SPE 146107

Errors and Repeatability in VSARA Analysis of Heavy Oils Wenhui Wu, Milad Saidian, Stuti Gaur, and Manika Prasad, Colorado School of Mines

Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Heavy Oil Conference Canada held in Calgary, Alberta, Canada, 12–14 June 2012. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

Increasing demands for world energy resources have accelerated the development of unconventional resources, especially of

heavy oil reservoirs. Yet, the recovery of heavy oils remains challenging mainly due to variations in their viscosity. It is well

known that chemical components of heavy oil control fluid properties, such as density, viscosity and shear modulus. Open

column liquid chromatography is used to separate the Saturate, Aromatic, Resin, and Asphaltene (SARA) fractions. Although

SARA fractions are a common method to report heavy oil compositions, they can have over 20 % errors. In this work we

discuss potential error sources and establish a best-practice methodology to reduce the errors, which results in developing a

modified SARA method (VSARA) to determine the composition of heavy oil. Experimental results show that the evaporative

components of heavy oils, Volatile (V) fractions, are a major source of error in SARA fraction estimates. By tracking weight

changes at every step of the SARA fractionation, errors are greatly reduced. Based on the comparison between SARA and

VSARA results, VSARA fractions have a significantly lower error (within a 5% range) than SARA fractions alone. Multiple

measurements for a single sample by different operators revealed that VSARA measurements are repeatable. Structural

differences between the fractions have been verified using Fourier Transform Infra-Red (FTIR) spectroscopy, which shows

the reliability of the proposed SARA method. We also compare our VSARA analyses with viscosity and show that viscosity

of heavy oils correlates with resin and asphaltene fractions at concentrations above 25%; below 25%, it is uncorrelated. Since

heavy oil composition can change with depth, viscosity can be expected to vary as well. Accurate information of changes in

the VSARA fractions can be used to evaluate viscosity and viscosity heterogeneity in heavy oil reservoirs, select appropriate

recovery methods, populate reservoir models with viscosity heterogeneity, and thus predict reservoir productivity more

accurately.

1. Introduction

As the world faces declining production from conventional reservoirs and an ever-increasing demand for energy,

development of unconventional oil reservoir, especially of heavy oils, becomes critical in the petroleum industry. There are

abundant heavy oil resources in the world. Total world oil resources are estimated to be about 9-13 trillion barrels, with the

breakdown being 30% conventional oils and 70% heavy oils (Meyer, 2003).

More than one trillion barrels of heavy oil in place are located in Canada, Venezuela, and Russia and more than 100

billion barrels of heavy oil are in Alaska and California (Figure 1 from Dusseault, 2004). In Canada, heavy oil production

takes up more than 50% of total oil production and is considered as a “conventional oil” resource (Bott, 2004). The Orinoco

tar sands in Venezuela are the world’s richest oil deposits; with an estimated 500 billion barrels of recoverable heavy oil, ;

they surpass the oil reserves in Saudi Arabia. More than 30 countries in the world have abundant heavy oil reserves. Thus,

developing heavy oil resources has become a sustainable form of resource development strategy in these countries (Schenk,

1991).

Heavy oils have API gravities between 10º and 22º as defined by the US Department of Energy. Extra heavy oils are

denser than water with less than 10º API gravity. In comparison, the densities of conventional light oils are between 30 to 40

ºAPI units. Density and viscosity are significantly higher in heavy oils as compared to conventional oils and can be used

distinguish them from conventional oils. Conventional oil viscosities range from 0.1 cp to about 10 cp while heavy oil

viscosities are above 1,000 cp and could reach up to more than 1,000,000 cp (Meyer, 2003). Heavy oils contain abundant

resin and asphaltene fractions with large molecules that contribute most to the high density and viscosity.

High viscosity of heavy oils makes these reservoirs special in terms of reservoir performance, reservoir modeling, shear

properties of fluids and heavy-oil saturated rocks, and seismic mapping.

2 SPE 146107

Viscosity is the ability of the oil to flow in the reservoir during oil production process. For example, heavy oils with the

same API gravity in a reservoir exhibit different viscosities in summer and winter producing considerable seasonal changes

in the oil production. Oil viscosity is the most important fluid property that affects reservoir productivity and hence the oil

recovery factor (Huang, 2006). Heavy oil reservoirs can have considerable viscosity heterogeneity that can affect reservoir

productivity. In these reservoirs, fluid properties, in particular oil viscosity varies greatly in a short distance, which makes

viscosity heterogeneity more important than reservoir heterogeneity (Huang, 2006; Larter, 2006; Gates, 2008). Thus,

reservoir models need to consider viscosity heterogeneity in addition to rock heterogeneity.

