Thermally Active Polymer to Improve Sweep Efficiency of Water Floods: Simulation and Pilot Design...

2012 SPE Reservoir Evaluation & Engineering 1

Thermally Active Polymer To Improve Sweep Efficiency of Waterfloods:

Simulation and Pilot Design ApproachesR. Garmeh, M. Izadi, M. Salehi, J.L. Romero, C.P. Thomas, and E.J. Manrique, all SPE, TIORCO

SummaryA common problem in many waterflooded oil reservoirs is early water breakthrough with high water cut through highly conductive thief zones. Thermally active polymer (TAP), which is an expand-able submicron particulate of low viscosity, has been successfully used as an in-depth conformance to improve sweep efficiency of waterfloods.

This paper describes the workflow to evaluate technical fea-sibility of this conformance technology for proper pilot-project designs supported with detailed simulation studies. Two simula-tion approaches have been developed to model properties of this polymer and its interaction with reservoir rock. Both methods include temperature-triggered viscosification and adsorption/reten-tion effects. Temperature profile in the reservoir is modeled by energy balance to accurately place this polymer at the optimum location in the thief zone. The first method considers a single chemical component in the water phase. The second method is based on chemical reactions of multiple chemical components. Both simulation approaches are compared and discussed.

Results show that temperature-triggered polymers can increase oil recovery by viscosification and chemical adsorption/reten-tion, which reduces thief-zone permeability and diverts flow into unswept zones. Sensitivity analyses suggest that ultimate oil recov-ery and conformance control depend on the thief-zone temperature, vertical- to the horizontal-permeability ratio (Kv /Kh), thief-zone vertical location, injection concentration and slug size, oil viscos-ity, and chemical adsorption and its reversibility, among other fac-tors. For high-flow-capacity thief zones and mobility ratios higher than 10, oil recoveries can be improved by increasing chemical concentration or slug size of treatments, or both. Reservoirs with low Kv /Kh (< 0.1) and high permeability contrast generally shows faster incremental recoveries than reservoirs with high Kv /Kh and strong water segregation.

The presented workflow is currently used to perform in-depth conformance treatment designs in onshore and offshore fields and can be used as a reference tool to evaluate benefits of the TAP in waterflooded oil reservoirs.

IntroductionA common problem in waterflooded oil reservoirs is early water breakthrough with high water cut through highly conductive thief zones. Several approaches have been proposed to reduce water chan-neling and high water cuts. Mechanical isolation, the use of selective advanced completions (e.g., sliding sleeves), and especially polymer gels to modify injection profiles or as water-shutoff strategies are some of the most common approaches used to manage water-injec-tion projects. However, the use of TAP for in-depth conformance strategies has been gaining more interest in recent years.

Fletcher et al. (1992) wrote one of the first published papers proposing the use of deep diverting gels to improve waterflood sweep efficiencies. This study reported slimtube tests using sys-tems of polyacrylamide polymer and aluminum citrate and also

conceptual simulations using the BPOPE model, a modified ver-sion of UTChem, originally developed at the University of Texas at Austin. In 1996, BP sponsored an industry academic seminar that later became a joint research project (BP, ChevronTexaco, and Nalco) known as BrightWater® (Frampton et al. 2004; Pritchett et al. 2003).

BrightWater is a TAP that has been designed to activate at a predetermined “in-depth” location within the reservoir. The trigger for this expansion is heat and time. Upon activation, particles begin to expand up to 10 times their original size and volume, blocking pore throats and diverting injection water into untapped, oil-rich zones. This deep-reservoir-profile modification causes additional oil to be swept toward the producing wells, and, over time, produc-tion begins to improve.

Fig. 1 shows the mechanism of TAP activation that is triggered by time and heat. Permanent and reversible crosslinkers hold TAP polymers tight in their initial state by internal linkages. The reversible linkages break by hydrolysis, and after that the particles expand to their natural size. The biggest resistance is created where most of the particles are located, which is in the main thief zone between the injection and production wells. This resistance against flow is created by polymer viscosity, adsorption, and retention in pore throats in the thief zone and diverts chase water to displace unswept oil in adjacent zones, as shown in Fig. 2. The strength of the resistance factor (RF) in the thief zone depends on the concen-tration, slug size, and the level of dispersion in the thief zone.

The first TAP test was in the Minas field, Indonesia, in 2001. The reservoir thief zone was identified throughout the main reser-voir layers. The diverting-agent treatment of 42,000 bbl of water containing 4,500 ppm of active material was pumped deep into the reservoir at low viscosity. Pre- and post-treatment tracer tests were conducted to determine the sweep improvement; several of the major objectives of the Minas Field trial were met (Pritchett et al. 2003).

Since then, almost 60 treatments have been performed in the North Sea (Frampton et al. 2009), Alaska (Frampton et al. 2009; Ohms et al. 2008, 2009), Argentina (Mustoni et al. 2010; Denney 2008), Tunisia (Ghaddab et al. 2010), and Brazil (Roussennac and Toschi 2010). The first offshore project was in a UK North Sea field during the summer of 2002. This treatment proved that this technol-ogy could be injected offshore without injectivity loss into 400-md sandstone (Frampton et al. 2009). Husband et al. (2010) present a list of TAP treatment projects performed by BP Alaska. The paper gives useful information about field types, injection water salinity, injection and reservoir temperature, thief-zone permeability, perme-ability contrast, and the success rates of these projects.

