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An empirical model for predicting crude sludging potential caused by acidizing.

Abstract

Acid stimulation experimental data collected in the laboratory on 231 crude samples from various oil fields were used in this study to formulate an empirical model for quantifying the amount of asphaltic sludge precipitating as a consequence of an acidizing job. Throughout the experiment, individual components of the acid system were introduced separately in order to single out their effects on sludge. The standard API procedures were slightly modified in order to mimic downhole conditions. Data showing the individual effects of acid strength, acid type, solvent preflush, iron control additives, ferrous and ferric ion concentrations, mutual solvent concentration, corrosion inhibitor type, and surfactant types have been used as the basis for formulating an empirical model for the weight percent of asphaltene sludge. The acid-induced sludge model has been validated with stimulation data from the Endicott field. The model is then used to study the effect of various factors on sludging.

A 15% HCL concentration is found to be the threshold for serious acid-induced sludge. Hydrofluoric acid exhacerbates sludging except at low concentrations less than 3%. Asphaltene sludging is promoted by the presence of ferrous and ferric ions. However, Ferric ions cause more sludging. The addition of iron control additives like citric acid, EDTA, and NTA is found to cause sludging. Erythorbic extractant causes less sludging than any of the iron control additives commonly used. The three surfactant types investigated (Fluoro-surfactant, Non-emulsifier, wetting agent) are found to have an identical effect on sludging. The use of a mutual solvent concentration greater than 5% is found to increase the sludging tendency.

Acid-induced asphaltene sludging is becoming an increasing cause of oil well stimulation treatment failure. The proposed model predicts quantitatively the effect of various acid additives on crude oil sludging, and may be used as a designing tool for an acidizing job with minimum sludging potential.

Keywords: Sludging, acid, expert system.

Introduction

Asphaltene deposition is one of the most difficult problems encountered during the exploitation of oil reservoirs. Miscible and immiscible flooding operations exhibit suitable environments for such precipitation. In some cases, asphaltene precipitation can occur during natural depletion and oil transportation and, commonly, during well stimulation (Islam, 1995). Changes in temperature, pressure, and composition during oil production can destabilize the colloidal dispersion of asphaltenes in oil (Hirschberg, 1984). Crude oils are typically categorized as either paraffinic or asphaltenic depending on the nature of the predominant heavy species. Asphaltenes are contained in crude oils in the form of a colloidal dispersion. Amorphous in structure, the asphaltene micelle consists of higher molecular weight compounds surrounded and peptized by neutral resins and aromatic hydrocarbons. The micelle consists of sheets of polycyclic rings containing 6-14 rings per sheet. These sheets are stacked to form the asphaltene particle. The particle has a diameter of 30 to 65 angstroms and a molecular weight ranging from 1,000 to 50,000 (Hirschberg, 1984).

Aggregated asphaltenes can cause a variety of problems in injection and production wells, surface facilities, pipelines, and in refinery operations. Within the formations, aggregation of asphaltenes results in a decrease in absolute permeability, and may change the relative permeability profile. In many occasions, asphaltene deposition has threatened the economic recovery of the oil and increased the cost of production of many oil fields around the world considerably. There has been a considerable effort focused on predicting the appearance and extent of asphaltene precipitation. The amount of asphaltene present in oil is readily quantified by a simple solvent precipitation test; but whether that asphaltene causes problems depends on whether or not it reaches instability during its removal from the reservoir and subsequent transport to the refinery. Detecting the onset of asphaltene precipitation presents greater technical challenges than quantifying the amount initially present in the oil, especially at reservoir conditions. Methods have been developed based on filtration, refractive index, and solubility, to name only a few (Wang et al., 1999; Lababidi et al., 2004).