Heavy oil shear properties are strongly dependent on its temperature and frequency. The bulk and shear moduli decreases

linearly with an increase in temperature. Heavy oils act like solids around 0 ºC and like liquids around 20 ºC (Watson et al.,

2002; Han et al., 2005; Batzle et al., 2006; Behura et al., 2007; Hinkle, 2007; Das, 2008; Johnson, 2009). Thus, seismic

characterizations of heavy oil reservoirs differ from conventional oil reservoirs; their resin and asphaltene fractions contribute

to shear velocity. Further, the Vp-Vs ratio is a good lithology discriminator of heavy oil reservoir (Dumitrescu, 2007).

Researching individual heavy oil chemical components is seen as a solution to determine heavy oil viscosity and shear

modulus. Investigations of individual heavy oil component: Saturates, Aromatics, Resins and Asphaltene (SARA) by open

column liquid chromatography reveal that these heavy oil chemical components do influence the heavy oil viscosity and

shear modulus as a whole (Pierre, 2004; Hinkle et al., 2008; Johnson, 2009). Chemical separation methods of fluid mixtures

include column chromatography and molecular absorption spectroscopy. Column chromatography is classified into gas

chromatography, liquid chromatography and supercritical fluid chromatography (Skoog et al., 2007). Open column liquid

chromatography, in other words, SARA fractionation is one of the most common compositional analysis methods for

petroleum samples and a screening criterion for asphaltene stability of reservoir fluids due to pressure depletion or

commingling of different fluids (Kharrat et al., 2007). Johnson (2009) showed that current SARA fractionation methods are

insufficient to predict viscosity due to their imprecise procedures and inconsistent results. SARA analysis performed on the

same sample gave large variations; the differences of SARA fractions are about 20% by weight (Johnson, 2009).

Figure 1: Heavy oil global view showing reserves and production strategy being used (Dusseault, 2004).

Argillier (2001) showed that asphaltene fractions control heavy oil viscosities: in a “dilute system” with asphaltene

concentration less than 10%, viscosity increases slowly with increasing asphaltene content whereas in a “semi-dilute system”

with asphaltene concentration above 10%, viscosity increases dramatically with asphaltene content. Hinkle (2007) found that

correlations between either resins or asphaltene and viscosity were poor. However, a good linear relationship existed between

the resin + asphaltene content and heavy oil viscosity. Similarity in size and chemical composition of heteroatams and polar

compounds of the resins and asphaltenes promotes entanglement with each other and leads to a good correlation between the

resin + asphaltene content and heavy oil viscosity (Hinkle, 2007). Johnson (2009) showed a linear correlation between API

gravity, viscosity, and shear modulus with asphaltene + resin content of the heavy oil.

In this paper we developed an improved procedure to measure repeatable quantities of the saturate, aromatic, resin and

asphaltene fractions in heavy crude oil with open column liquid chromatography method. The newly established procedure

allows repeatable measurements of heavy oil VSARA fractions and increased the accuracy of the results. Distinction between

different fractions also has been verified using FTIR spectroscopy. Moreover, heavy oil chemical composition is correlated

with sampling depth, heavy oil viscosity and shear modulus to find out the relationship in between.

SPE 146107 3

2. Experimental Setup and Procedure

Here we describe the basic principle and methodology of the open column liquid chromatography experiment, in other

words, the Saturates, Aromatics, Resins and Asphaltene (SARA) Fractionation experiment and the repeatability and potential

errors in the existing SARA separations as well as our proposed method with repeatability tests. Also SARA fraction has

been tested with FTIR Spectroscopy to confirm the distinction between different fraction by using SARA method.

2.1 Principle

Crude oils are composed of saturated hydrocarbons, aromatic hydrocarbons, resins and asphaltenes. The definitions of

these fractions are as follows: Saturates, also called paraffins, are saturated, straight chain hydrocarbons, and have the

formula CnH2n+2, (naphthenes have cyclic saturated hydrocarbons and have the formula CnH2n). Aromatics compounds are

hydrocarbons with at least one benzene ring. Aromatics are found to a small degree in light oils but their presence increases

greatly with decreasing API gravity and they could contribute to more than 30% in heavy oils. Resins are larger molecules as

compared to saturates and aromatics. They contain different atoms such as sulfur, nitrogen or oxygen elements. Resins

readily dissolve in paraffins and aromatics. Asphaltenes are the largest molecules that are dispersed as colloids in paraffin and

aromatics. Asphaltenes have high molecular weight with high viscosity and contain substantial amounts of nitrogen, sulfur,

or oxygen atoms in addition to hydrocarbons (McCain, 1990).