Pritchett et al. (2003) present some screening criteria for evalu-ation of potential candidates for this technology; however, the list is not up to date because of new improvements in the technology and its design. Roussennac and Toschi (2010) describe feasibility, screening, execution, simulation, and laboratory studies that led to performing a TAP trial in Salema field, Brazil. Ohms et al. (2009) present a successful waterflood-sweep improvement case from a BP Alaska field. The paper gives details about target selection, simulation and lab work, pretreatment tracer test, post-treatment falloff test, and production responses after 3 years of treatment injection. Similar results can be found in Husband et al. (2010). Table 1 summarizes a few TAP projects well documented in the literature.

Copyright © 2012 Society of Petroleum Engineers

This paper (SPE 144234) was accepted for presentation at the SPE Enhanced Oil Recovery Conference, Kuala Lumpur, 19–21 July 2011, and revised for publication. Original manuscript received for review 29 April 2011. Revised manuscript received for review 17 August 2011. Paper peer approved 25 September 2011.

2 2012 SPE Reservoir Evaluation & Engineering

Despite the number of field applications published and ongoing evaluations (e.g., Argentina, Azerbaijan, Pakistan, and West Africa) not documented in the literature, few papers have been focused on numerical-simulation approaches of in-depth conformance of TAP (Fletcher et al. 1992; Woods et al. 2002). Therefore, this paper is mainly focused on simulation approaches to model TAPs. Basic lab-oratory data required for numerical simulation and general workflow for field-project design and monitoring will be also discussed.

TAP Simulation ApproachesSimulation approaches that have been developed for project design are described in this section of the paper. Several approaches are described that can be used to model a TAP system that capture the critical aspects of the technology. Conceptual geological models

are used to illustrate the effects of the TAP system under different scenarios. These results clearly show that a good understanding and description of the geology of the reservoir is critical to the optimum design of a TAP project. To model a TAP treatment, we combined thermal and compositional simulations. Thermal simu-lation is used to capture temperature-triggered characteristics of the polymer. Therefore, injection and reservoir temperatures, rock and fluid heat conductivities, and rock heat capacity are required information for thermal simulation. Throughout this paper, we used rock and fluid thermal properties given in Table 2.

There are different TAP grades available depending on reservoir- temperature profile, thief-zone properties, and water salinities, among other variables. The reservoir-temperature profile is used to determine the grade that should be used in each specific treatment,

1- to 10-µ Diameter

0.01- to 1-µ Diameter

PermanentCrosslinks

ReversibleCrosslinks

TIME

TIME

TIME TIM

E

TIME

HEAT

HEAT HEATHEAT

HEAT

Fig. 1—TAP is activated by heat and time. Particles expand up to 10 times their original size; they are adsorbed and retained by the rock and divert flow into the unswept zones.

Water Injector Water Injector Oil ProducerOil Producer

Water breakthrough in a verticallyisolated thief zone

Thermally active polymer diverts flowinto unswept zone

Diverting agenttreatment

Fig. 2—RF developed by particle adsorption/retention diverts chase water to low-permeability zones and increases sweep efficiency.

TABLE 1—FIELD EXAMPLES OF TAP TREATMENT AND REFERENCE ARTICLES

Field Injection

Temp. (°F) Res.

Temp. (°F) Volume

Injected (m3) Conc. (ppm)

Injection Date

First Oil Response Results

Milne Point, Alaska* 110 175 59 3.300 June 2004 May 2005 + Koluel Kaike, Argentina** 120 160 34 3,000 September 2006 May 2007 + El Borma, Tunisia† 110 167 52 5,000 January 2010 September 2011 + * Ohms et al. 2009 ** Denney 2008; Mustoni et al. 2010 † Ghaddab et al. 2010


and it also helps to target the placement at an optimum location in the thief zone. Next, a tracer-test simulation is performed to deter-mine the transit time to the target location or temperature in the thief zone. Tracer-transit volume is also used to confirm the thief-zone channel volume estimated from injection/production data.

After the grade is selected on the basis of the reservoir-tempera-ture profile and transit time, TAP viscosity and adsorption/retention are triggered by temperature of the activation zone. This means that this polymer will have low viscosity and adsorption near the injec-tion well, and then its viscosity and adsorption gradually increase with heat and time. The rate of increase in viscosity and adsorption depends on the product grade. In this paper, two approaches are described for modeling of this diverting agent’s characteristics:

• Single-component approach: In this approach, TAP is injected as a single chemical component at the injector, and it remains as a single component throughout the course of action. However, its physical characteristics such as viscosity and adsorption increase with heat and time. This characteristic increases the resistance against flow in the thief zone away from the injector.

