - Corrosion due to substrate oxidation (Image courtesy of P. Pastusek, ExxonMobil)

Figure 17 - Stress induced corrosion/erosion (Image courtesy of P. Pastusek, ExxonMobil)

31

3.1.7 EROSION

Erosion is due to fluid entrained particles removing the carbide substrate and blade

material. Unlike wear scars that show clear striations, indicating the direction of motion, erosion

tends to be “soft” and “cloudy in appearance (Figure 19) without an obvious surface to wear

against.

Erosion becomes an issue when the material loss is enough that it reduces support for the

diamond table under load, at which stage it is possible to chip, break, and lose cutters. Although

erosion does not tend to be life limiting in terms of drilling, it does affect the ability to

refurbish/repair used bits, increasing the associated costs.

Figure 19 - Examples of substrate, matrix and steel erosion (far right) (Images

courtesy of P. Pastusek, ExxonMobil)

32

High local velocities and turbulence around a cutter and high solids content will cause more

rapid erosion. Computational fluid dynamics (CFD) modelling can often be used to reorient

nozzles to limit or reduce the local velocity and associated cutter erosion. As a rough guide, local

velocities greater than 50 ft/sec tend to quicker erosion. Higher mud solids also create more erosion

due to the abrasive particles present the mud. As noted above, erosion is commonly seen along

with corrosion. If erosion is life limiting, local velocities, solids content, and corrosion should be

considered as a potential root causes.

33

3.2 Damage and Wear Progression

There are multiple ways and scenarios in which a bit can fail but from a high level the

progression of PDC failure is outlined in Illustration 2.

How a bit/BHA behaves and subsequently wears downhole are functions of various factors

including drilling parameters, BHA design, bit design, wellbore trajectory as well as formation

strength (bit rock interaction.) Regardless of these variables, there are generalizations that can be

made about bit wear and its progression. In the absence of drilling dysfunction, a cutter will wear,

then chip or break. If a cutter does chip or break (before it wears,) it is generally due to some kind

of impact damage due to vibration.

Cutter load is a function of contact area and rock strength. Contact area decreases with

increased cutter density (i.e., through the use of back up/secondary cutters and increased blade

count) and thus tends to decrease with distance from the center. As the gauge trimmers tend not to

DAMAGED CUTTER

THERMAL

MECHANICAL

CHEMICAL

LOST CUTTER BIT BODY DAMAGE

Illustration 2 - High level PDC wear progression from damaged cutter to bit failure

34

engage with the formation, it can be assumed their contact area is minimal. For a constant WOB,

the higher the cutter density the smaller the contact area per cutter, and therefore the smaller the

individual load on each cutter (Figure 20).

For a given RPM, the cutters at a greater radius (from bit center) will travel at a faster

velocity and thus have a larger sliding distance per revolution than the cone cutters. As a result,

wear generally commences in the outer nose/shoulder region, where the cutters are doing the most

work. Once wear flats develop drilling efficiency reduces. Rather than shearing the formation, the

cutter will commence to crush the formation (Bruton et al., 2014). The increase in friction coupled

with the change in the residual stress distribution, created by the growing wear flat, leads to

increases in thermal load and thus accelerated cutter degradation. It is common to see delamination

of the diamond table after more than 50% of the cutter has been worn. Once the diamond table is

Figure 20 - Contact area of a typical cutter, on center rotation with no vibration. The

contact load on the cutter face is a function of the formations confined

compressive strength (Pastusek et al., 2018)

35

lost the softer substrate and matrix material will cause accelerated wear leading to catastrophic bit

failure.

Once a cutter is severely damaged or lost it imbalances the load distribution across the

remaining intact cutters. As the bit is rotated, if one cutter is damaged, the cutter in the following

radial position is doing more work. The result is a knock-on effect, whereby once one goes, it is

not long before the others follow (Timonin et al., 2017.) At this stage due to the altered distribution

load more chipping and tangential damage (structural overloading) is seen and the remaining

cutters degrade at an accelerated rate.

Wear is not the only damage experienced by PDC bits. Tangential and normal damage are

also common, especially if there are interbedded formations and dysfunction present. Damaged

cutters also develop wear flats, and will tend to follow the aforementioned degradation process.

Once all the cutters at the same radial position are damaged, ring out (RO) will commence

(Figure 21). Ring out is by far one of the most common types of drill bit failure, as it is caused by

the systematic degradation of the cutting structure. The location of the ring out depends on where

the initial damaged occurred within the cutting structure. Bits most commonly ring out on either

the shoulder or nose. Coring occurs when the cone of the bit fails (Figure 22). Wear is less common

in the cone region of a bit, and damage in this region is more likely to be the result of impact

(normal) damage or structural overload (tangential fracture). Cone cutters have the highest load

per cutter due to the low cutter density in the center of the bit and are the most susceptible to

structural overload due to excessive WOB. It is generally recommended to run three or more blades

to the center of a bit, as opposed to two, to increase cutter density and reduce the risk of structurally

overloading the cone cutters.

36

Figure 21 - Examples of PDC ring out on the shoulder (left) and nose (right)

Figure 22 - Examples of two and three blade core out (Left image courtesy of Marathon Oil)

37

4. WORKFLOW DEVELOPMENT

The developed workflow consists of three steps:

1. Calculate the median factor value each stand drilled. This will enable the

identification of the drill bit point of failure.

2. Once the point of failure has been identified, observe the corresponding surface data.

Determine whether dysfunction or other failure mechanisms can be identified that

would corroborate point of failure.

3. Conduct forensic analysis of dull photos and identify / validate root cause of failure.

In order to identify the point of failure, we need to be able to recognize trends in the wear factor

data. This can be achieved by understanding what the metric represents and combing that with

knowledge regarding how PDC’s degrade.

In 1986, Glowka and Stone likened the volumetric wear seen by a PDC cutter in the absence

of thermal effects, to that of a metal specimen travelling across an abrasive surface. The basic

linear relationship can be expressed as:

𝑉𝑤 ∝ 𝐹𝐿𝑠 (2)

Where Vw is volumetric wear, F is load and Ls is the sliding distance, the distance travelled by

the specimen. This relationship can be rewritten in a different form as shown below:

𝑊𝑒𝑎𝑟 𝑓𝑎𝑐𝑡𝑜𝑟 (𝑟𝑒𝑣

𝑓𝑡∙ 𝑘𝑙𝑏) = 60 ∙

𝑅𝑃𝑀𝑏𝑖𝑡

𝑅𝑂𝑃∙ 𝑊𝑂𝐵 (3)

WOB can simply be interpreted as the load acting on the bit. The remaining terms on the right-

hand side of the equation act as a pseudo “sliding distance” and represent the revolutions required

38

to drill 1 ft (unit) of formation. If the revolutions required to drill 1 ft (unit) of formation increase,

the overall sliding distance of the bit increases. Depth of cut (DOC), not to be confused with

contact area, is the penetration per revolution. It is often used as a performance metric to help

identify PDC dysfunction and can be written as:

𝐷𝑂𝐶 (𝑖𝑛

𝑟𝑒𝑣) =

𝑅𝑂𝑃

𝑅𝑃𝑀𝑏𝑖𝑡∙

1

5 (4)

and thus Equation 3 can be rewritten in terms of DOC as:

𝑊𝑒𝑎𝑟 𝑓𝑎𝑐𝑡𝑜𝑟 (𝑟𝑒𝑣

𝑓𝑡∙ 𝑘𝑙𝑏) = 60 ∙

𝑊𝑂𝐵

𝐷𝑂𝐶 (5)

The “wear factor” presented here is not a quantitative metric describing the physical

volumetric wear encountered but merely an indicator that can be used to track a departure from a

baseline. As sliding distance increases, the wear factor will increase. In hard, abrasive formations

this can be attributed to smooth wear as a result of abrasion. However, more often than not wear

flats develop as a result of an earlier damage event. As the metric increases, it is indicative that the

bit has simply been damaged and is continuing to wear/degrade.