In chromatographic separations, the sample is dissolved in a mobile phase and filtered through an immiscible stationary

phase. In the separation process of heavy oil, the maltene is dissolved in a mobile phase, such as iso-octane. The solution is

filtered through the stationary phase, composed of silica gel and alumina packed in a column. The polarity of the fractions

increases from low in saturates, to intermediate in aromatics, and high in resin. Silica gel and alumina, used as polar

adsorbents, adsorb the components of maltene according to their polarity. The components with strong polarity are retained

by the silica gel and alumina and the components with low polarity go through the column with the mobile phase. Saturates,

with very low polarity, go through the column first with iso-octane as mobile phase. Aromatics, with higher polarity, are

separated second by using benzene, which absorbs aromatics. Resins, with the highest polarity, are separated last by using a

very strong polar solvent, methanol (Scott, 1992).

2.2 Experimental Procedure

Heavy oil usually contains a considerable amount of volatile material which must be considered for accounting 100 %

yield in SARA separation. Most open column choromatographies suffer from inaccuracies stemming from weight losses or

gains due to incomplete drying and loss f volatile components during various drying events. These descrepencies are dealt

with by either forcing all fractions to 100% or by topping. The procedure of topping is the preferred practice for the removal

of volatiles from the heavy oils prior to SARA analysis. Topping involves heating under atmospheric or reduced pressure

conditions along with distillation or rotary evaporation. This topping technique strips not only the volatiles but also the semi-

volatiles from the heavy oil. There are several procedures for SARA experiments in which the separation is based on

solubility in different solvents with different polarities. In this work we have used the United States Geological Survey

(USGS) standard method as the base method (USGS Website, 2010) and in order to account for volatile loss and a more

precise accounting of SARA fractions, we have modified the evaporation and weight tracking methods of USGS method to

develop a new VSARA method, where the total weight after the SARA separation is 100%, that includes weight fractions of

organic volatiles + moisture, asphaltenes, saturates, aromatics and resins.

2.3 Improvements – The VSARA Method

The most important improvement in the USGS procedure was to track volatiles at each step during the SARA

experiment. Heavy oil weight loss is checked continuously and heavy oil samples are analyzed for their saturate, aromatic,

resin, asphaltene, and volatile content. Volatile content refers to the weight change during the SARA process thus this

experiment is named “VSARA”, with the assumption that all the weight change are caused by volatile content. The

experimental procedure followed to obtain the percentage for volatiles is tracked at four stages. Initial Nitrogen drying of

heavy oil removes moisture and volatiles from the sample. Since the sample (heavy oil) was very viscous dilution with the

volatile organic solvent (iso-octane) was required and its removal through evaporation under nitrogen assists in removal of

organic volatile components.

The experimental procedure is shown in Figure 2. 50 to 100 mgrr of oil sample was weighed (W2) and nitrogen dried for

8 hours (W3). To the oil sample iso-octane was added and dried again under nitrogen for 8 hours (W4). W2, W3 and W4 are

the weights of oil sample after each stage. Asphaltene were precipitated out by the addition of iso-octane to the oil sample

and filtered, the filterate was the Maltene and Asphaltenes were extracted from the filter using chloroform. Maltenes were

further separated dequencially to Saturates, Aromatics and Resins by column choromatography using solvents iso-octane,

toluene, benzene:methanol (60:40) respectively.

Volatiles were tracked during the removal of solvent from the asphaltene and maltene fractions and during evaporation

of solvent from saturate, aromatics, and resins fractions. Volatile components lost during the process are calculated by weight

difference and the calculation method is given below:

4 SPE 146107

Volatile 1: Initial nitrogen drying process. The weight of volatile 1 is equal to the initial heavy oil weight minus heavy

oil weight after nitrogen-drying process (Volatile 1=W2-W3).

Volatile 2: Solvent drying process. The weight of volatile 2 is equal to heavy oil weight after nitrogen drying process

minus heavy oil weight after solvent-drying process (Volatile 2=W3-W4).

Volatile 3: De-asphaltene process. The weight of volatile 3 is equal to heavy oil weight after solvent-drying process

minus the total weights of dried maltene and asphaltene (Volatile 3=W4-(AS+M)).

Volatile 4: Open column liquid chromatography process. The weight of volatile 4 is equal to maltene minus the total

weights of saturate, aromatic and resin fractions (Volatile 4=M-(S+AR+R)).