• Chemical-reaction approach: In this approach, TAP is the product of a reaction between polymer and crosslinker. The chemi-cal reaction is a nondecay reaction, and total mass is conserved. In this approach, the treatment is modeled using three water-soluble components (polymer, crosslinker, and TAP). In the model, a chemical reaction is triggered by temperature; therefore, at the acti-vation temperature, the reaction between polymer and crosslinker is started and the TAP component is generated, which has higher viscosity and higher adsorption than polymer and crosslinker com-ponents individually. The rate of reaction (product generation) can be controlled by a reaction-rate coefficient.

Adsorption and Resistance FactorThe rate of propagation of many additives (water-soluble compo-nents) in porous media is strongly affected by their interaction with the rock matrix. Interactions can be mechanical (e.g., blockage or retention), chemical (e.g., ion exchange), or some combination of mechanisms (STARS 2009). The capture level of the adsorption phenomenon in simulations can depend on fluid concentration, temperature, and rock type. A set of adsorption isotherms (adsorp-

tion level as a function of component concentration) at a constant temperature is defined in the model. Adsorption isotherms can be either in tabular format or the well-known Langmuir adsorption correlation. Eq. 1 is the Langmuir adsorption equation, where (a/b) is the slope of the Langmuir type curve and it quantifies the adsorption sensitivity. Adsorption type curves can be quantified from laboratory data or correlations.

Adsi = ⎛⎝⎜

⎞⎠⎟ +

⎛⎝⎜

⎞⎠⎟

a

b

bz

bzi

i1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (1)

Fig. 3 shows a typical isothermal Langmuir adsorption curve including the reversible threshold. It shows that the level of adsorp-tion increases as solution concentration is increased. The reversible threshold proposes that if the concentration falls before Point A has been reached, then the adsorption does not reverse (irrevers-ible). If the concentration starts to fall between Points A and B, then desorption occurs along a straight line from the maximum point reached on the adsorption curve to Point C. If the concen-tration starts to fall after Point B, then desorption proceeds down the adsorption curve until Point B is reached, and then down the straight line connecting Point B to Point C.

The permeability-reduction factor (resistance factor against flow) is related to the adsorption level as given in Eq. 2. The permeability-reduction factor at the pore-scale level is caused by adsorption, retention, and filtration. All these effects are translated to RF and residual RF (RRF) at the simulation scale.

RKwi= + −

⎛⎝⎜

⎞⎠⎟

1 0 1 0. ( . )RFMaxMax

Ads

Ads. . . . . . . . . . . . . . . . . . (2)

Conceptual Model and Sensitivity AnalysisBase-Case Model. A 2D conceptual model was used to validate simulation approaches of modeling TAP characteristics. Simula-tions were performed using the Computer Modeling Group STARS simulator (STARS 2009). Various sensitivity analyses on the key parameters that impact fi eld application designs were performed. Later in this paper, the 2D conceptual model is extended to a 3D model.

The base-case reservoir model is a 2D cross-sectional model, as given in Fig. 4. The model is 500×40 ft, with a Cartesian grid of 100×8 gridblocks in the x- and z- direction, respectively. For simplicity, the sizes of all gridblocks are equal. The injection rate is held constant at 100 B/D. The thief zone is located in the middle zone in Layers 4 and 5. The thief-zone permeability is 1,500 md, and upper and lower zones have a constant permeability of 50 md. Porosity is 20% and is constant. Vertical to horizontal-permeability ratio (Kv /Kh) is 0.1. Injection and reservoir temperatures are 60 and 200°F, respectively. Water is injected for 600 days [1.0 pore volume (PV)] and is followed by 5% of the channel volume (CV) chemical injection (7.5 days) using the same injection rate. TAP is injected in 5,000-ppm active concentration, where its adsorption at the maximum concentration is assumed to be 0.3 mg/g rock.

TABLE 2—ROCK AND FLUID THERMAL PROPERTIES USED IN THIS PAPER

Thermal Conductivity

(btu/ft-day-F) Heat Capacity

(btu/ft3-F)

Reservoir rock 44 35 Non-reservoir rock 34 30

– 6.8 retaW – 8.1 liO – 5.0 saG

Residual AdsorptionAdsorption

Concentration, ppm

Ads

orpt

ion

mg/

g ro

ck

C

A

B

Fig. 3—Reversible Langmuir curve. Residual adsorption is the irreversible part of the Langmuir adsorption.

Permeability (md)

1,500

1,355

1,210

1,065

920

775

630

485

340

195

50

Fig. 4—The conceptual 2D model has eight layers, where the thief zone is located in Layers 4 and 5. Permeability of the thief zone is 1,500 md, and other layers are 50 md.


A maximum RF of 40 is assumed at the maximum concentration. The TAP activation-temperature range is between 130 and 160°F. Maxi-mum adsorption and RFs are set at the fully activated condition (T >160°F). The treatment is followed by 2.0-PV waterflood. Fig. 5 shows the temperature profile after 600 days (1.0 PV) of waterflood, and Fig. 6 shows the resistance factor/permeability-reduction factor

(RF/RRF). As can be seen in Fig. 6, the strongest permeability-reduction factor is created in the high-permeability layers and in the mid-distance between injection and production wells.