To understand the trends in the data we must understand how all the variables interact. The

relationship between WOB, RPM and ROP is that an increase in either RPM and/or WOB should

lead to a proportional increase in ROP, as per the founder curve. In a case of idealized drilling,

where there is no damage, no wear and a homogenous formation with no dysfunction, the metric

would remain constant for a given set of parameters.

However, in a homogeneous formation an increasing linear relationship may be noted

between the metric and depth. As the sliding distance increases the cutter dulls and small wear

flats develop. The observed linear relationship is equivalent to the “accumulated wear” noted by

39

Liu et al. (2018). They also observed failure due to “fast worn out”, which they identified as a

sharp departure from a “low range” wear value. They attributed these rises to “hard stringers.” A

sharp departure from a steady linear increase could be a hard stringer but it could also reflect a

catastrophic failure of the bit or some other downhole component. To merely attribute this

departure to a hard stringer, fails to capture nuances of PDC wear and is one of the shortcomings

of their approach.

Other trends expected in the data would include non-linear patterns and exponential

increases. These trends emerge in conjunction with increasing wear flat size. Cutter thermal loads

increase as wear flat area increases. This accelerates cutter degradation and the associated thermal

damage self-perpetuates. As the model does not consider cutter temperature or wear flat size, it is

important when analyzing the data to not forget the implications of wear flat area and cutter

temperature.

The size of a wear flat will also affect and sensitivity of WOB on the wear. As wear is a

function of sliding distance, increasing the penetration per revolution (DOC) will reduce total wear

recorded for a given footage. This is statement that holds true as long as the cutter is below the

critical diamond temperature (temperature at which degradation will occur.) If WOB is high early

in the run, the wear flat is small and cutter temperature is likely to stay below critical. However,

if the cutter is run at low penetration per revolution (DOC) it will slide more for the footage drilled

and the corresponding wear flat will increase in size. Adding WOB now, with a larger wear flat

will dramatically increases the wear flat temperature and total cutter wear (due to increased thermal

load etc.). Given this relationship, as discussed by Dupriest et al. (2020), to optimize bit life WOB

and DOC should be increased to the structural limits of the cutters. This will give the lowest sliding

distance and thus wear for a given footage drilled.

40

By understanding how PDC wear progresses and the relationship between cutter temperature

and wear trends in wear factor versus depth can be recognized. The instantaneous wear factor value

calculated is important. It is a snapshot in time for the bit condition relative to a baseline for a

given set of parameters and formation properties. However, trends seen within the data are equally

valuable as they show how the bit is failing, and can help pin point catastrophic failure events.

Observing a sharp departure in the wear factor from a base line value indicates there is

something wrong. When plotting median wear factor for a given stand, it removes noise that can

be present in 1 Hz data. This also allows the stand of failure to be easily identified and the

corresponding surface data pulled for further investigation.

An increase or departure in the wear factor from baseline would be caused by either a sudden

drop in ROP or a large increase in WOB and RPM without a corresponding increase in ROP. There

are many reasons this could occur including:

- Hard stringers

- Dysfunction

- Downhole tool failure

- Bit balling

- Bit failure

These events are not mutually exclusive. For example, hard stringers could cause dysfunction

that leads to bit failure but conversely dysfunction could occur and not cause bit failure (i.e. in

formations <20k psi UCS). Not all of these events are easy to detect in surface data. However

when conducting root cause analysis it is important to review surface data for any indications of

what caused the departure from baseline. Some examples of trends include:

41

- Large sinusoidal fluctuations in torque are linked to changes in downhole RPM and are

indicative of stick slip. The presence of a saw tooth pattern within a torque channel is

evidence that full stick slip is occurring (Ertas et al. 2014).

- Bit balling often presents as a decrease in ROP and torque and an increase in stand pipe

pressure.

- Downhole motor failure, for example elastomer chunking, can present itself as a loss in

differential pressure and decreased ROP. Simultaneously, an increase in standpipe pressure

could occur if the drill bit nozzles become blocked.

- Bit/BHA whirl is notoriously hard to diagnose in surface data, but low DOC coupled with

hard formation could be an environment in which whirl occurs.

These are just a handful of examples of downhole events that could be inferred from surface

data. These events can all cause an increase in the wear factor but they may not cause bit damage.

Also, the absence of noticeable trends in the surface data does not necessarily indicate no

dysfunction or damaging event has occurred. This emphasizes the importance of utilizing bit

images and forensics when completing root cause analysis.

Once the surface data has been reviewed PDC dull photos need to be analyzed and the

different modes of damage (as discussed in section 3.1) need to be identified on the bit. By

identifying the modes of damage as well as their location on the drill bit, conclusions can be

made about the downhole environment in which they occurred.

42

4.1 Workflow Implementation

The wear factor was validated using a data set comprising of nine wells and 51, 8.75”

heel/lateral production runs. Surface electric drilling recorder (EDR) data alongside bit dull photos

were used to interpret the relationship between the wear factor and observed PDC wear.

The BHA’s designs across the wells were similar, with slight BHA variations in terms of

motor specifications. Each well was targeting the same formation, within the same field, although

there were variations of up to ~3000 ft TVD between the lateral sections of some wells. The lateral

sections were long, ~13,000 ft on average. The drill bits analyzed for this work were supplied by

the same vendor, and were 8.75” 7 blade PDC’s. There were 6 different cutter types used as well

as 4 different frames, although the majority of runs were completed with the Frame 1 (Figure 23).

All runs were within the same formation, at varying true vertical depths. Although, the

formation strength was not recorded, it is known to be and extremely hard, abrasive shale, requiring

multiple runs (upwards of 15 BHA’s to reach total depth (TD). The shale itself was made up of

two lithofacies, an upper region that was a less clay rich (~10%), clean siltstone (quartz rich) and

suspected to be harder and a lower region that was more clay rich (~20%+) which was suspected

to be softer due to higher amounts of illite. The overall hardness and high quartz content of the

formation, regardless of lithofacies, represents a highly abrasive environment.

43

The 1 Hz surface EDR data was processed and filtered. Only data where the bit was on

bottom was analyzed. Sliding was filtered out, as to ensure only rotary drilling was considered.