The VSARA procedure for drying and evaporation of the heavy oil and separated SARA fractions was consistent

throughout the experiment. Nitrogen (inert) gas was used for drying which when purged into the sample matrix, removed the

organic volatiles and moisture. Nitrogen gas immediately removes molecules of water or organic solvent being evaporated

that enter the vapor state, decreasing the partial vapor pressure, not giving the solvent molecules a chance to return to the

liquid, thus increases the evaporation rate. Evaporation of organic solvents from the sample further assists in irretrievable

removal of the volatiles. Thus the loss of organic volatiles and moisture from heavy oil and separated SARA fractions at

ambient temperature under constant nitrogen flow rate was taken into consideration.

Figure 2: Open column liquid chromatography experiment separation process with solvents used for separating SARA composition of heavy oils. Notice that after each N2 drying process the sample is weighted precisely and the weight differences before and after N2 drying in each step is the volatile weight of that step. Measuring these values improves the precision of SARA fractions significantly.

Comparing with conventional methods that normalize all SARA fractions to be 100%, the VSARA calculation method

records the weight loss in the SARA experiment process and the total weight goes to 100% only when adding SARA

fractions and volatile fraction together.

The second improvement is using exact volume of solvents for each step to keep the consistency at all experiments.

During the de-asphaltene process, in the traditional SARA method after asphaltene separation process we used to evaporate

the maltene and iso-octane solution to reach 0.5 ml of solvent. The measurement of the volume of solvent while it is under

the nitrogen evaporator was difficult and in most cases it was not precise. In the new method maltene solution is evaporated

completely, then the maltene weight is recorded, and 0.5ml iso-octane is added in dry maltene again and complete mixing is

achieved using sonic mixers. The third improvement is designing the nitrogen evaporator in a way that gas flow rate is

controllable during all evaporation processes to make the experiments as repeatable as possible and omit the sources of

irepeatability.

2.4 Weight Fraction Calculation

In this paper a new approach to SARA experimentation has been discussed which improves the SARA fractions

measurement precision by including the volatile weights in each step of separation process. In this part, based on the

SPE 146107 5

extensive experimental works and results we propose a different methodology to calculate the fractions based on the weight

measurement. Experimental results of oil samples named “C-St” are analyzed to find the best methodoly of calculation of

fractions using the measured weights in each separation step.

Normally, SARA fractions are calculated by dividing the weight of SARA fractions by heavy oil weight. Heavy oil

weights are usually measured in three different ways among various laboratories: (1) the initial heavy oil weight, (2) dry

heavy oil weight after heavy oil is dried by nitrogen, and (3) heavy oil weight after evaporation by nitrogen and iso-octane or

heptanes are added as solvent and evaporated again, called “solvent dry”. SARA fraction comparisons of these methods are

shown in Figure 3 and Figure 4.

Figure 4: Comparison of SARA fraction percents calculated using (a) C-St and (b) U-BP heavy oil initial weight and dry heavy oil weight. SARA fraction calculated based on dry heavy oil weight is systematically higher than initial weight.

Figure 3 shows that the percent of C-St heavy oil SARA fractions calculated using dry heavy oil weight is systematically

higher than initial weight because heavy oil weight after drying process is less than initial weight, especially for saturate and

aromatic fractions. Some laboratories use the initial heavy oil weight to calculate the SARA fraction and normalize SARA

fractions to 100%. This does not consider the volatile content and underestimates the saturate and aromatic fractions.

Figure 4 compares the percent of SARA fractions calculated using heavy oil initial weight and heavy oil weight after

adding solvent and evaporation. For C-St heavy oil samples, SARA fractions calculated based on heavy oil weight after

solvent drying process are higher or lower than initial heavy oil weight. Comparing heavy oil initial weight and weight after

adding solvent and drying process, there is weight loss or gain for different oils. The weight loss is caused by the volatile lost

and the weight gain is caused by solvent trapped inside the oil sample. For U-BP heavy oil samples, SARA fractions based

on heavy oil weight after solvent drying process is systematically higher than initial heavy oil weight due to the weight loss

of heavy oils in the solvent drying process.

Figure 4: Comparison of SARA fraction percent calculated based on (a) C-St and (b) U-BP heavy oil initial weight and heavy oil weight after adding solvent and evaporation.

(b) (a)

(a) (b)

6 SPE 146107

Figure 3 and Figure 4 show that when using different heavy oil weight to calculate SARA fractions, resin and asphaltene

fractions are relatively steady while saturate and aromatic fractions vary greatly.