Fig. 7 shows how RF created by TAP diverts flow into a low-permeability zone and increases the oil-production rate. Fig. 8 shows the incremental oil-production rate and incremental

Temperature (°F)

200

186

172

158

144

130

116

102

88

74

60

Fig. 5—Temperature profile after 600 days (1.0 PV) of water-flooding.

Residual Resistance Factor

13.9

12.6

11.3

10.0

8.8

7.5

6.2

4.9

3.6

2.3

1.0

Fig. 6—RRF (permeability-reduction factor) in high-permeabil-ity layers created by TAP adsorption/retention.

Oil Saturation 600 days






0.72

0.67

0.62

0.57

0.52

0.47

0.42

0.37

0.32

0.27

0.22

Fig. 7—Comparison of TAP (left) and waterflood (right) performance. TAP is injected in 5% of CV after 600 days of waterflood and is followed by 2.0-PV waterflood.

(b)(a)

Oil

Rec

over

y Fa

cto

r (%

OO

IP)

Oil

Rat

e S

C (

B/D

)

Fig. 8—(a) Incremental oil-production rate; (b) incremental recovery factor after TAP treatment. Treatment improves incremental recovery factor by 5% OOIP after 1.0-PV waterflood.


recovery factor. Fig. 9 shows the tracer test before and after TAP treatment. It indicates that TAP diverts the tracer flow path and that transit time has increased after the treatment.

Various sensitivity tests were performed to examine parameters and conditions that may impact TAP application.

Treatment-Slug Size. The normal rule-of-thumb slug size is 5% of the CV; however, the size of the slug largely depends on the TAP dispersion (dilution), vertical to horizontal-permeability ratio, and mobility ratio, among other factors. Therefore, the impacts of different slug sizes were examined. Figs. 10 and 11 show the sensitivity of incremental oil recovery and injection-well bottom-hole pressure (BHP) to slug size for different treatment-slug sizes. Results indicate that oil recovery increases as the treatment-slug size is increased because of increased permeability-reduction fac-tor in the thief zone (Fig. 11a).

Treatment Concentration. The base-case treatment concentration was set at 5,000-ppm active concentration, which is equivalent to 1.67% as supplied concentration (30% active). Figs. 12 and 13 show the sensitivity of incremental oil recovery and injection-well BHP to solution concentration for different injection concentra-tions. Different injection concentrations have different active vis-cosities, adsorption, retention, and RFs, as given in Table 3. Results indicate that oil recovery increases as treatment concentration is

increased because of the increased permeability-reduction factor in the thief zone.

Permeability Contrast (i.e., Dykstra-Parsons Coeffi cient). Per-meability contrast of the thief zone and the rest of the reservoir is a signifi cant reservoir parameter that impacts the treatment performance. As can be observed in Fig. 14, the high permeability contrast is a desirable factor in TAP application. In the case of high permeability contrast, the thief zone takes the larger portion of the injection water, and therefore TAP has more impact on reducing permeability of the thief zone.

Vertical to Horizontal-Permeability Ratio (i.e., Kv /Kh): Kv /Kh is another reservoir parameter that impacts the treatment perfor-mance. Fig. 15b shows the impact of Kv /Kh on incremental oil recovery. It can be seen that the performance of the treatment is better for smaller Kv /Kh (lower dispersion/dilution in the reservoir). In the case of large Kv /Kh, TAP easily fl ows to the low-permeability zone and its concentration decreases in the thief zone, causing the effective permeability-reduction factor to be smaller in the thief zone (Fig. 15a).

Activation Location. TAP is available in different grades, which can be used for different activation-temperature and -time profi les. The characteristics of these grades allow them to be placed in

Inj.

Trac

er C

on

c. (

Mas

s F

ract

ion

)

Pro

. Tra

cer

Co

nc.

(M

ass

Fra

ctio

n)

Pro

. Tra

cer

Co

nc.

(M

ass

Fra

ctio

n)

Inj.

Trac

er C

on

c. (

Mas

s F

ract

ion

)

(b)(a)

Fig. 9—(a) Tracer test before TAP treatment; (b) tracer test after treatment. Tracer test indicates that treatment changes the flow path and that the transit volume is increased after the treatment.

(b)(a)

Oil

Rec

over

y Fa

cto

r (%

OO

IP)

Oil

Rat

e S

C (

B/D

)

Fig. 10—Comparison of oil rate and incremental oil-recovery factor for different treatment slug sizes. Oil recovery increases as the treatment slug size is increased, resulting from increased RF against flow in the thief zone (Fig. 11a).


Wel

l Bo

tto

mh

ole

Pre

ssu

re (

psi

)


5% Channel Volume

10% Channel Volume

20% Channel Volume

20.5

18.5

16.6

14.7

12.7

10.8

8.8

6.9

4.9

3.0

1.0

(b)(a)

Fig. 11—(a) RRF at different treatment slug sizes; (b) comparison of well BHP for different treatment slug sizes. Injection well BHP increases because of increased area of permeability reduction in the thief zone.