The sliding interval and time spent sliding was recorded for each run and no relationship between

dull condition and sliding was recorded. Using rotary drilling only for this analysis, allowed for

the broad assumption that WOB recorded at surface, was in fact being exerted, to some extent, on

the bit downhole. Stand detection was run to isolate data from individual stands (~90 ft). To track

performance, basic statistics were run for each stand.

Frame 2 Frame 3 Frame 4

Frame 1

Figure 23 - Frame designs used in this study

44

The wear factor was calculated using Equation 3. Once the data was filtered, WOB and

ROP were taken directly from the 1 Hz surface data. Bit RPM was calculated by the addition of

surface RPM and downhole RPM, where downhole RPM is calculated as:

𝐷𝑜𝑤𝑛ℎ𝑜𝑙𝑒 𝑟𝑜𝑡𝑎𝑟𝑦 (𝑅𝑃𝑀) = 𝐺𝑃𝑀 ∙ 𝑀𝑜𝑡𝑜𝑟𝑠𝑝𝑒𝑒𝑑 (𝑟𝑒𝑣/𝑔𝑎𝑙) (6)

GPM is the mud flow rate in gallons per minute. Unlike Liu et al. (2018) who used continuous

data, here the median wear factor values per stand were calculated. The median wear factor value

for each stand was then plotted versus measured hole depth. Using a median value for the analysis,

instead of plotting the 1 Hz data removed noise from the data. This made it easier to identify long-

term trends, the importance of which were previously discussed. Conclusions surrounding PDC

wear progression as well as root cause analysis were able to be inferred from these plots when

combined with PDC forensics.

45

5. RESULTS AND DISCUSSION

5.1 Results

The following graphs (Figure 24 – Figure 32) were constructed by plotting the median

wear factor for each stand drilled versus measured depth. Each curve on a plot represents a separate

run and each point is a stand (usually ~90ft). For each well, the runs are numbered sequentially

from left to right starting at 1. Gaps within the depth data represent runs where drill bits outside

this study were used and data was unavailable. Graphs that overlap and indicative of sidetracks

that were drilled due to hole trouble. Each run is annotated with a short comment describing the

final dull condition of the PDC or reason pulled. The dashed horizontal lines represent four

thresholds to estimate PDC dull condition, the calculation of which is discussed within the

following section.

For all wells there is a roughly linear relationship between measured depth drilled and wear

factor recorded. In some cases there is a departure from this relationship, seen through a sudden

exponential growth in the wear factor.

46

0

5,000

10,000

15,000

20,000

25,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 1 - West (N-S)

Bad wear

Shoulder impact damage

Bad RO, shoulder and cone damage

Slight nose and gauge damage but in good condition

Figure 24 - Well 1: Median wear metric value for each stand vs. measured hole depth and PDC bit dull description

47

0

5,000

10,000

15,000

20,000

25,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(rev

*klb

/ft)

Depth (ft MD)

Well 2 - West (N-S)

Cone damage,broken nose, almost RO

Worn with gauge damage

Gauge damage, worn, nose and cone (?) damage

Gauge damage, worn, nose and cone (?) damage

Very flat wear, gauge and cone damage

RO and cone damage

Slight gauge and cone damage

RO cone/nose, cone damage


48

0

5,000

10,000

15,000

20,000

25,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 3 - West (N-S)

Cored and worn Cone damage only, barely worn


49

0

5,000

10,000

15,000

20,000

25,000

30,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 4 - West (N-S)

Poor nozzle design, RO

Poor nozzle design, light wear only

Shoulder wear, RO nose/cone

Shoulder wear, RO nose/cone

Broken on shoulder

Broken nose, shoulder

Gauge spalling andnose/cone damage

Shoulder damage only

Poor nozzle design

Consecutive RO and/or commencing to RO

Figure 27 - Well 4: Median wear metric value for each stand vs. measured hole depth and PDC bit dulls showing inefficient nozzle placement (left),

and suspected stick slip/whirl damage (right)

Well 4 – Run 7

50

0

5,000

10,000

15,000

20,000

25,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 5 - West (N-S)

Different frame design, light damage. Rotary steerable with mud motor (?)

Light wear


51

Well 6 – Run 6 Well 6 - Run 5 Well 6 – Run 7 Well 6 - Run 8

0

5,000

10,000

15,000

20,000

25,000

30,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 6 - East (N-S)

Bad RO Downhole motorfailure (DMF)

Wear Wear

Start to RO, worse than Run 5

Wear


Start to RO (Run 5) Slight wear (Run 6)

Nose damage and wear (Run 4)

52

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 7 - East (N-S)

Bad shoulder RO

Shoulder damage, missing cone cutter

Basic wear

Bad RO Bad RO

Wear only Wear only Wear only, junk damage?No data


53

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 8 - East (N-S)

Bad RO

Moderate RO

Bad RO, nose damage Soft RO


54

0

5,000

10,000

15,000

20,000

25,000

14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ft MD)

Well 9 - East (NW-SE)

Gauge, cone damage

Bad RO

Bad RO

Bad RO


55

5.2 Discussion

The presented workflow and subsequent data analysis reinforced many of existing notions

about PDC wear and failure. Under normal drilling conditions, where smooth wear is the driving

mode of damage and formation homogeneity can be assumed, severity of bit wear is a function of

sliding distance. This relationship however is not necessarily linear. As previously discussed, as

wear flat area increases so does temperature. This holds especially true if WOB is also increasing.

0

10

20

30

40

50

60

70

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

17,000 18,000 19,000 20,000 21,000 22,000 23,000 24,000 25,000 26,000

RO

P (

ft/h

r)

rev/

ft*W

OB

(re

v*kl

b/f

t)

Depth (ftMD)

Well 7 - East (N-S)

Wear Metric ROP

Ring out Wear only

Figure 33 - Graph comparing wear metric and ROP for two runs from Well 7, as well as corresponding dull grades

56

The result is accelerated thermal wear of the diamond table. Once the harder diamond table is lost,

and the softer substrate/matrix material is exposed and PDC bit failure accelerates rapidly.

These relationships are clear when observing the results. In Figure 33 there are two

examples of the linear trend between measured depth drilled and wear factor. However, in the first

run of Figure 33 there is a departure from this trend at the end of the run. The exponential growth

in the wear factor signifies the point at which catastrophic PDC damage occurs. From this point

PDC bit failure is imminent and generally occurs within a few stands. Identifying this point of

failure can help with root cause failure analysis of the drill bit.

When observing the corresponding the PDC dull photos, it was clear that the final recorded

wear factor value, when not related to tool or another downhole failure, could be equated to the

severity of the PDC damage. It was possible to separate the wear severity into four buckets (Figure

34). All relevant sets of dull photos were split into these buckets and pull criteria was established.

Although the IADC dull grades were available for each run, the dull photos were the primary

means of determining damage severity. This is due to the ongoing issues regarding subjectivity

and inconsistencies with the IADC code. Table 1 shows for each bucket, the corresponding 𝑟𝑒𝑣∙𝑘𝑙𝑏

𝑓𝑡

value that represents the average value that would correspond to that degree of wear for the given

formation and BHA. An example of the dull grades and corresponding final recorded wear values

can be seen in Figure 29.