VSARA results of C-St samples in Table 1 show that in the nitrogen drying process, heavy oils lose some weight, named as

“Volatile 1” and there is weight gain or loss after adding iso-octane, named as “Volatile 2”, weight gain may be caused by the

trapped solvent in the sample matrix due to incomplete drying and loss of weight is due to the loss of organic volatiles +

moisture assisted by the drying of solvent. Although adding the total volatile lost during all the steps of this experiment and

the SARA fractions together keeps the total VSARA fraction percentage to be consistent as 100%.

Table 1: C-St heavy oil VSARA fractions measured during the experiment. Adding fractions excluding volatile fraction results in a total percentage less than 100% and needs to be normalized which leads to in accuracies. By adding volatile weight fraction, summation of all fractions is 100 percent and does not need normalization any more.

Samples V1 V2 V3 V4 Volatile Saturate Aromatic Resin Asphaltene Total

C-St-16-402.3 1% 19% -8% 6% 17% 27% 27% 17% 12% 100%

C-St-16-422.1 2% -1% 4% -3% 1% 31% 31% 25% 12% 100%

C-St-09-425.3 6% -3% 10% 1% 14% 26% 27% 20% 13% 100%

C-St-16-428.7 13% -10% 7% 5% 14% 24% 28% 19% 15% 100%

C-St-09-434.3 20% -4% -6% 1% 10% 25% 25% 23% 17% 100%

3. Experimental Results and Discussion

In this part some experimental results are presented using VSARA method which is performed by different trained

operators. We present the experimental result of each operator working on the same sample in order to investigate the

repeatability of the VSARA method. Also using different solvents on the precision of the VSARA results are investigated.

3.1 Repeatability

Analytic SARA experiments which had been conducted commonly by commercial laboratories differ significantly, either

in different laboratories or different analysis on the same sample by the same laboratory (Johnson, 2009). Therefore,

controlling the precision of SARA composition analysis experiments is a major objective of this work.

The measured SARA fractions are affected by changing solvents, packed columns, human errors, or other experiment

conditions such as change in humidity and room temperature. To maintain consistency in the experimental results the same

sample was measured repeatedly by one operator, several operators, and by changing solvents. For this purpose SARA

experiment has been conducted 28 times on the same heavy oil sample, CLHO2, by different operators. Table 2 shows the

details of experiments in terms of operator, run time and the method which is used for fractionation.

Table 2: Records of SARA experiment conducted towards CLHO2 sample. USGS and CSM denote the laboratories located at Colorado School of Mines and United States Geological Survey, respectively.

Experiment

Conductors

Run

Time

Sample

Numbers

Experiment

Location

Operator (1) Mar-09 4 USGS

Operator (1) Jun-09 10 CSM

Operator (2) Apr-10 4 CSM

Operator (3) Apr-10 4 CSM

Operator (4) Jun-10 4 CSM

Operator (1) Jun-10 2 CSM

The SARA experiment was conducted in USGS laboratory four times by Operator 1, and the results are shown in Figure

5. Resin fractions have the biggest differences of the maximum and minimum values. The same sample has been tested by

the same operator for ten times in the CSM laboratory and the results are shown in Figure 6. All the results are in the range of

5% of mean value and show the repeatability of the the experimental data by the same operator in CSM.

SPE 146107 7

Figure 5: CLHO2 sample SARA composition measured by Operator 1, in Mar. 2009 for four times in USGS using traditional SARA method.

Figure 6: CLHO2 sample SARA composition measured by operator (1) in June 2009 for ten times in CSM using VSARA method.

As we can see in Figure 6, the average values of saturate, aromatic, resin and asphaltene fractions are 22%, 42%, 12%

and 20%, respectively. The differences of maximum and minimum values for saturate, aromatic, resin, asphaltene fractions

are 3%, 5%, 5% and 4%, respectively. The aromatics with 42% average proportion clearly dominate the heavy oil

composition while the resins average proportion, with 12%, is a minor component.

Aromatics and resins are separated out by the column in sequence based on color (aromatics front is orange color and

resins front is brown color), it is difficult to clearly differentiate between them. This leads to an inaccuracy of separating

aromatics and resins proportions by color change only during column chromatography process. By adding aromatics and

resin proportions together, the result have even less fluctuation: The average aromatics and resins proportions in CLHO2

sample are 42% and 12%, respectively with a maximum difference of 5% in each case. By adding the aromatics and resins

fractions together, we get an average value of 54% and a maximum proportion deviation of 2%.

Same measurements with the standard VSARA procedure have been performed by three trained operators at CSM

laboratory to investigate the effect of human errors committed by different operators on the precision of the measurements.