Acid induced asphaltene sludging is becoming an increasing cause of oil well stimulation treatment failure. Numerous chemical processes involved in an acid system contribute to the effect of acid on sludge potential (Houchin et al., 1990). Asphaltene sludge, which occurs when crude oil contacts acids, can be differentiated from naturally occurring asphaltene deposits. Once formed, this precipitate is extremely difficult to remove. As a result, it can be classified as one of the most severe forms of formation damage. Houchin et al. (1990) provided evidence that sludge and rigid film emulsion tendencies could be classified according to the chemical and physical nature of the specific crude as follows: "Acid induced sludge primarily occurred on crudes with API gravities [greater than or equal to] 27 and asphaltene contents of [less than or equal to] 3% by weight. Crude oils with API gravities [less than or equal to] 22 and asphaltene contents of [greater than or equal to] 4 % by weight typically form rigid film emulsions and subsequently do not sludge."

This study addresses many factors causing sludge formation. These include acid strength, acid type, solvent preflush, iron control and additive compatibility. The objective of this research is to develop an expert system that uses minimum production data to estimate the potential weight percent of asphaltene sludge that may deposit as a consequence of an acidizing job.

Methodology

Acid stimulation experiments were performed in the laboratory on 231 crude samples from 17 different formations by Houchin et al. (1990). Throughout the experiment, individual components of the acid system were introduced separately in order to single out their effects on sludge. The standard API procedures were slightly modified in order to mimic downhole conditions. Samples were left for 45 minutes in a constant temperature bath at 180 [degrees]F, in order to simulate static contact time between the acid and the oil. Only fresh wellhead crude samples that have been collected in less than 3 hours were used in the experimental tests. This measure was undertaken to prevent aging effect on sludging. Sludge is known to increase considerably as oil samples age. In order to prevent loss of the semi-liquid sludge that may form, the 100 mesh screens which allow material less than 100 ?m to pass through were abandoned. Filter paper which retains material 8 ?m in size or larger was used instead.

Collected data showing the individual effects of acid strength, acid type, solvent preflush, iron control additives, ferrous and ferric ion concentrations, mutual solvent concentration, corrosion inhibitor type, and surfactant types are documented by Houchin et al. (1990). Sample results are shown in Figures 1 through Figure 3. Houchin et al. (1990) results, presented as histograms, have been used as the basis for developing empirical correlations. Using these correlations, we formulate the total potential percent increase in sludge out of the original stock tank asphaltene weight percent ([P.sub.T]). The total potential increase in sludge out of the original stock tank asphaltene weight percent is given as an accumulation of the individual effects of acid strength and type, concentration of ferrous and ferric ions, the type of iron control additive, the surfactant type used, the mutual sovent concentration, and the type of corrosion inhibitor as follows:

[P.sub.T] = [P.sub.[alpha]] + [P.sub.[beta]] - [P.sub.[gamma]] - [P.sub.[theta]] + [P.sub.[epsilon]] + [P.sub.[phi]] + [P.sub.[lambda]]

[P.sub.[alpha]] is the increase in sludge out of the original stock tank asphaltene weight percent due to HCl concentration effects. Based on results of Figure 1, when HF % = 0, this term is given by:

[P.sub.[alpha]] = 0.2C 0 [less than or equal to] C [less than or equal to] 10 (2)

[P.sub.[alpha]] = 0(6C/5) - 10 10 [less than or equal to] C [less than or equal to] 15 (3)

[P.sub.[alpha]] = 9.076C- 128.14 15 [less than or equal to] C [less than or equal to] 28 (4)
Figure 1: Effect of HCl acid strength on sludging
(Houchin et al., 1990).

HCL CONCENTRATION, % %INCREASE IN SLUDGE

5% <1%
10% 2%
15% 8%
28% 126%

Note: Table made from bar graph.


In this notation, C is the % HCL concentration by volume. If HF % [not equal to] 0, then results of Figure 2 are correlated to the ratio of HCl to HF concentrations. [P.sub.[alpha]] takes the following expression:

[P.sub.[alpha]] = -148.74 + 154.23[R.sub.1] - 39.41 [R.sub.1.sup.2] + 2.9748[R.sub.1.sup.3] (5)

[R.sub.1] is the ratio of HCl to HF concentration given by:

[R.sub.1] = (%HCL by volume / %HF by volume) (6)
Figure 2: Effect of HCl:HF acid strength on sludging
(Houchin et al., 1990).