57

Figure 34 - Four buckets used to capture the various stages of PDC wear

Table 1 - Pull criteria for the given 8.75” PDC design

Once a bit dulls there comes a point where the cost/depth drilled exceeds an arbitrary limit,

whereby tripping becomes more economical than continuing to drill. This is when the decision to

pull an underperforming PDC is made. This calculation relies heavily on ROP. The wear factor

provides an additional assessment of bit performance to support the decision making surrounding

a bit trip. By normalizing ROP data with RPM and WOB, it more accurately identifies the point

(stand) of failure than ROP alone. An example of this can be noted in Figure 33. Two similar sharp

declines in ROP (highlighted by the red dashed line) are noted during the initial run. However only

Bit condition

Pull Criteria

(𝑟𝑒𝑣 ∙ 𝑘𝑙𝑏

𝑓𝑡)

1 – Slight wear (mild) 14,200

2 – Heavy wear (moderate) 16,000

3 – Broken cutters 17,900

4 – Ring out (RO) 20,000

1 – Slight wear

3 – Broken cutters

4 – Ring out 2 – Heavy wear

58

the second run can be attributed to catastrophic bit damage, as reflected by the exponential rise in

the wear factor. If we had pulled the bit based on the initial decrease in ROP, more than likely the

bit would have still been green.

The gradient of the corresponding curve can be used to identify drilling efficiency as well

as premature failure of the PDC bit, examples of which are seen in Figure 27. An immediate

exponential growth in both Runs 1 and 2, shown in purple in Figure 27, are representative of some

kind of inefficiency or dysfunction. On further inspection of the dulls, it was identified that the

frame design of these bits was a departure from those used in previous runs. Nozzle density was

shifted from the cone to the nose. This design change was an attempt to increase bit/cutter life by

directing mud flow to the shoulder and thereby increase cutter cooling. The result was a drastic

decrease in efficiency. The lack of nozzle placement in the cone resulted in cuttings pack off. This

design failure is immediately identifiable in the data from Run 1, and further reinforced in Run 2.

The wear factor, thus can also be used to identify deviations for the norm and highlight possible

drilling inefficiencies. This highlights the importance of considering the bit and BHA designs,

when reviewing the dull photos, in conjunction with the metric.

Runs 3, 4, 5 and 6, grouped by the red parenthesis in Figure 27 are representative of another

well-known PDC issue. In hard formation, once you ring out a PDC, or run under gauge, the

likelihood of premature bit failure in the subsequent run increases. This can be attributed to the

uneven load distribution across the cutters upon reentry (as well as possible associated

dysfunction.)

59

Illustration 3 outlines the genesis of PDC ring out in hard formation and the structural

overload seen by the nose cutters upon reentry. As drilling progresses, the nose and shoulder

cutters experience greater sliding distance per revolution than the cone cutters. They do more work

and experience higher temperatures than the gauge trimmers, due to their engagement with the

formation. As a result, these cutters wear quicker than the cone and gauge cutters. This is

particularly true if they are prematurely chipped or damaged through dysfunction or other means.

When a bit is run to the stage where it rings out it creates an irregular borehole pattern. At the base

of the hole it is possible for a ledge, the same depth as the ring out, to be created. Upon reentry,

given the profile of PDC bits, the nose cutters contact the ledge first. They take the full load

transferred from the BHA. In soft formation <20k psi UCS it is likely this ledge would be

inconsequential and the contact stress per cutter would be minimal. However within hard

formations it can become problematic as the contact stress per cutter is now much higher. PDC’s

are designed so the weight of the BHA is evenly distributed across all the cutters. If the weight

Illustration 3 - Genesis of PDC ring out in hard formation followed by structural overload of nose cutters

upon reentry

Normal Drilling Ring Out New bit - Cutter overload

60

distribution shifts it is possible to structurally overload the cutters resulting in tangential fracture

damage.

In Figure 27, the bit is rung out on Run 3, the “initial” run, as indicated by the wear factor.

Although the wear progression (gradient) is steep, it does not show immediate signs of PDC

failure, represented by more exponential growth. This exponential growth however, is noted on all

subsequent runs (run 4, 5 and 6).

Table 2 shows the differences in drilling efficiencies in runs directly after instances of PDC

ring out and mild/moderate wear (Bucket 1 and 2). Both cases saw decreases in the subsequent

interval drilled which was unexpected for the mild/moderate wear case. Regardless, the average

interval drilled post ring out was still subsequently less (~ -18%) than the interval drilled when

only mild wear was seen on previous runs. However, “average interval drilled” is not normalized

and does not consider on bottom time. Average rate of penetration (ROP) is a better parameter to

compare cases. The ROP results are the most telling. Changes in ROP for runs where the previous

run PDC condition was noted as mild/moderate (1 or 2) were virtually unchanged, for both sliding

and rotary drilling. Whereas, there was a significant performance decrease in runs directly

following a ring out. Although the results are promising, the sample space was relatively small,

and these concepts need to be further explored in future work. Nevertheless, there is a clear

relationship between ring out and decreased performance in subsequent runs. This highlights the

importance of developing pull criteria when operating in hard formations, especially where ring

out is expected.

61

Table 2 - Drilling efficiencies seen on runs after RO as well as after only mild/moderate wear

Figure 27 also highlights the use of the wear factor as a visual diagnostic tool to help

determine PDC root cause failure. The bit damage recorded on Run 7, as seen in the dark navy,

was recorded between mild and moderate as there were no broken nose/shoulder cutters. Looking

at the graph, after the 7th stand, (shown by the red marker,) there seems to be a marked decrease

in performance, suggesting whilst drilling the 7th stand, there was some event that caused

irreversible damage to the drill bit. This information can then be used to prompt further

investigation into the surface data to help determine the root cause of the decrease in efficiency.

Figure 35 shows the EDR data from this stand. There are two clear instances of erratic

torque, driven by top drive stall out, which could be indicative of downhole dysfunction. Figure

36 is a snapshot of the second torque event. Torque is stalling out at 30 klbs and exhibiting ~5kftlb

periodic swings at a frequency of 12 seconds. As a low frequency phenomenon, this frequency is

typical of stick slip. Without downhole data it is not possible to determine if it is the bit or the

BHA exhibiting stick slip. It can only be inferred stick slip is occurring somewhere downhole. The

torque signal does not match the saw tooth pattern seen in surface data during full stick slip (Ertas

et al., 2014), when the bit/BHA comes to a full stop. However, torsional oscillations can still be

RO Mild/Moderate wear (1 and 2)

Initial

run

Subsequent

run

%

change

Initial

run

Subsequent

run

%

change

Average interval

drilled (ft) 1444 824 - 43% 1652 1237 -25%

Average rotary ROP

(ft/hr) 36 30 - 16% 32 31 -3%

Average sliding

ROP (ft/hr) 17 15 - 11% 18 18 -1%

62

damaging and for the given drill pipe size, torque swing and depth, it is possible that the bit/BHA

is on the verge of undergoing full stick slip.