Their results are shown in Figure 7. A good repeatability is shown comparing the results got from these three operators and

the results from operator (1).

Repeated SARA experiment on CLHO2 showed that the SARA total percentage should be more than 95%. From Figure

7, Operator (2)’s data usually have high weight loss and the 4th run by Operator (3) on CLHO2 sample shows an extremely

high aromatics fraction. These data are not used for further analysis.

8 SPE 146107

Figure 7: SARA fractions of CLHO2 sample measured by three different operators. ∆w refers to average weight loss during SARA experiment.

A comparison of the SARA results from these three operators to those by Operator (1) in 2010 is shown in Figure 8. In

general good repeatability among the different conductors is demonstrated. According to Figure 8, the resin and asphaltene

composition measured by these students overlap with Operator (1)’s data, the biggest differences exist for the measured

saturate fraction. The aromatic fraction appears to be in a relatively steady range.

SPE 146107 9

Figure 8: Comparison of SARA composition measurements of CLHO2 sample by Operator (1) made at 2010 to the results obtained by three undergraduate researchers.

3.2 Solvents

SARA composition experiments are frequently performed in industry, and there are many solvents used for separating

the SARA components. In the CSM laboratory, the saturate fraction is separated by iso-octane while heptane is used to

separate saturates in some commercial laboratories. Moreover, the aromatics fraction is separated by benzene in the CSM

laboratory, but toluene is also widely used in industry. For separating the resin fraction, methanol is used in both the CSM

laboratory and commercial laboratories.

A CLHO2 sample was sent to commercial laboratory to measure the SARA composition. A comparison of the SARA

fraction comparisons between the commercial laboratory and this study is shown in Figure 9.

Figure 1: Comparison of the SARA fractions between a commercial laboratory and CSM. Blue color represents the commercial laboratory data and red represents CSM data.

Figure 9 shows that the SARA fractions results from the commercial laboratory differ clearly from those from the CSM

laboratory. The largest difference is between aromatic fractions: 51% by commercial laboratory versus 42% by CSM. For

saturate, resin, and asphaltene components, the differences between two laboratory measurements are also larger than 5%.

When adding SARA fractions together, we notice that the sum of saturates and aromatics yield the total fractions of 68%

and 64%. Similarly, the sum of resins and asphaltene fractions yield total fractions of 32% for both measurements. This

shows that the separation of large molecules (resins and asphaltene) from small molecules (saturates and aromatics) produces

similar results, but the separation of saturates from aromatics, and resins from asphaltene lead to the differences. A potential

source of data variation is that the SARA total fraction from commercial laboratory is normalized to100%, while SARA total

fraction from CSM laboratory is only 96% with 4% volatiles. This causes some differences in estimating SARA fractions as

well between two laboratories.

Resin

Asphaltene

Saturate

Aromatic

10 SPE 146107

The first separation step in both laboratories is separating asphaltene from the other components. To dissolve asphaltene,

the commercial laboratory uses dichloromethane as solvent while the CSM laboratory uses chloroform. Note that the

commercial laboratory leads to a smaller fraction of asphaltene than the CSM. A reason could be that as a polar solvent,

dichloromethane has weaker absorption ability to asphaltene molecules compared to chloroform.

The second separation step is to separate saturates, aromatics, resins, different solvents are used in this two methods.

During the chromatography process, maltene is loaded on the column, saturates are eluted first, and then follow aromatics

and finally the resins. Comparing the solvent used for saturates, n-heptane and iso-octane, the different effects are not so

obvious due to their similar chemical structure.

Benzene and toluene are used to extract aromatics from the column. As discussed previously, swamping these two

solvents does not cause a big difference in the separation process. And the reason of total fractions of saturates and aromatic

are close to each other could be that either benzene or toluene is able to extract both the saturate and aromatic fractions

completely from the column.

The solvents used to elute resins from the column are chloroform/methanol (87%:13% by volume) or benzene:methanol

(60%:40% by weight). Since resins are remaining group of molecules on the column, everything washed out from the column

is considered resins. The solvent mixtures used to dissolve resins are not a key factor in determining the SARA fractions.