(b)(a)

Oil

Rec

over

y Fa

cto

r (%

OO

IP)

Oil

Rat

e S

C (

B/D

)

Fig. 12—Comparison of oil rate and incremental oil-recovery factor for different treatment concentrations. Oil recovery increases as solution concentration is increased as a result of increased RF against flow in the thief zone (Fig. 13a).

Wel

l Bo

tto

mh

ole

Pre

ssu

re (

psi

)


5,000 ppm

10,000 ppm

15,000 ppm

40

36

32

28

24

21

17

13

9

5

1

(b)(a)

Fig. 13—(a) RRF at different treatment concentrations; (b) comparison of well BHP for different solution concentrations. Injec-tion-well BHP increases because of increased permeability-reduction factor and fluid viscosity in the thief zone.


different locations of the thief zones. Fig. 16a shows the perme-ability-reduction factor and its location for different grades in the conceptual model, and Fig. 16b shows the oil-recovery factor for different grades. The impact of the treatment placement is a strong function of reservoir heterogeneity, reservoir and thief-zone temperatures, thief-zone transit time, Kv /Kh, and mobility ratio, among other factors.

Mobility Ratio. Water/oil mobility ratio M is another reservoir fl uid property that impacts the performance of the treatment. Fig. 17 shows the incremental oil recovery for different mobility ratios. For lower mobility ratios, the incremental oil recovery is lower because of lower remaining oil saturation in the reservoirs (e.g., effi cient waterfl ood). On the other hand, incremental oil recovery for higher mobility ratios is lower because of the unfa-vorable mobility ratio (e.g., ineffi cient waterfl ood), which results

in diverted water fl ow fi ngering through viscous oil. The optimum mobility ratio of approximately 10 was observed during the sensi-tivity analysis (Fig. 17). However, it is important to note that the sensitivity case presented depends on reservoir heterogeneity, fl ow pattern, and thief-zone location. Therefore, further analysis will be required to better understand the effect of M on incremental oil recovery of TAPs.

3D Simulation Model. A conceptual model was built to demon-strate TAP effects in more-realistic 3D simulations. The base-case 3D simulation model is 2,040×2,040×40 ft with a Cartesian grid of 51×51×8 gridblocks in the x- , y-, and z-direction, respectively. For simplicity, the size of every gridblock is equal. The injection rate is held constant at 4,000 B/D. The thief zone is located in the middle zone in Layers 4 and 5. Thief-zone permeability is 1,500 md, and upper and lower zones have a constant permeability of

TABLE 3—TAP PROPERTIES FOR DIFFERENT INJECTION CONCENTRATIONS USED IN THIS PAPER

TAP Concentration (ppm)

Viscosity (After Activation)

Adsorption (mg/g rock)

Residual Resistance Factor (RF/RRF)

5,000 35 0.3 40 (20.5) 10,000 83 0.4 65 (33.0) 15,000 145 0.5 100 (50.5)

Incr

emen

tal O

il R

eocv

ery

(%O

OIP

)Residual Resistance Factor

Permeability Contrast: 30



13.9

12.6

11.3

10.0

8.8

7.5

6.2

4.9

3.6

2.3

1.0

(a) (b)

Fig. 14—Impact of permeability contrast (thief zone and the rest of the pay zone) on the TAP application. TAP has higher dilution and dispersion in the case of low permeability contrast.

Incr

emen

tal O

il R

ecov

ery

(%O

OIP

)14.7

13.3

11.9

10.6

9.2

7.8

6.5

5.1

3.7

2.4

1.0

Kv /Kh: 0.02

Kv /Kh: 0.10

Kv /Kh: 0.9

Kv /Kh(b)(a)

Fig. 15—(a) RRF at different Kv/Kh; (b) impact of Kv /Kh on incremental oil recovery. Dilution/dispersion of TAP is higher in higher Kv /Kh; therefore, its impact on flow diversion is less.


50 md. Porosity is 20% and is constant. Vertical-to-horizontal permeability ratio (Kv /Kh) is 0.1. Injection and reservoir tem-peratures are 60 and 200°F, respectively. Water is injected for 1,000 days (0.67 PV) and is followed by 5% of the CV chemical injection (18.5 days) using the same water-injection rate. TAP is injected at 5,000-ppm active concentration, where its adsorption at the maximum concentration is assumed to be 0.3 mg/g rock. The maximum resistance factor of 40 is assumed at the maximum concentration. Fig. 18 shows the 3D conceptual model. Fig. 19 shows the temperature profi le after 1,000 days of waterfl ood. Fig. 20 shows the RRF generated against fl ow by chemical adsorption onto the rock and possibly by retention in the pore throats. It can be seen that the majority of the TAP goes to the thief zone because the larger portion of the waterfl ood goes through the thief zone; therefore, the most signifi cant adsorption/retention and RFs occur in the thief zone. Fig. 21 shows the oil-recovery factor and water cut for the waterfl ooding and TAP-injection scenarios evaluated. The incremental-oil-production response starts 6 months after the treatment, and incremental oil recovery is 2.7% of the OOIP after 2 years (0.5 PV injected).