Figure 35 - Surface EDR data from 7th stand of Run 7 from Well 4 showing instances of erratic torque

Erratic torque

63

Figure 36 - Snapshot from surface EDR data from 7th stand of Run 7 from Well 4 showing possible stick

slip event

12 second period

suspected stick slip

64

Once this region of dysfunction is identified using the wear factor we can postulate what

has caused the damage to the drill bit. Figure 37 shows three consecutive blades from the bit, the

other four exhibited minimal wear (refer to Appendix 7.5.7). Uneven/one sided wear exhibited on

bits and BHA’s is indicative of forward whirl. The jump rope motion seen during this type of

dysfunction loads one side of the bit/BHA more than the other. This is because the same location

on the bit/BHA continually impacts the borehole (Pastusek 2019). On all three blades, significant

normal damage is seen on the gauge cutters, as well as shallow spalling along consecutive cutters

on the shoulder. This damage is likely a combination impact and thermal damage. The smaller

micro spalling along the wear flats, could simply have arisen from increases thermal loads due to

the growing wear flats. The analysis of surface data alongside bit dulls suggests the stick slip was

coupled with whirl.

Figure 37 – Suspected whirl damage on gauge cutters from Well 4, Run 8

65

5.3 Additional Observations

5.3.1 CHARACTERIZING WHIRL DAMAGE

Irrespective of the wear factor additional observations were made from reviewing the dull

photos that require further investigation. 24% of the bits exhibited gauge damage and 16% of the

runs exhibited cone and gauge damage, an example of which is shown in Figure 38.

This damage has been attributed to whirl but requires further investigation for validation.

Whirl is notoriously hard to determine from surface data and is commonly attributed to low DOC

within hard formations. During whirl there is an increase in lateral vibrations and it is common to

observe normal (impact) damage on the gauge. Although there are different types of whirl

(forward, backward, chaotic), all types of whirl are characterized by off center rotation of the bit.

As the bit whirls, it can create spiral borehole patterns (Pastusek, 2019). It also can create a small

nodule on the bottom of the hole as the bit gears around the wellbore, much like a spirograph. In

soft formations, this does not pose an issue and the ledge can simply be knocked away without

Number 1 cutter damage Gauge cutter damage

Well 1 – Run 4

Figure 38 - Example of gauge and number one cutter damage

66

much fanfare. However in hard formations it can sideload a cutter and cause it to fracture. It is

possible that this is how the cone cutters were damaged.

High angle back rake Low angle back rake

Figure 39 - Low versus high angle back rack on gauge cutters

67

When analyzing cutter damage on the gauge it is important to note cutter back rake angle

(Figure 39). When the diamond table impacts the borehole wall, the cutter is less likely to spall if

the diamond table is in compression versus tension. A high back rake angle will put the diamond

in compression upon impact, making it less susceptible to damage. We cannot conclude, just

because a cutter is undamaged that a certain dysfunction did not occur. It is important to consider

elements of PDC design when reviewing the drilling data and dull images.

68

5.3.2 IMPLICATIONS OF WELL ORIENTATION

The wear factor successfully reflected the dull condition for the vast majority of runs from

Well 1 through to Well 8. However for Well 9 (Figure 32), for 3 out of 4 runs the metric returned

values which were highly erroneous for the given dull condition. All 3 runs reported values that

would suggest light wear. However they all had significant ring outs, the wear factor was too low

for the reported damage. This suggested that as PDC damage increased, the wear factor was not

increasing at the same rate as seen in previous wells.

With all things similar, in regards to bit and BHA what was different between Well 9 and

Wells 1 - 8 was its orientation. Wells 1 – 8 were drilled north to south and Well 9, north west to

south east. Although detailed geomechanical studies were not available for this work, literature

suggest these wells lie within a normal/strike slip faulting regime (Figure 40) where Sv~SHmax >

Shmin, with SHmax running east-west. It is possible that different drilling dynamics associated with

borehole break out or strength anisotropy resulted in lower wear factor values for a given damage

profile for these runs. This observation needs to further investigated.

Figure 40 - Schematic showing normal/strike-slip faulting regime (Ma and Zoback, 2017)

69

6. CONCLUSIONS AND FUTURE WORK

A PDC wear factor was implemented to successfully track PDC wear and degradation

whilst drilling in hard formations, validating observations by Liu et al. (2018). By combining this

data with PDC dull photos we were able to define clear pull criteria based on PDC damage state,

as opposed to IADC dull code. It was also shown that the point of absolute PDC failure can be

determined from the exponential increase in the wear metric value.

By understanding PDC cutter damage modes forensic analysis of damaged bits can be

executed. Once the stand of bit failure is successfully identified, it is possible to determine when

and why the bit failed with the help of surface data. For example, fluctuations in torque that

coincide with an increase in the wear factor can be indicative of stick slip related damage. Once

observing the corresponding dulls, the presence of gauge spalling due to impact suggests whirl.

Thus conclusions such as, stick slip coupled with whirl may have been the initial damage event

that caused eventual PDC failure. This type of analysis can be completed for all runs with

significant decreases in drilling efficiency to improve future runs through drilling parameter

optimization, bit selection and BHA design.

Other interesting observations were recorded whilst conducting further forensic analysis of

the damaged PDC’s. The data suggests that hard ledges created when a PDC rings out can lead to

premature failure of subsequent runs. This highlights the importance of tracking PDC condition in

real time and pulling the PDC’s before unfavorable borehole patterns emerge. When ledges form,

upon reentry, it causes an uneven distribution of weight on the PDC cutters. The loaded cutters

experience structural overload and tangentially fracture or break. This accelerates both cutter and

catastrophic PDC failure.

70

The presented workflow is a cheap and effective means to better understand and track PDC

failure. By using a simple combination of surface data and PDC forensics, root cause analysis of

drill bit failure can be successfully conducted. Implementing this metric in real-time would help

with operational decisions and improve drilling efficiency.

6.1 Future Work

6.1.1 DRILLING STRENGTH

The concept of drilling strength was first presented by Detournay and Defoury (1992). They

showed how the rock bit interaction could be described by two components: rock cutting and

frictional contact. They expressed the drilling response in terms of specific energy and drilling

strength, with drilling strength defined as:

𝐷𝑟𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑟𝑒𝑛𝑔𝑡ℎ = 𝑊

𝑎𝛿 (7)

Where W is weight on bit, a is bit diameter and δ is depth of cut per revolution which is given by;

𝛿 =2𝜋𝑣

𝜔 (8)

and ω is the angular rotational speed of the bit, and v the rate of penetration. Substituting equation

8 into 7, drilling strength can be expressed as:

𝐷𝑟𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑟𝑒𝑛𝑔𝑡ℎ = 𝑊 ∙ 𝜔

2𝜋 ∙ 𝑣 ∙ 𝑎 (9)

This relationship is also known as axial energy, which is the same as the presented wear factor but

normalized for bit diameter. This metric could be applied to the given data set but as all runs were

71

the same bit diameter, it would have minimal effect. By normalizing the equation for bit diameter

it allows data from various hole sizes to be compared. Although it is still important to consider any

other factors that could affect ROP such as drill pipe size, BHA design, formation heterogeneity,

deviation etc. work could be done comparing drilling strength values and corresponding dulls over

the course of multiple runs of varying sizes in order to investigate any relationships.

