SPE-194706-MS

Asphaltene Stability Analysis for Crude Oils and Their Relationship With
Asphaltene Precipitation Models for a Gas Condensate Field

Muhammad Arsalan Siddiqui, Syed Mohammad Tariq, Javed Haneef, Syed Imran Ali, and Abdul Ahad Manzoor,
NED University of Engineering & Technology

Copyright 2019, Society of Petroleum Engineers

This paper was prepared for presentation at the SPE Middle East Oil and Gas Show and Conference held in Manama, Bahrain, 18-21 March 2019.

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
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ABSTRACT
Asphaltene deposition can cause production reduction in oil fields and can create problems in surface/
subsurface equipment. The three main factors which affect asphaltene stability in a crude oil are the changes
in pressure, temperature and composition. Composition changes occur as the pressure depletes with time and
fluid becomes heavier or with gas or chemical injection in reservoir. Any of these changes can destabilizes
the asphaltene in crude oil and can cause different operational difficulties, loss in production and increases
safety concerns. The objective of this study is to develop a workflow for modeling asphaltene precipitation
during pressure depletion and its application to develop mitigation strategy via asphaltene stability maps
for a gas condensate field in South Potwar basin, Pakistan

INTRODUCTION
In this study, a workflow, based on thermodynamic principles, is developed to model asphaltene
precipitation. The key to proper modeling of asphaltene problem is the correct splitting of plus fractions
in the fluid composition. This study applies the method of Nghiem et. al. (1997) to model asphaltene
precipitation. In this modeling approach, the precipitated asphaltene is considered as a pure solid. The
parameters used for observation of asphaltene behavior are the interaction coefficient, molar volume of
solid (asphaltene), volume shift parameters and mole% of asphaltene component. Simulation results under
several runs for the asphaltene precipitation are also described. This approach was applied to gas condensate
field in a South Potwar Basin field of Pakistan. Using the proposed modeling workflow, precipitation models
of three different fluid samples were generated and compared to publish results to validate the approach
before their application to develop mitigation strategies.
The asphaltene models are based on assumed values of certain required parameters due to lack of
experimental lab data. To match and validate the generated models, SARA values and the asphaltene
screening method CII (Colloidal Instability Index) is used. The results demonstrate the relation between
SARA values and crude oil stability using the generated asphaltene precipitation curves.
2 SPE-194706-MS

NATURE OF ASPHALTENES
Petroleum fluids consist of four main classes as follows: (McCain, 1990; Pederson et al., 1989) (Nghiem
et al., 1999):

• Paraffins (or Alkanes)

• Napthenes

• Aromatics

• Resins and Asphaltene

Paraffins or Alkanes are single chain hydrocarbon with most common example of Methane. Napthenes
are similar to paraffins but usually contain one or more cyclic structures. Aromatics consist of one or more
ring structures and the atoms are connected by aromatics double bonds.
Resins and Asphaltene are large molecules (size ~ 10 Angstrom, MW ~ 700 amu) which primarily consist
of hydrogen, carbon along with some sulfur, oxygen or nitrogen atoms per molecule and trace amount of
nickel and vanadium. They are poly-aromatic compounds with abundance of ring structures. Asphaltenes
are insoluble in light petroleum components and are dispersed as colloids in fluid system. In oil field
terminology, Asphaltenes are defined as component of crude oil which is insoluble in n-heptane but is
soluble in toluene. Asphaltene micelles (aggregates) are kept in solution by a layer of resins adsorbed on their
surface. Changes in pressure, temperature and composition alter the asphaltene/resins association and may
cause precipitation. During distillation process, when petroleum are separated into fractions, the asphaltene
remains in the heaviest fraction, while resins are distributed through the various fractions according to
volatility. (Nghiem et al., 1999)

SCREENING METHODS FOR ASPHALTENE PRECIPITATION

Crude oils are considered as colloidal system and the stability of these colloidal systems is actually its
resistance to flocculation. The degree of resistance to flocculate can be used as a measurement of dispersion
stability. (Buriro et al., 2012)
Stability of colloidal system and tendency of asphaltene precipitation depends on the number of factors
and can be evaluated using various methods. The most common methods are Colloidal Instability Index
and DeBoer Plot.

Colloidal Instability Index (CII)

This method was introduced by Yen et al. (2001) which is based on the ratio of sum of asphaltene and
saturates to the sum of aromatics and resins.
In this method asphaltene colloidal stability is determined using analysis of Saturates, Aromatics, Resins
and Asphaltene fractions of crude oil. CII is a measure to identify the asphaltene deposition potential of
petroleum systems.
Crude oils with a value of CII less than 0.7 are considered as stable; while, oil systems with CII greater
than 0.9 are considered as unstable colloidal system and prone to asphaltene precipitation and deposition.