ACID CONCENTRATIONS, % HCL: %HF % INCREASE IN SLUDGE

5:0.8 2%
7.5:1.5 9%
12:03 28%
15:05 37%

Note: Table made from bar graph.


Equation (5) is valid for 2.5 [less than or equal to] [R.sub.1] [less than or equal to] 6.25. The term [P.sub.[beta] reflects the effects of both Ferrous and Ferric ions on sludging. If pure HCl acid is used, the term [P.sub.[beta]] is given as a function of Ferrous (FeII) and Ferric (FeIII) ion concentration ([I.sub.2] and [I.sub.3] , respectively) in ppm as follows:

[P.sub.[beta]] = -152 + [5.8.sup.*] [10.sub.-3]I2 + [4.68.sup.*][10.sup.-2][I.sub.3] (7)

If HCl is mixed with an organic acid such as Acetic acid, or Formic acid, then:

[P.sub.[beta]] = -15.6 + 3.4 * [10.sup.-3] [[I.sub.3] + [I.sub.2]/5] (8)

The term [P.sub.[gamma]] reflects the effect of iron control additive (ICD) on sludging. For standard dosage, the effects of a particular iron control additive are summarized in Table 1. The term [P.sub.[theta]] accounts for solvent preflush effects on sludging. Solvent preflush reduces sludging. In addition, the use of a solvent preflush in acidizing helps in dissolving organic deposits, and breaks emulsion blocks. This term is correlated as a function of the Ferrous and Ferric ion concentration (in ppm) as follows:

[P.sub.[theta]] = 124.778 - 6.3167 * [10.sup.-3] [[I.sub.2] + [I.sub.3]] + 1.92787 * [10.sup.-6] [[I.sup.2.sub.2] + [I.sup.2.sub.3] (9)

The term [P.sub.[epsilon] takes on values that vary according to the surfactant type in standard dosage use (Table 2). The term [P.sub.[phi]] evaluates the effects of mutual solvent concentration on sludge percent increase. Results of Figure 3 evaluate the effects of the commonly used mutual solvent in acid jobs, ethylene glycol mono butyl ether (EGMBE). These results are correlated as a function of the mutual solvent concentration (I) by the following expression:

[P.sub.[phi]] = 65.857 - 38.248I + 6.2143 [I.sup.2] - 0.22381[I.sup.3] (10)
Figure 3: Effect of mutual solvent concentration (EGMBE) on
sludging (Houchin et al., 1900)

MUTUAL SOLVENT CONCENTRATION %INCREASE IN SLUDGE

3% <1%
5% 2%
8% 43%
10% 81%

Note: Table made from bar graph.


The concentration I is given in percent. The term [P.sub.[lambda]] accounts for the effect of corrosion inhibitor. Values of [P.sub.[lambda]] are given in Table 3 for standard dosage. Corrosion inhibitors are acid treating fluids that are used to prevent acid attack on metal surfaces. The American Petroleum Institute classified corrosion inhibitors with respect to formation of asphaltene sludge as Classes # I, II, and III (Houchin et al., 1990).

The weight percent (wt%) of asphaltene sludge that may form as a consequence of an acid job is given by:

wt % of asphaltene sludge = ([P.sub.T])*(STO wt%)+ (STO wt%) (11)

In this notation (STO wt%) is the weight percent of asphaltene deposited in the stock tank. Conditions for asphaltene sludge occurence are classified by the expert system as follows:

wt% of asphaltene sludge< 1wt% , minor sludge occurence.

1 wt %< wt% of asphaltene sludge< 2.5wt%, moderate sludge occurence.

wt% of asphaltene sludge >2.5wt%, severe sludge occurence.