3.3 Separation Verification

To verify chemically the distinction between SARA fractions we have used FTIR spectroscopy to characterize the

separtations. FTIR spectra of SARA fractions were recorded on a Thermo Nicolet Nexus 470 FTIR spectrometer. The

infrared region of interest covers the region between 4000 and 500 cm-1. The FTIR spectra of the fractions from the heavy

crude oil are reported in Figure 10. FTIR spectra of saturate fraction show the dominance of aliphatic hydrocarbons its typical

vibrations are observed as follows: Stretching frequencies of C-H bond of alkyl are at 2800-3000cm-1. C-H deformation

peculiar to methyl and methylene group are at 1383cm-1and 1466cm-1respectively. Absences of peak at 1600cm-1 and 3000-

3010 cm-1 provide the proof of absence of aromaticity. The spectra of the Aromatic, Resin and the Asphaltene fractions, apart

from the peaks indicated in saturate fraction also show absorption peaks for C=O (carbonyl group) at 1714 cm-1, stretching of

multiple C=C at 1606cm-1and prominent band indicate the presence –OH and –NH groups at 3600-3100cm-1this band is most

prominent in Asphaltenes and Resins. Presence of aromatic nucleus mono-substituted with di-(1, 2) substitution and tri-(1, 2,

3) substitution is indicated by the presence of absorption in the region of 730-900cm-1. The FTIR spectra indicate a good

separation between Saturates, Aromatics, Resins and Asphaltenes.

3.4 Composition Heterogeneity

To investigate the extent of composition heterogeneity in heavy oil reservoirs, VSARA experiments are performed on

two sets of samples. Each set of samples is taken from the same producing well of a heavy oil reservoir at different dates of

production. Ten U-BP-37 heavy oil samples are collected from the same well from Ugnu formation, the percentages of

VSARA fractions are shown in Figure 11. Also five C-St samples taken from the same well at different dates, were

characterized using VSARA method. The results are shown in Figure 12. It can be seen that SARA fraction percentages vary

greatly among ten different oil samples from the same well, which represents the heterogeneity of reservoir fluid chemical

composition. Correlation of heavy oil SARA fractions with viscosity is presented in the correlation part.

VSARA fractionation analyses were conducted on five C-St heavy oil samples from different depths of two wells, named

“16” and “09” located in the McMurray formation in Canada and ten U-BP heavy oil samples from the same well in the

Ugnu formation in Alaska. The correlations of their chemical composition with depths, density, shear modulus and viscosity

are given below.

SPE 146107 11

Figure 10: FTIR spectroscopy of SARA fractions. This figure indicates indicates a good separation between (a) Asphaltenes (b) Resins (c) Aromatics (d) Saturates. Differences between the indicated wavenumber ranges show the distinction between the fractions in terms of Aromatics and –OH and –NH groups.

Figure 112: VSARA fractions of U-BP heavy oil samples at different dates. The differences between different fractions at different dates are due to the composition heterogeneity in the reservoir.

(a) Asphaltenes

(b) Resins

(c) Aromatics

(d) Saturates

-OH and –NH group

3600-3100 cm-1

Stretching frequencies of C-H

bond of alkyl are at 2800-3000cm-1

Stretching frequencies of C-H bond

of Aromatics are at 2800-3000cm-1

Carbonyl Group at

1714 cm-1

Aromatic Region

730-900 cm-1

12 SPE 146107

Figure 123: VSARA fractions of C-St heavy oil samples at different depths. The differences between different fractions at different dates are due to the composition heterogeneity in the reservoir.

4. Experiments vs. Logging

4.1 Correlate SARA Fractions with Depth

The change in heavy oil chemical composition with respect to depth is shown in Figure 13. Saturate and aromatic

fractions of heavy oil samples do not relate with depth. Although resin fraction increases with depth in general, but there are

large deviations. It can be seen that asphaltene fractions from C-St Samples at different depths increases with the increase of

depth.

The heterogeneity of reservoir oil composition is indicated from Figure 13. Take the two oil samples from well 09 as an

example, the asphaltene and resin fractions of these two oil samples are different for about 5%, and there is only a 20m

difference in depth. If significant amounts of heavy oil samples are obtained from the formation, mapping out heavy oil

SARA fractions with relation to depth could provide a better understanding of the reservoir fluid heterogeneity.

Figure 134: Correlate C-St saturate, aromatic, resin and asphaltene fractions with sample depths. The samples are from two different wells: well 16 and well 09 in Mc Murray Formation, Alberta, Canada.