De Boer Method
De Boer plot is the commonly known and most widely used method suggested by De Boer et al. (1995) to
predict and evaluate the risk of asphaltene precipitation during depressurization. The method was developed
to find out the thermodynamic conditions at which the oil may start forming solid phase leading to reduction
SPE-194706-MS 3

in flow rate. As shown in Fig.1, evaluation is based on the difference between reservoir and bubble point
pressure and initial density of the reservoir fluid. (De Boer et al. 1995)

Figure 1—De Boer Plot, representing (Pi–Pb) versus ρ (De Boer et al., 1995).

The plot is divided into three regions;

1. Region A: It is an unstable region with high possibility of serious asphaltene precipitation/deposition
2. Region B: With moderate concerns
3. Region C: It is a stable region with slight or negligible asphaltene issues
The unstable, moderate and stable regions are based on calculations of asphaltene super saturation using
the Hirschberg Model (Hirschberg et al., 1984)
Apart from Colloidal Instability Index and De Boer Plot there are some other methods to determine the
crude oil stability like Refractive Index Method (Tianguang Fan et al., 2002) and Asphaltene Resin Ratio
Approach (Jamaluddin et al. 2002) etc.

FIELD DESCRIPTION
This case study is based on a condensate field located in Eastern Potwar Basin of Pakistan. The field was
identified in mid 1950's and was discovered in 1978.
Adhi field is a gas condensate field with two producing formations of sandstones. Most of the wells are
producing from single tubing which means the fluid coming at the surface is the mixture of two reservoirs
fluids. The processing facilities consist of three processing plants, Plant I, II and III, and an Early Production
Facility (EPF). Plant I and II were originally designed to handle the light condensate produced.
During initial operating life of field, no flow assurance issues were encountered with wells producing
light condensate. But during the last decade, starting in 2006, the plants started experiencing the problem of
solid deposition/precipitation. These solid deposits were identified as mostly asphaltene thru composition
analysis.
The current study was initiated in 2017 to understand the asphaltene deposition issue, predict the behavior
of fluid and to recommend mitigation techniques to help minimize the asphaltene precipitation/deposition.

CRUDE OIL STABILITY AND SARA FRACTIONS

SARA fractions are main constituents of crude oil consisting of saturates, aromatics, resins and asphaltene.
Saturates are non-polar fractions and saturated hydrocarbons. Aromatics are polar molecules with one or
4 SPE-194706-MS

more aromatic rings. Resins and asphaltene are also polar substituents but asphaltenes are insoluble in
alkanes (pentane, hexane). (Tianguang Fan et al., 2002).

Relationship between SARA Fractions and CII

The samples studied in this work were obtained from gas condensate field as mentioned above. In the
absence of subsurface samples at close to original reservoir conditions, the basis for this study is liquid
samples collected from different wells at separator conditions.
The saturates, aromatics, resins and asphaltene contents of collected liquid samples are listed in Table 1.
Table 2, presents the observed ratio of asphaltenes to resins (As. /Re.) and saturates to aromatics (Sa. /Ar.),
as well as the results of CIIs for the collected oil samples.

Table 1—SARA Fractions

Sample Saturates Aromatics Resins Asphaltene

No. % % % %

1 72.30 20.20 7.30 0.20

2 80.10 19.30 0.50 0.10

3 65.60 24.10 9.90 0.40

4 70.43 22.68 6.60 0.29

5 75.19 20.41 3.87 0.53

6 72.01 19.19 8.58 0.22

7 80.77 18.48 0.74 0.01

8 81.01 17.64 1.32 0.03

Table 2—SARA Ratios and CII

Sample No. Sat/Arm As/Re CII

1 3.579 0.027 2.636

2 4.150 0.200 4.051

3 2.722 0.040 1.941

4 3.105 0.044 2.415

5 3.684 0.137 3.119

6 3.752 0.026 2.601

7 4.371 0.014 4.203

8 4.592 0.023 4.274

As shown in Table 2, the CII value is more than 0.9 for all samples indicating propensity for asphaltene
precipitation and deposition in various wells in the field.
Correlation between Asphaltene and CII. Asphaltene are heaviest and most polar molecules in crude oil,
soluble in toluene and insoluble in n-heptane (Standard method D2007-80). (Verdier et al., 2006) (Choiri
et al., 2011) (Aske et al., 2002)
From Fig-2 it can be seen that sample-8 which has highest value of CII has very low asphaltene value
and sample-5 with highest value of asphaltene has low CII value. This is in line with conclusion reached
by earlier studies that if crude oil contains low asphaltene, it does not necessarily mean that it has a lower
tendency to precipitate. (Sinnathambi et al., 2012) (Ashoori et al., 2016)
SPE-194706-MS 5

Figure 2—Comparison between CII and Asphaltene Content

Correlation between Resins and CII. Resin molecules behave as stabilizers for asphaltene in crude oil;
they inhibit the major aggregation of the asphaltene particles.(Aske et al., 2002). The CII and the resin
component were studied together to understand the behavior of resin and to find a correlation between them.
Resin has polar constituents. (Zendehboudi et al., 2014) (Ashoori et al., 2016). From Fig-3, it can be seen
from the results of collected samples that increase in resins value decreases value of CII.