Results and Discussion

Case studies have been constructed to validate the asphaltene sludge module. Table 4 and Figure 4 show summary of case studies results obtained by studying the effect of HCL concentration. As the HCL concentration increased from 5% to 28%, the sludge wt% increased from 5.7 wt% to 9.45 wt%. As shown in Figure 4, the threshold for severe sludge formation appears to take place at HCL concentration of approximately 15%. Figure 5 displays the solution window of case D in Table 4 with 28% HCL. HCL of 28% acid appears to cause serious problems for sludge. It was found that mixing HCL with HF acid caused more severe sludging than pure HCL of the same concentration up to 12.21 wt% of asphaltene sludge (compare Figures 6 ands 4). Lowering the HCL: HF strength below 12:3% would slightly reduce sludging (Table 5).

[FIGURE 4 OMITTED]

Table 6 shows that both ferrous and ferric ions exacerbate slightly sludging. However, an excess of ferric ions results in a higher degree of sludging. This potential problem must be addressed during pre-treatment planning. It has been found that the primary source of Fe III originates in the production tubing. Fe II is predominantly produced as a result of acid dissolution of iron rich minerals, such as siderite and chlorite clay, found in oil bearing reservoirs. The sensitivity of chlorite clay to HCl begins at a temperature of about 125 [degrees]F (Coulter and Jennings, 1999). Even though Fe II can be oxidized to be Fe III, most acid systems have relatively low oxygen solubility. Therefore, the focus should be preferentially placed on control of Fe III in tubulars.

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

Table 7 shows several cases that test the effect of iron control additives on wt% of sludge. Figure 7 shows the results of the five most commonly used iron control additives when tested with 15% HCL containing 10,000 ppm of FeIII. Sludge was reduced best by the Erythorbic extractant. The results in Figure 7 indicate that citric acid, EDTA, and NTA caused the maximum wt % of sludge.

[FIGURE 7 OMITTED]

Other cases have been used to test the effect of surfactant type on the wt% of sludge. Table 8 shows that for the three surfactant types used (Fluorosurfactant, non-emulsifier, wetting agent), the wt% of induced sludge is about the same.

Table 9 and Figure 8 show that the mutual solvent concentration of greater than 5% in acid system resulted in a significant increase in wt% of sludge. The most commonly used mutual solvent in acid systems is ethylene glycol mono butyl ether (EGMBE). The use of concentration of greater than 5% EGMBE in acid systems resulted in a significant increase in sludge. One plausible explanation is that for higher concentrations, EGMBE strips the maltene resins, depeptizing the asphaltene particle.

[FIGURE 8 OMITTED]

Table 10 documents data used to test the effect of corrosion inhibitor type on sludge aggregation. It is found that class III corrosion inhibitor resulted in slightly higher wt % of sludge (Table 10).

The acid-induced sludge module has been tested with stimulation data from the Endicott field which is located in the Beaufort Sea, close to the Prudhoe Bay Field in Alaska (His et al., 1991). As shown in Table 11, Endicott sludging was aggravated when mixing 12:3 mud acid with Endicott crude. This has been confirmed by performing API field lab testing procedures prior to pumping the acid treatment downhole.

[FIGURE 9 OMITTED]

[FIGURE 10 OMITTED]

The 0.46 wt% of asphaltic sludge predicted by our acid-induced sludge module (Figure 9) is in perfect agreement with the 0.5 wt% of asphaltic sludge observed in the field lab (His et al., 1991). Conformal to field observations, the module also predicts no sludge when Endicott crude is contacted by HCl acid free ferric ions even in the presence of 5000 ppm ferric ions (Figure 10, Table 11).

Conclusions

An expert system for estimating the potential of asphaltic sludging caused by acidizing has been developed in this study. The system was developed using a graphical user interface that provides a user-friendly means of interactive communication between the user and the expert system. The expert system can be used for automating the process of diagnosing preliminary formation damage caused by organic scale deposition.