TAP Technology: Laboratory Data and Treatment DesignThis section briefly describes laboratory data required to evaluate and estimate potential benefits of TAP technology. Basic screening

to consider technical feasibility of the technology and general workflow for treatment design will be also discussed.

Laboratory Data. TAP viscosity and static-adsorption (bottle-test) tests at reservoir temperatures are the minimum laboratory tests required to estimate project design and incremental-recovery potential through numerical simulations. TAP viscosity and static-adsorption (e.g., input data for Langmuir isotherm) tests using different concentrations are always recommended. Viscosity mea-surements vs. time (e.g., activation temperature and maximum vis-cosity reached) at different shear rates are also required. For thick intervals and possible changes in mineralogy composition within the production column, static-adsorption tests using rock samples from different pay-zone intervals might be required, especially for reservoirs showing more than one thief zone and if bulk injection is planned. Although slimtube tests (1 to 40 ft long) or corefl oods, or both, can be considered to evaluate TAP performance and dynamic adsorption, these types of tests are less common. Slimtube tests can be based on cleaned quartz sand or crushed reservoir material, or both. Slimtube tests can also be used to estimate thermal stability vs. time at reservoir temperature.

Fig. 22a shows the TAP viscosity profile for different solu-tion concentrations at reservoir temperature and injection-water salinity. As can be observed, higher-concentration solutions have higher viscosity, and viscosity increases with time and aging at temperature until it reaches its plateau for a given concentration. It is important to mention that maximum viscosity buildup in bottle tests can take several days or weeks, depending on reservoir con-ditions (e.g., temperature and water salinity) and on TAP grade. Fig. 22b shows the viscosity profile at a concentration of 5,000

Fast Activation Grade

Moderate Activation Grade

Slow Activation Grade

20.5

18.8

16.6

14.7

12.7

10.8

8.8

6.9

4.9

3.0

1.0

Oil

Rec

over

y Fa

cto

r (%

)

(b)(a)

Fig. 16—(a) RRF of different grades (different activation time and temperatures): fast grade (80–90oF), midgrade (140–150oF), and slow grade (175–185�F). (b) Oil-recovery factors. Incremental oil recovery depends on the location of TAP activation; however, thief-zone temperature, thief-zone transit time, and mobility ratios are significant parameters that impact the design of the treat-ment placement in the thief zone.

Fig. 17—Impact of mobility ratio on treatment performance. Optimum treatment performance is a function of reservoir het-erogeneity, flow pattern, and thief-zone location and is case/ scenario sensitive.

1,500

1,355

1,210

1,065

920

775

630

485

340

195

50

Fig. 18—The conceptual 3D model has eight layers, where the thief zone is located in Layers 4 and 5. Permeability of the thief zone is 1,500 md, and other layers are 50 md.


ppm aged at different temperatures. Viscosity develops faster at higher temperature.

Fig. 23 shows static adsorption onto different rock types. It can be seen that the adsorption amount is a strong function of rock mineralogy. In other words, high-clay-content rocks will show higher TAP adsorption and vice versa. X-ray diffraction, includ-ing clay-fraction compositional analysis and cationic-exchange capacity (CEC), provides good laboratory data for preliminary inference of TAP adsorption. For example, low CEC values (e.g., 2 meq/100 g) suggest lower adsorption compared with higher CEC values (e.g., > 2 meq/100 g). Finally, the higher adsorption values will be reflected in higher permeability-reduction factors, as described in Eq. 2.

Slimtube Test and History Match. Fig. 24 shows viscosity buildup for a grade of TAP that is proper for low-temperature reservoirs. It can be observed that viscosity reaches its plateau after 30 days. The slimtube is 20 in. long, and its porosity and permeability are 0.44 and 291 md, respectively. A solution of 5,000 ppm (Fig. 24) was prepared in synthetic fi eld brine. After the injection of 2.0 PV of synthetic fi eld brine, 3.0 PV of freshly made TAP solution was injected at room temperature. Fig. 25a shows the RF. The increased RF against fl ow is the result of TAP viscosity and adsorption/retention. The RF was history matched by solution viscosity of 1.4 cp at 5,000 ppm and an RF of 3.0 owing to adsorption/retention. A dynamic adsorption of 0.3 mg/g was used, which is representative of low-clay-content sand. Next, the slimtube was aged for 50 days at a temperature of 86°F, and then synthetic fi eld brine was injected for 3.0 PV. Fig. 25b shows RF and RRF. It can be seen from Fig. 25b that RF against fl ow increases up to 80 owing to solution viscosity (see Fig. 24) and adsorption/retention, and then after 1.0 PV of brine injection, RRF reaches 54, which is caused by only adsorption/retention.

Basic Screening and Treatment Design. In order to design a treatment, the following technical steps are required.

Basic Screening. The first step is to perform a basic screening of candidate wells (patterns/sectors/fields) to assess applicability of this technology for the target reservoir. Basic screening criteria include

1. Presence of unswept zones and moveable oil2. Early water breakthrough, resulting in high water cuts and

suggesting water channeling3. Moderate to high permeability contrast4. Reservoir temperatures below 300°F5. Sandstone formations only6. Injection water pH equal to or greater than six (pH ≥ 6)7. Injection-water salinity less than 150,000 ppm8. Expected transit times of greater than 30 days9. Minimal natural fracturesCV Estimation. The next step is to confirm water channeling

and estimate the CV, provided that the basic screening criteria are met. Two methods are used to estimate CV.