Figure 3—Comparison between CII and Resin Value

6 SPE-194706-MS

Correlation between Aromatics and CII. As compare to other fractions of crude oil, aromatics are more
polarizable. Asphaltene are also polar part of petroleum in the form of a complex molecular structure and
contains aromatic chains (Choiri et al., 2011) (Zendehboudi et al., 2014).
Fig. 4 shows the relationship between CII and aromatic values for the collected samples. From Fig. 4,
it can be seen that oils which have higher aromatics value are more stable as compare to oils with low
aromatics. This is in line with conclusion reached by earlier studies that Aromatics are good solvents for
asphaltene molecules. (Zendehboudi et al., 2014)

Figure 4—Comparison between CII and Aromatics Value

Moreover, it can be seen from Table-2 that CII has a trend to the saturate/aromatics ratio. The lower
values of CII show higher asphaltene stability due to the dispersant effect of aromatics and saturates. (Choiri
et al., 2011) (Ashoori et al., 2016)
Correlation between Saturates and CII. The Saturate components are considered as non-polar constituents
of oil. Crude oils with a high content of saturate value contain low content of aromatic and resin fractions,
so these crude oils can be highly unstable. According to the study done by Carbognani and Espidel, it is
reported that reservoirs with high saturate fractions and low asphaltene content are more vulnerable for
asphaltene precipitation/deposition as compare to reservoirs with high asphaltene content but low saturate
fraction (Taylor et al. 1992)
Fig-5 illustrates the relationship between CII values and saturate from eight different samples of crude
oil. It is observed that samples with higher saturate values also have higher colloidal instability index. Fan
et al. demonstrate that the saturate, makes a negative impact to colloidal stability of crude oil. (Tianguang
Fan et al., 2002) (Pfeiffer et al., 1940) (Ashoori et al., 2016)
SPE-194706-MS 7

Figure 5—Comparison between CII and Saturate Value

MODELING WORKFLOW
To predict the asphaltene precipitation during pressure depletion a workflow is developed during this
study. This workflow follows the outline presented by Long X. Nghiem, "Phase Behavior Modeling and
Compositional Simulation of Asphaltene Deposition" PhD Thesis, University of Alberta, 1996.
Following are the main steps required to develop a precipitation model.
– Fluid Characterization
– Specification of solid model phase
– Regression
– Prediction of asphaltene precipitation

Fluid characterization
To begin with asphaltene modeling, a data set is prepared to characterize the fluid by defining the
compositions of main HC components and pseudo-components (C7+) After defining fluid compositions
the next step is plus fraction splitting. The process includes splitting (breaking down) fractions such as C7+
into a single carbon number (SCN) fraction up to C20+ or more. The number of total splitting components
depends upon the molecular weight of heaviest fraction. Higher the molecular weight of heaviest fraction
the more components it will split into.

Specification of solid model phase

The next step consists of splitting the heaviest component in the oil into a non-precipitating component
(i.e. C36+) and a precipitating component (i.e. asphaltene). These two components have identical critical
properties and acentric factor but different interaction coefficient with the light components, which lead
to more precipitation as the amount of light component in the solution increases. (Nghiem et al., 1996)
(Interaction coefficient accounts for interaction between dissimilar molecules. (i.e. between C30+ and
lighter components)
8 SPE-194706-MS

Regression
The purpose of the regression is to tune the cubic equation of state (Peng-Robinson) to match experimental
measurements or to obtain a closer value to experimental data. In this study the regression procedure of
Agarwal et al. (1987) was used. The parameters that we used in regression are interaction coefficient and
solid molar volume. Model was run at different values of these parameters to best match the assumed
experimental data.

Prediction of asphaltene precipitation

To predict the asphaltene precipitation the main step is to specify the fugacity. Fugacity is defined as the
"the tendency of a component to escape from its state." Following is the correlation that the software use
to specify fugacity

Where fs* is the reference fugacity, at the reference conditions Pr and Tr and Vs is the molar volume
of the solid.
The reference fugacity is basically the fugacity of precipitating component calculated by the equation of
state at experimental value of asphaltene onset conditions (pressure and temperature). Reference fugacity
calculation make sure that model will predict the correct onset pressure.
Onset conditions can be determined with the help of different solid detection systems. But, due to
unavailability of experimental onset data in this study, the onset conditions of asphaltene were assumed as
shown in Table-4. The fugacity was calculated from assumed onset pressure & temperatures.