6.1.2 DOWNHOLE SENSORS

The observations made in this study in relation to premature PDC failure and subsequent

ring out need to be further investigated. The sample space for this work was small and a larger

field study needs to be conducted. Not all types of drilling dysfunction can be easily inferred from

surface data. Further validation of the model and associated forensic analysis needs to be

completed. To confirm whether the premature bit failure observed was indeed caused by damage

due to structural overload of cutters and not other downhole dysfunctions, such as whirl (due to

low DOC and BHA/bit instability), when tagging bottom, high frequency data should be compared

with the metric and dull photos. Furthermore, the use of downhole sensors would be able to help

confirm the root cause of the gauge and number one cutter damage that was frequently observed.

6.1.3 REAL TIME ANALYSIS

This study was not completed in real time. Historical EDR data was combined with dull

photos to identify relationships and validate the metric. The goal of this work was establish a

workflow to determine root cause of drill bit failure from surface data and bit dull photos. The

presented metric and associated pull criteria need to be implemented in real time in order to

evaluate their effectiveness in supporting operational decisions. Also as previously discussed, Liu

et al. (2018) commented that the wear metric was a better predictor of PDC damage state than

72

MSE and bit aggressiveness and it would be prudent to use the real time trials to test these

observations. This would further support the use of the “wear factor” versus existing mechanics-

based metrics whilst tracking PDC damage.

6.1.4 IADC DULL GRADING

The current IADC dull code system was established in 1987 The purpose of the dull grading

system has always been to record the condition of the bit for future reference in a way that is easy

and straight forward to communicate (Brandon et al., 1992). Although the IADC system outlines

the appropriate manner in which to measure and average the damage across cutters and regions,

the process is still highly subjective. Herein lies its weakness as a classification system. Without a

standardized/automated process, valuable forensic data is poorly communicated and lost. Using

the IADC dull grade to compare bit performance becomes virtually impossible, especially if the

bits have been graded by different individuals.

Alongside the IADC dull grade, the second most common method to evaluate bit

performance is post-run images. Various instructions have been issued by service companies and

operators, outlining the proper procedure to capture dulls. Nevertheless, poor conditions on site as

well as a lack of education (in terms of blade numbering, image capturing etc.) quite often results

in low quality, incomplete image sets. This was an ongoing issue during this study. Much like the

highly subjective IADC dull grade, the result is a poor-quality data set from which it is difficult to

make critical operational decisions.

As technology and machine vision has improved over the years, there is no reason as to why

the IADC system cannot be automated and/or improved, to provide a higher fidelity data set. This

work has already commenced with Ashok et al. (2020) showing how machine learning can be used

to automatically quantify cutter damage and grade PDC’s from 2D images. The industry now

73

recognizes the shortfall in the current system and work is under way to update the system to make

it more meaningful for performance optimization and forensic analysis. A classification of cutter

damage has been presented within this thesis. The next step in this process is to characterize wear

patterns observed on used PDC drill bits, through the correlation of these patterns with downhole

drilling environments. This work forms the basis of a case study correlating surface data to PDC

wear as well as PDC ring out. Additional case studies that relate various types of PDC damage to

downhole drilling conditions need to be compiled and presented to the industry.

74

7. APPENDICES

7.1 Appendix A – Well orientations, locations and motor speeds

*Motor speeds were not provided and had to be assumed from offset data

Table 3 - Well names, orientations, locations and motor speeds

.

Placeholder Orientation Location (Field) Motor speed

(rev/gal)

Well 1 N-S West 0.23




Well 5 N-S West 0.2

Well 6 N-S East 0.25*



Well 9 NW-SE East 0.25

75

I O MD LOC B G OD RP

2 4 WT A X 2 WT PR

Figure 41 - Well 1, Run 1: Dull photos and grading

7.2 Appendix B – Well 1: Dull Photos and Grading

7.2.1 RUN 1

76


7.2.2 RUN 2


1 2 WT A X 1 WT

77


7.2.3 RUN 3


4 8 RO S X 1 CT PR

78


7.2.4 RUN 4


1 3 CT S X WT PR

79

7.3 Appendix C – Well 2: Dull Photos and Grading

7.3.1 RUN 1


80

7.3.2 RUN 2


81

7.3.3 RUN 3


1 3 WT S X BT PR


82


7.3.4 RUN 4


2 4 WT S X CT PR

83


7.3.5 RUN 5


1 4 WT S X 1 CT PR

84


7.3.6 RUN 6


2 4 WT S X 1 CT PR

85

7.3.7 RUN 7


2 3 CR N X 1 WT PR


86

7.3.8 RUN 8


1 1 BT G X CT TD


87

7.4 Appendix D – Well 3: Dull Photos and Grading

7.4.1 RUN 1 I O MD LOC B G OD RP

6 4 BT A X CR PR


88


7.4.2 RUN 2


1 2 CT A X WT PR

89


5 3 CT S X I RO PR


7.5 Appendix E – Well 4: Dull Photos and Grading

7.5.1 RUN 1

90

7.5.2 RUN 2


1 2 WT S X I NO PR


91

7.5.3 RUN 3


2 4 RO A X WT PR


92


7.5.4 RUN 4


6 3 RO C X WT PR

93


7.5.5 RUN 5


1 3 WT S X BT PR

94


7.5.6 RUN 6


2 3 WT G X 1 BT PR

95


7.5.7 RUN 7


1 2 WT S X CT PR

96


7.5.8 RUN 8


1 2 WT S X CT HP

97


1 2 CT S X WT PR


7.6 Appendix F – Well 5: Dull Photos and Grading

7.6.1 RUN 1

98


7.6.2 RUN 2


1 2 WT S X 1 CT PR

99


7.7 Appendix G – Well 6: Dull Photos and Grading

7.7.1 RUN 1

100


7.7.2 RUN 2

101


7.7.3 RUN 3

102

7.7.4 RUN 4


103

7.7.5 RUN 5


104

7.7.6 RUN 6


105

7.7.7 RUN 7


106

7.7.8 RUN 8


107

7.7.9 RUN 9

7.8


108


1 8 RO S X 1 CT PR


Appendix G – Well 7: Dull Photos and Grading

7.8.1 RUN 1

109


7.8.2 RUN 2


1 2 WT S X 1 CT PR

110


7.8.3 RUN 3


1 2 WT S X CT PR

111


7.8.4 RUN 4


1 8 RO S X WT PR

112

7.8.5 RUN 5

- No photos available

- Grading: 1-4-CT-S-X-I-WT-PR

113


7.8.6 RUN 6


2 5 RO S X I WT PR

114

7.8.7 RUN 7


2 3 WT S X 1 CT PR


115


7.8.8 RUN 8


1 2 WT S X CT PR

116


7.8.9 RUN 9

117


2 4 WT M X RO PR


7.9 Appendix H – Well 8: Dull Photos and Grading

7.9.1 RUN 1

118


7.9.2 RUN 2


2 8 RO S X 1 CT PR

119


7.9.3 RUN 3


8 6 RO N X WT PR

120


7.9.4 RUN 4


6 8 RO S X BT PR

121


7.10 Appendix I – Well 9: Dull Photos and Grading

7.10.1 RUN 1

122


7.10.2 RUN 2


3 2 RO N X FC PR

123


7.10.3 RUN 3


1 2 FC S X 1 CT PR

124


7.10.4 RUN 4

125

8. REFERENCES

Application specific design and PDC failure modes. (2020). [PowerPoint presentation]. Internal

US Synthetic presentation: unpublished.