1. In injection-/production-data analysis, we first estimate the swept-channel mobile pore volume (MPV) between the injec-tor and its offset producers. The MPV of the swept interval is estimated by creating water/oil ratio (WOR) vs. cumulative oil (Np) plots per well and then calculating the cumulative secondary oil recovered at the offset producers between the time of water injection started and the time when water broke through at these wells (sudden increase in WOR). The CV will be the volume of secondary oil displaced (swept) by water injection until water breakthrough. CV estimated with Np vs. WOR could be adjusted by use of an allocation factor if more than one injector is affecting the producers.

2. Transit volume from numerical simulations. If available, results from tracer-injection programs can be also used to estimate CVs. CV estimation can be refined using injection- (e.g., spinner surveys) or production-logging tools. These logs will also con-tribute to treatment design based on thief-zone location within the injection/production interval. The normal rule-of-thumb treatment slug size is 5% of the CV, though it may vary from 1.25 to 10% of the CV. However, in the case of injection time constraints (e.g., offshore applications), treatment slug sizes are generally reduced, increasing TAP concentration depending on thief-zone permeabil-ity and/or crude-oil viscosity. As of this writing, concentrations of TAP field treatments have ranges from 3,000 to 15,000 ppm.

Temperature Gradients and Transit Time. To accurately select the proper treatment grade, temperature gradients (injector-to- producer temperature profile) and transit time must be determined. The temperature gradient is obtained by temperature logs and thermal numerical simulations. Transit times can be obtained by tracer tests (field tests or numerical simulations; field-test tracer data are preferable).

Laboratory Data. The next steps after grade selection are static adsorption and viscosity bottle tests with injection water, as was described in a previous subsection. The bottle-test proce-

200

186

172

158

144

130

116

102

88

74

60

Fig. 19—Temperature profile (°F) after 1,000 days (0.67 PV) of water injection.

14.4

13.1

11.7

10.4

9.1

7.7

6.4

5.0

3.7

2.3

1.0

Fig. 20—RRF against flow developed by chemical adsorption/retention. Adsorption/retention is modeled through a tempera-ture-dependent process.

Oil

Rec

over

y Fa

cto

r (%

OO

IP)

Fig. 21—Oil-recovery factor and water cuts of waterflooding and TAP treatment. TAP diverts flow to the unswept zone, which decreases water production and increases oil production.


(b)(a)

Vis

cosi

ty @

SR

= 3

6 se

c–1

(cp

)

Vis

cosi

ty (

cp)

Fig. 22—(a) TAP viscosity vs. time aged at reservoir condition (196°F and injection-water salinity); (b) TAP viscosity vs. time aged at different temperatures. Viscosity increases as time and/or heat increases.

(b)(a)

Fig. 25—(a) RF for synthetic reservoir brine and fresh TAP flood at room temperature; (b) RF and RRF after aging slimtube for 50 days at a temperature of 86°F.

Fig. 23—Static-adsorption density for adsorption of 1,500-ppm TAP solution onto different rock types.

Vis

cosi

ty (

cp)

Fig. 24—TAP viscosity at 5,000-ppm concentration vs. time aged at 86°F and injection-water salinity that is used for the slimtube test given in Fig. 25. Freshly made solution has a viscosity of 1.4 cp.

dure is used to monitor viscosity development of TAP at constant temperature vs. time at reservoir conditions for salinity, pH, and temperature. Samples are made up in injection water and separated into small vials in an anaerobic chamber and sealed for aging at reservoir temperature. Sample bottles are periodically removed

from the oven and viscosity development vs. time and shear rate is measured. A modified bottle test is used to determine the adsorption levels for TAP on sand and other solid materials, such as crushed reservoir rock.


Numerical Simulation. In this step, results from the laboratory data are used to numerically model the TAP treatment. From the injection/production analysis, candidate pilot areas are ranked. After history matching (or model conversion to chemical-flood platforms) of the candidate pilot is completed, the treatment simu-lation prediction and field-project design are performed using the simulation approaches described previously. Numerous sensitivity analyses are performed on the key uncertain or unknown parame-ters. Next, the optimum slug size and concentration are determined, and, finally, the incremental oil recovery is predicted.

Monitoring. The recommended monitoring program includes falloff tests, injection-pressure monitoring, water-composition analysis (before, during, and after TAP treatment), and injec-tion-/production-well logs. In cases where tracer injection before treatments was performed, a second tracer injection can be used post-TAP treatment to estimate possible changes in flow patterns in the reservoir caused by TAP injection.