Table 3—Separator Liquid Samples

Pre. Temp. Asp. Content

Sample No. °API
Psig °F Weight%

1 1000 90 40.9 0.2

2 1050 98 59.5 0.1

3 210 92 34.3 0.4

Table 4—Assumed Asphaltene Onset Points

Onset Conditions Asp. Precipitates

Sample No.
Pressure Temp. weight%

1 1200 90 0.01

2 1200 98 0.01

3 300 92 0.01

After completing these four steps, we ran the model with different values of interaction coefficient to
match the assumed experimental data.

MODELING ASPHALTENE PRECIPITATION

The modeling of asphaltene precipitation at separator conditions are demonstrated below using the modeling
workflow mentioned above.
SPE-194706-MS 9

Data
Three liquid samples collected at separator conditions listed in Table-3 were used to predict asphaltene
precipitation during pressure depletion. Experimental data of asphaltene onset conditions was assumed as in
Table-4. In asphaltene modeling, separator pressure is taken as saturation pressure to match it with generated
asphaltene precipitation curves.
Table-5 shows the composition of the samples and other essential data used to model asphaltene
precipitation.

Table 5—Composition of Samples

Component Sample-1 Sample-2 Sample-3

- Mol% Mol% Mol%

N2 0.13 0.3 0.01

CO2 0.23 0.17 0.05

C1 19.71 24.86 4.5

C2 7.14 9 2.69

C3 6.88 8.73 3.52

I-C4 2.58 3.17 1.59

N-C4 4.71 5.82 3.39

I-C5 2.98 3.79 2.62

N-C5 3.42 4.41 3.18

C6 5.39 6.91 5.53

C7+ 46.83 32.84 72.92

RESULTS
Phase envelope of each sample is shown in Fig-6, Fig-8 and Fig-10 was generated to match the maximum
amount of precipitation which is normally around the bubble point pressure. Using the modeling workflow
as mentioned above, asphaltene precipitation curve for each sample was generated. (Fig-7, Fig-9 and Fig-11)
These curves show asphaltene onset pressure and give an estimate of the amount of precipitated asphaltene.
It is observed that generated curves show a good match between the predicted precipitation values and
assumed experimental data. We can see maximum asphaltene precipitation is around the saturation pressure.
It can be seen from Fig-9 that sample-2 which is lightest crude with 59.5 API and lowest asphaltene
content of 0.1 wt% has highest maximum asphaltene precipitation. While Sample-3 (API 34.3) which
has highest asphaltene content of 0.4 wt% has lowest maximum asphaltene precipitation as compared to
sample-1 & sample-2. (Fig-11)
As explained earlier, SARA constituents of crude oils play an important role in the tendency of asphaltene
to precipitate. It is notable that Sample-2 however has lowest asphaltene content but the reason of its higher
tendency to precipitate could be the lowest value of resins, Table-1 as resins stabilize the colloidal system
of crude oil.
10 SPE-194706-MS

Figure 6—Phase Envelope of Sample-1

Figure 7—Asphaltene Precipitation Curve of Sample-1

SPE-194706-MS 11

Figure 8—Phase Envelope of Sample-2

Figure 9—Asphaltene Precipitation Curve of Sample-2

12 SPE-194706-MS

Figure 10—Phase Envelope of Sample-3

Figure 11—Asphaltene Precipitation Curve of Sample-3

CONCLUSION
After comparison of crude oil stability with SARA values and asphaltene modeling based on assumptions
it can be concluded that apart from pressure & temperature changes, stability of crude oil highly depends
upon its composition especially SARA constituents. It is observed that higher asphaltene precipitation is
not directly related to higher asphaltene content but mostly on the amount of saturates and resins.
It is observed that increase in non-polar constituents like saturates increase crude oil instability. The
presence of more saturates means less resins and higher tendency to asphaltene precipitation.
SPE-194706-MS 13

It is observed that maximum asphaltene precipitation is around the saturation pressure (i.e. bubble point)
because as the bubble point achieves the lighter components starts separating out from the system. As the
fluid gets heavier the ratio of resins, aromatics vs saturates increases and system stabilizes.
Finally, the modelling workflow presented in this paper can be used to establish asphaltene onset
envelopes for various hydrocarbon fluids and provide basic data to define operating conditions and
mitigation strategy to prevent asphaltene deposition problems.

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