4.2 Correlate SARA Fractions with Viscosity

Figure 14 shows the correlation between viscosity and chemical composition; the increase in viscosity directly

proportional to an increase of resin and asphaltene components. However, this relation is seen only when resin+asphaltene

fractions are greater than 25%. Argillier (2001) made a similar observation that asphaltene fractions control heavy oil

SPE 146107 13

viscosities. In Argiller (2001) dilute system, defined as asphaltene concentration below 10%, show a gradual viscosity

increase with increasing asphaltene content. When asphaltene concentration is above 10%, so-called semi-dilute systems,

viscosity increases dramatically with asphaltene content. Argillier (2001) contributed this to the entanglement of asphaltene

molecules when asphaltene content is above 10%, which leads to the dramatic increase of relative viscosity. Figure 17 shows

a similar threshold of viscosity change at Resin + Asphaltene content below 25%. This threshold has important implications

for viscosity estimations from heavy oil compositions and need to be studied further.

Since VSARA fractions of heavy oils change greatly along with sample depths, viscosity would vary with depth as

well. Measuring the VSARA fractions of heavy oils is helpful to understand the viscosity as well as the viscosity

heterogeneity of heavy oil in the reservoir. VSARA fractions and viscosity determination, helps in selecting the appropriate

recovery method of the heavy oil. And also, putting the viscosity heterogeneity data into reservoir modeling could assist in

predicting reservoir productivity more accurately. In the heavy oil rock modeling process, the shear modulus generated by

heavy oils is not considered. Measuring VSARA fraction of heavy oils could help in determining shear modulus, and putting

heavy oil shear modulus into seismic mapping and rock modeling could increase the accuracy of the measurement.

Figure 145: Correlate viscosity of C-St heavy oil samples with temperature and depth. Viscosity and Asphaltene+Resin weight fraction are directly correlated above 25 % weight fraction of Asphaltene+Resin. Below this value the correlation breaks down (From Johnson (2009) and Zhang (2010)).

4.3 Correlate SARA Fractions with Density

Density measurements of SARA fractions were conducted by Peramanu (1999) using the Gel Permeation

Chromatography (GPC) method, shown in Table 3. The average density of SARA fractions of Athabasca and Cold Lake

heavy oil samples measured by Peramanu (1999) to can be used to multiply the percentage of SARA fractions measured in

CSM and add them together to predict the heavy oil density. Calculated values are shown in Table 4, which also confirms the

heterogeneity in different samples from different depths. The equation to calculate the density from VSARA fractions is

shows below.

Table 3: Density of saturate, aromatic, resin and asphaltene for Athabasca and Cold Lake heavy oils using Gel Permeation Chromatography (Peramanu, 1999).

Fraction Density (gr/cm

3)

Athabasca Cold Lake Average

Saturates (Sat) 0.823 0.871 0.847

Aromatics (Aro) 0.945 0.912 0.928

Resins (Res) 1.034 1.019 1.026

Asphaltenes (Asp) 1.200 1.180 1.190

Viscosity at 10 Hz, 20 °C

by Johnson (2009) Oil

samples are from worldwide

Viscosity at 10 Hz, 20 °C

by Zhang (2010), oil samples

are from Ugnu formation

14 SPE 146107

Table 4: Density of heavy oil samples from Wells 9 and 16 Mc Murray Formation, Alberta, Canada calculated using VSARA fractions and the

average density values from Peramanu (1999).

Depth

(ft)

Density from VSARA

Fractions (gr/cm

3)

Density from Laboratory

Measurements (gr/cm

3)

Well 9

425 0.94926 1.11

434 0.96673 1.182

Well 1

6

402.5 0.93118 1.058

422.5 0.95802 1.114

428 0.96442 1.36

5. Conclusions

We have developed a methodology to make repeatable measurements of Volatile, Saturate, Aromatic, Resin and

Asphaltene (VSARA) fractions in heavy oils. The major improvement is to track heavy oil volatile components, because they

reduce errors caused by neglecting the organic volatile composition of heavy oils.

VSARA fractions measured using the measurements procedure lies within a 5% error range.

We have demonstrated repeatability of VSARA fractions through: (1) multiple measurements by the same

laboratory operator, (2) by different laboratory operators, and (3) by changing solvents from benzene to toluene.

Structural differences between fractions are verified by FTIR spectroscopy.

Composition heterogeneity is observed: Asphaltene components increase with sample depths for the C-St oil

samples.

The VSARA fractions can be used to derive the density of the heavy oil sample.

Viscosity and Asphaltene+Resin weight fraction are directly correlated above 25 % weight fraction of

Asphaltene+Resin. Below this value the correlation breaks down.

Acknowledgements

We are indebted to Paul Lillis for helping us understand the USGS procedure for SARA analysis. We thank Mike Batzle,

Merrick Johnston, Matt Liberatore, Andy Herring, and John Dorgan for valuable discussions. This work was supported by a

DOE grant (#DE-NT0005663).

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