Ashok, P., Vashisht, P., Kong, H., Witt-Doerring, Y., Chu, J., Yan, Z., van Oort, E. & Behounek,

M. (2020, October). Drill Bit Damage Assessment Using Image Analysis and Deep

Learning as an Alternative to Traditional IADC Dull Grading [Paper presentation]. SPE

Annual Technical Conference and Exhibition, Virtual.

doi: https://doi.org/10.2118/201664-MS

Bellin, F., Dourfaye, A., King, W., & Thigpen, M. (2010). The current state of PDC bit technology.

World Oil, 231. 53-58.

Bertagnolli, K., & Vale, R. (2000). Understanding and controlling residual stresses in thick

polycrystalline diamond cutters for enhanced durability. Finer Points (USA), 12 (1).

Brandon, B.D., Cerkovnik, J., Koskie, E., Bayoud, B.B., Colston, F., Clayton, R.I., Anderson,

M.E., Hollister, K.T., Senger, J., & Niemi, R. (1992, February). First Revision to the IADC

Fixed Cutter Dull Grading System [Paper presentation]. IADC/SPE Drilling Conference,

New Orleans, Louisiana. doi: https://doi.org/10.2118/23939-MS

Brett, J.F., Warren, T.M., & Behr, S.M. (1989, October). Bit Whirl: A New Theory of PDC Bit

Failure [Paper presentation]. SPE Annual Technical Conference and Exhibition, San

Antonio, Texas. doi: https://doi.org/10.2118/19571-MS

Bruton, G., Crockett, R., Taylor, M., DenBoer, D., Lund, J., Fleming, C., Ford, R., Garcia, G., &

White, A. (2014, June). PDC bit technology for the 21st century. Oilfield Review, 26(2).

48-57.

Carcione, E., Easow, I., & Chiniwala B. (2017, July). Alkenes Detection From Drill Bit

Metamorphism and Real-Time Geochemical Elemental Analysis on Drill Cuttings Aids

Drilling Optimization and Geo-steering in Tight Unconventional Laterals [Paper

presentation]. SPE/AAPG/SEG Unconventional Resources Technology Conference,

Austin, Texas. doi: https://doi.org/10.15530/URTEC-2017-2697162

Cooley, C.H., Pastusek, P.E., & Sinor, L.A. (1992, October). The Design and Testing of Anti-Whirl

Bits [Paper presentation]. SPE Annual Technical Conference and Exhibition, Washington,

D.C. doi: https://doi.org/10.2118/24586-MS

Dupriest, F. E., Noynaert, S., Cunningham, T., & Rendon, M. (2020, March). Maximizing Drilling

Performance Through the Delaware Basin Brushy Canyon and Interbedded Formations

[Paper presentation]. IADC/SPE International Drilling Conference and Exhibition,

Galveston, Texas. doi: https://doi.org/10.2118/199599-MS

https://doi.org/10.2118/201664-MS

https://doi.org/10.2118/23939-MS


https://doi.org/10.15530/URTEC-2017-2697162


https://doi.org/10.2118/199599-MS

126

Dykstra, M.W., Neubert, M., Hanson, J.M., & Meiners, M.J. (2021, February). Improving Drilling

Performance by Applying Advanced Dynamics Models [Paper presentation]. SPE/IADC

Drilling Conference, Amsterdam, Netherlands. doi: https://doi-org/10.2118/67697-MS

Ertas, D., Bailey, J.R., Wang, L., & Pastusek, P.E. (2014, December). Drillstring Mechanics Model

for Surveillance, Root Cause Analysis, and Mitigation of Torsional Vibrations. SPE

Drilling & Completion, 29(04),405–417. doi: https://doi.org/10.2118/163420-PA

Fear, M.J., Abbassian, F., Parfitt, S.H.L., & McClean, A. (1997, March). The Destruction of PDC

Bits by Severe Slip-Stick Vibration [Paper presentation]. SPE/IADC Drilling Conference,

Amsterdam, Netherlands. doi: https://doi.org/10.2118/37639-MS

Giltner, M., Earle, L., Willis, J., Tellez, D., & Neel, R. (2019, March). Performance Impact of

Downhole Data from Wired Drill Pipe and Downhole Sensors [Paper presentation].

SPE/IADC International Drilling Conference and Exhibition, The Hague, Netherlands.


Glowka, D.A. (1985, September). Implications of Thermal Wear Phenomena for PDC Bit Design

and Operation [Paper presentation]. SPE Annual Technical Conference and Exhibition,

Las Vegas, Nevada. doi: https://doi.org/10.2118/14222-MS

Glowka, D.A., & Stone C.M. (1986, June). Effects of Thermal and Mechanical Loading on PDC

Bit Life. SPE Drilling Engineering, 1(03), 201–214. doi: https://doi.org/10.2118/13257-

PA

Glowka, D.A. (1987, September). Development of a method for predicting the performance and

wear of PDC (polycrystalline diamond compact) drill bits. United States. doi:

https://doi.org/10.2172/5591640

Glowka, D. A. (1989, August 1). Use of Single-Cutter Data in the Analysis of PDC Bit Designs.

Journal of Petroleum Technology, 41(8), 797–849. doi: https://doi.org/10.2118/15619-PA

Hareland, G., & Rampersad, P. R. (1994, April). Drag - Bit Model Including Wear [Paper

presentation]. SPE Latin America/Caribbean Petroleum Engineering Conference, Buenos

Aires, Argentina. doi: https://doi.org/10.2118/26957-MS

Hennessy, L. (2016, August 1). Using wired drill pipe to drive down well cost. Offshore Engineer.

https://www.oedigital.com/news/448701-using-wired-drill-pipe-to-drive-down-well-cost

Ledgerwood, L.W.W., Jain, J.R., Hoffmann, O.J., & Spencer, R.W. (2013). Downhole

Measurement and Monitoring Lead to an Enhanced Understanding of Drilling Vibrations

and Polycrystalline Diamond Compact Bit Damage. SPE Drilling & Completion, 28(03),

254-262. doi: https://doi.org/10.2118/134488-PA

https://doi-org/10.2118/67697-MS

https://doi.org/10.2118/163420-PA


https://doi.org/10.2118/194093-MS


https://doi.org/10.2118/13257-PA


https://doi.org/10.2172/5591640

https://doi-org.ezproxy.lib.utexas.edu/10.2118/15619-PA


https://doi.org/10.2118/134488-PA

127

Liang E., Wang J., Zhou L., & Wang L. (2014). The Analysis of Force on PDC Cutter [Paper

presentation]. In Energy Materials 2014. (pp. 781-787). Springer, Cam. doi:

https://doi.org/10.1007/978-3-319-48765-6_96

Liu, Y., Kibbey, J., Bai, Y., & Wu, X. (2018, March). Real-Time Bit Wear Monitoring and

Prediction Using Surface Mechanics Data Analytics: A Step Toward Digitization Through

Agile Development [Paper presentation]. IADC/SPE Drilling Conference and Exhibition,

Fort Worth, Texas. doi: https://doi.org/10.2118/189602-MS

Liu, Z., Marland, C., Li, D., & Samuel, R. (2014, May). An Analytical Model Coupled With Data

Analytics to Estimate PDC Bit Wear [Paper presentation]. SPE Latin America and

Caribbean Petroleum Engineering Conference, Maracaibo, Venezuela.