ConclusionsIn this paper, we presented simulation and field-design approaches to model a TAP. This paper presents a general workflow to perform in-depth conformance treatment designs in onshore and offshore fields, and can be used as a reference tool to evaluate benefits of the TAP in waterflooded oil reservoirs. Major findings of this study include• TAP is activated with time and heat (temperature). It is a deep con-

formance treatment, and it does not affect reservoir injectivity.• The TAP is adsorbed onto the rock surface or retained in pore

throats and small pores, or both, and creates resistance against flow (RRF) in the thief zone.

• The level of adsorption is a function of solution concentration, salinity, rock mineralogy, and CEC of the rock.

• The adsorption characteristic is not a deficiency of this technol-ogy, but creates retained resistance against flow and diverts flow into unswept zones.

• The basic screening criteria form a procedure for evaluation of the TAP application potential.

• The performance of the TAP is better in high-permeability-con-trast and low-Kv /Kh reservoirs.

• Treatment concentration and slug size depend on reservoir heterogeneity (permeability contrast, Kv /Kh) and mobility ratio,

among other factors.• TAP is capable of creating large RFs in highly permeable porous

media and is adsorbed onto the porous media.• Two simulation approaches were proposed to model character-

istics of the TAP. The chemical-reaction approach is based on a reaction between polymer and crosslinker to generate TAP, and it is controlled by time and temperature. In the single-com-ponent approach, physical characteristics such as viscosity and adsorption increase with heat and time, and the rate of increase depends on the product grade and transit time in the thief zone. Results presented in this paper are based on the single-compo-nent approach, the preferred approach because only one chemi-cal component is injected and it remains a single component throughout the simulation, which is similar to the characteristics of the TAP.

Nomenclature A = temperature-dependent coeffi cient of Langmuir adsorption Adsi = adsorption level of Component i at Concentration C AdsMax = maximum adsorption level at maximum concentration B = temperature-dependent coeffi cient of Langmuir adsorption RFMax = maximum resistance factor RKW = permeability-reduction factor Zi = fl uid composition of Component i

AcknowledgmentsThe authors would like to thank the Reservoir Engineering and Laboratory Research teams at TIORCO for technical support and TIORCO management for support and permission to publish this work.

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Gholamreza Garmeh is a Reservoir Engineer at TIORCO. He is responsible for modeling and design of chemical-flooding and conformance-improvement projects. His research interests are chemical and miscible gas EOR techniques and numerical reservoir simulation. He holds a BS degree from the Petroleum University of Technology in Iran and MS and PhD degrees from the University of Texas at Austin, all in petroleum engineering. He serves as peer-reviewer for SPEREE and SPE Journal.

Mehdi Izadi is a Senior Reservoir Engineer at TIORCO. He has more than 9 years of experience in reservoir simulation and EOR techniques. He is responsible for modeling and design of chemical-flooding projects and support of post-treatment


evaluation. He holds an MS degree in petroleum engineering from the Colorado School of Mines and is currently pursuing a PhD degree at the same institution.

Mehdi Salehi is a Senior Research Scientist for TIORCO. His research interests include conformance correction technologies (poly-mer, polymer-gels, CDG, and BrightWater) and EOR technology development and applications. He holds a BS degree in petro-leum engineering from the Petroleum University of Technology in Iran and MS and PhD degrees from the University of Kansas.

Jorge L Romero is a Senior EOR Reservoir Engineer for TIORCO. He began his professional career in 1998 at Petroleos de Venezuela S.A (PDVSA). In September 2003, he joined TIORCO and has been working exclusively in IOR/EOR projects, evalu-ating the technical feasibility of EOR processes for TIORCO customers worldwide. Romero holds a BS degree in petroleum engineering from the University of Zulia (Venezuela). He has authored or coauthored several SPE papers and TIORCO’s internal technical notes.

Charles P. Thomas is the Director of Reservoir and Technical Services for TIORCO. His career of over 40 years has been focused on EOR technology development and applications and reservoir engineering. Previously, Thomas held research

and management positions with Phillips Petroleum Company, was director of the Petroleum Recovery Research Center at New Mexico Tech in Socorro, an Engineering Fellow at the Idaho National Laboratory, and a Senior Energy Analysis at SAIC before joining TIORCO in 2008. He holds a BS degree in mechanical engineering from Auburn University, and MS and PhD degrees from the Georgia Institute of Technology. Thomas has authored or coauthored numerous SPE papers and DOE publications, and has served as an SPE Distinguished Lecturer.

Eduardo J. Manrique joined TIORCO in 2009 as a Senior Reservoir Engineer before becoming Director of Reservoir Engineering in January 2011. He began his professional career in 1989 with PDVSA, where he investigated IOR processes. Manrique even-tually became IOR Manager and community knowledge leader on EOR methods for medium and light oils for PDVSA E&P Division. In 1996–1997, Manrique worked for STATOIL in Norway as part of a special agreement on WAG technologies with PDVSA. After 14 years with PDVSA, he became Enhanced Recovery Program Manager for the Center for Energy and Technology of the Americas (CETA) in Florida with the support of the U.S. DOE (2003–2005) and Senior Reservoir Engineer/Project Manager for international and U.S. EOR projects at Questa Engineering (2005–2009).

Thermally Active Polymer to Improve Sweep Efficiency of Water Floods: Simulation and Pilot Design...

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