Ma, X., & Zoback, M. (2017). Lithology-controlled stress variations and pad-scale faults; a case

study of hydraulic fracturing in the Woodford Shale, Oklahoma. Geophysics, 82(6), ID35–

ID44. doi: https://doi.org/10.1190/geo2017-0044.1

Motahhari, H.R., Hareland, G., & James, J.A. (2010, October). Improved Drilling Efficiency

Technique Using Integrated PDM and PDC Bit Parameters. Journal of Canadian

Petroleum Technology, 49(10), 45–52. doi: https://doi.org/10.2118/141651-PA

Pastusek, P. E., Sullivan, E., & Thomas, M.H. (2007, February). Development and Utilization of

a Bit Based Data Acquisition System in Hard Rock PDC Applications [Paper presentation].

SPE/IADC Drilling Conference, Amsterdam, The Netherlands.


Pastusek, P., Sanderson, D., Minkevicius, A., Blakeman, Z., & Bailey, J. (2018, March). Drilling

Interbedded and Hard Formations with PDC Bits Considering Structural Integrity Limits

[Paper presentation]. IADC/SPE Drilling Conference and Exhibition, Fort Worth, Texas.


Pastusek, P. (2019). Limiter Redesign Process™, Section 07: Bit and BHA Forensics. [PowerPoint

presentation]. Unpublished.

Pessier, R.C., & Fear, M.J. (1992, October). Quantifying Common Drilling Problems With

Mechanical Specific Energy and a Bit-Specific Coefficient of Sliding Friction [Paper

presentation]. SPE Annual Technical Conference and Exhibition, Washington, D.C.


Rahimzadeh, H., Mostofi, M., Hashemi, A., & Salahshoor, K. (2010, June) Comparison of the

Penetration Rate Models Using Field Data for One of the Gas Fields in Persian Gulf Area

[Paper presentation]. International Oil and Gas Conference and Exhibition, Beijing, China.


https://doi.org/10.1007/978-3-319-48765-6_96

https://doi.org/10.2118/189602-MS

https://doi.org/10.2118/169451-MS

https://doi.org/10.1190/geo2017-0044.1

https://doi.org/10.2118/141651-PA

https://doi.org/10.2118/105017-MS

https://doi-org.ezproxy.lib.utexas.edu/10.2118/189608-MS


https://doi.org/10.2118/131253-MS

128

Rahmani, R., Pastusek, P., Yun, G., & Roberts, T. (2021, March). Investigation of PDC Cutter

Structural Integrity in Hard Rocks. SPE Drilling & Completion 36(01), 11–28.

doi: https://doi.org/10.2118/199598-PA

Rashidi, B., Hareland, G., & Wu, Z. (2010, November). New Approach in Real-Time Bit Wear

Prediction. [Paper presentation]. Abu Dhabi International Petroleum Exhibition and

Conference, Abu Dhabi, UAE. doi: https://doi.org/10.2118/136008-MS

Regan, M., Carcione, E., & Martocchia, A. (2018, August). Near Real-Time Monitoring of PDC

Bit Condition and Associated NPT Mitigation Using Online Alkene Detection [Paper

presentation]. IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition,

Bangkok, Thailand. doi: https://doi.org/10.2118/190997-MS

Scott, D. (2006). The History and Impact of Synthetic Diamond Cutters and Diamond Enhanced

Inserts on the Oil and Gas Industry. Industrial Diamond Review, 66, 48 – 55.

Scott, D. (2015). A bit of history: Overcoming early setbacks, PDC bits now drill 90%-plus of

worldwide footage. Drilling Contractor. https://www.drillingcontractor.org/a-bit-of-

history-overcoming-early-setbacks-pdc-bits-now-drill-90-plus-of-worldwide-footage-

35932

Sinor, A., & Warren, T.M. (1989, June). Drag Bit Wear Model. SPE Drilling Engineering 4(02),

128–136. doi: https://doi.org/10.2118/16699-PA

Sinor, A., & Warren., T.M. (1993, April). Application of Anti-Whirl PDC Bits Gains Momentum

[Paper presentation]. Middle East Oil Show, Bahrain. doi: https://doi.org/10.2118/25644-

MS

Sneddon, M.V., & Hall, D.R. (1988, December). Polycrystalline Diamond: Manufacture, Wear

Mechanisms, and Implications for Bit Design. Journal of Petroleum Technology, 40(12),

1593–1601. doi: https://doi.org/10.2118/17006-PA

Technical Summary: Drill Bit Dull Grading. (2020). Internal NOV report: Unpublished.

Teelken, R., Jaring, C., Craig, A., Allan, R., Roberts, H., Hatch, A., & Shepherd, N. (2016, March).

Implementation of Wired Drill Pipe Saved Multiple Days Per Well, by Addressing

Performance Limiters, Increasing Drilling Efficiency [Paper presentation]. IADC/SPE

Drilling Conference and Exhibition, Fort Worth, Texas. doi: https://doi.org

/10.2118/178798-MS

Timonin, V., Smolentsev, A., Shakhtorin, I. O., Polushin, N., Laptev, A., & Kushkhabiev, A.

(2017). Causes of wear of PDC bits and ways of improving their wear resistance. IOP

Conference Series: Earth and Environmental Science, 53(1), 196-201.

doi: https://doi.org/10.1088/1755-1315/53/1/012027

https://doi.org/10.2118/199598-PA

https://doi.org/10.2118/136008-MS

https://doi.org/10.2118/190997-MS





https://ui.adsabs.harvard.edu/link_gateway/2017E&ES...53a2027T/doi:10.1088/1755-1315/53/1/012027

129

Warren, T.M., Brett, J.F., & Sinor, L.A. (1990, December). Development of a Whirl-Resistant

Bit. SPE Drilling Engineering 5(04), 267–275. doi: https://doi.org/10.2118/19572-PA

Zacny, K. (2012, March). Fracture and Fatigue of Polycrystalline-Diamond Compacts. SPE

Drilling & Completion, 27(01), 145–157. doi: https://doi.org/10.2118/150001-PA


https://doi.org/10.2118/150001-PA

A Methodology to Identify Root Cause of Drill Bit Failure from ...

Documents

Transcript of A Methodology to Identify Root Cause of Drill Bit Failure from ...