A 15% HCL concentration is found to be the threshold for serious acid-induced sludge. Increasing the HCl strength beyond this concentration results in an increase in the amount of acid-induced sludge. Hydrofluoric acid exhacerbates sludging except at low concentrations less than 3%. Asphaltene sludging is promoted by the presence of ferrous and ferric ions. However, Ferric ions cause more sludging. The addition of iron control additives like citric acid, EDTA, and NTA is found to cause sludging. Erythorbic extractant causes less sludging than any of the iron control additives tested. The three surfactant types investigated (Fluoro-surfactant, Non-emulsifier, wetting agent) are found to have an identical effect on sludging. The use of a mutual solvent concentration greater than 5% is found to increase the sludging tendency.

Acknowledgments

The author wishes to thank Kuwait University for its financial support of project EP02/03.

References

[1] Coulter, G.R., and Jennings, A.R., 1999, "A contemporary Approach to matrix acidizing," SPE Production & Facilities, 14(2), pp.150-158.

[2] Houchin L.R., Dunlap D.D, Arnold B.D., and Domke K.M, 1990, "The Occurrence and Control of Acid-Induced Asphalting Sludge," paper SPE 19410 presented at the SPE Formation Damage Control Symposium held in Lafayette. Louisiana, February 22-23.

[3] Houchin L.R., Hudson L.M., 1986, "The Prediction, evaluation, and Treatment of Formation Damage Caused by Organic Deposition," paper SPE 14818 presented at the 7th SPE Symposium on Formation Damage Control of SPE, Lafayette. Louisiana, February 26-27.

[4] Hirschberg, A., 1984, "Influence of Temperature and Pressure on Asphaltene Flocculation," SPE Journal, 283.

[5] His, C.D., Strassner, J.E., and Blosser, W.R., 1991, "Acid Stimulation of Endicott Kekiktuk Formation, North Slope," paper SPE 22152, International Arctic Technology Conference, Anchorage, Alaska, May 29-31.

[6] Islam, M.R., 1995, Potential of Ultrasonic Generators for Use in Oil Wells and Heavy crude Oil/Bitumen transportation Facilities, Asphaltenes--Fundamentals and Applications, Sheu and Mullins eds., Plenum Press, New York, 191-218.

[7] Lababidi, H.M.S., Garrouch, A. A., and Fahim, M.A., 2004, "A fuzzy heuristic approach for predicting asphaltene precipitation potential," Energy and Fuels, 18(1), pp. 242-250.

[8] Wang J.X, Brower K.R and Buckly J.S., 1999, "Advances in Observation of Asphaltene Destabilization," paper SPE 50745 presented at the SPE International Symposium on Oilfield Chemistry held in Houston, Texas, February 16-19.

Ali A. Garrouch and Adel H. Malallah

Petroleum Engineering Department, Kuwait University, Kuwait
Table 1: Effect of standard dosage of iron control additive on sludge
percent reduction.

ICD Type P[gamma]

Citric acid 1
EDTA 2
NTA 2
Erythorbic acid 48
Fe Extractant 63
Erythorbic / Extractant 82

Table 2: Effect of standard dosage of surfactant type on sludge
percent increase.

Surfactant Type P[epsilon]

Fluoro-surfactant 10
Non-emulsifier 12
Wetting Agent 11

Table 3: Effect of standard dosage of corrosion inhibitor on sludge %
increase.

Corrosion Inhibitor Type P[lambda]

Class # I 2
Class # II --
Class # III 50

Table 4: Case studies data for investigating the effect of HCl
concentration on sludging.

 Case A Case B Case C Case D

HCL,% 5 10 15 28

HF,% 0 0 0 0

[I.sub.2], ppm 5000 5000 5000 5000

[I.sub.3], ppm 10000 10000 10000 10000

ICD Citric Citric Citric Citric
 acid acid acid acid

I, % 5% 5% 5% 5%
Surfactant Type Non Non Non Non
 emulsifier emulsifier emulsifier emulsifier

Type of corrosion Class I Class I Class I Class I
Inhibitor

STO, wt % 3 3 3 3

Wt % of sludge 5.7 5.73 5.91 9.45

Table 5: Case studies data used to investigate the effect of acid
concentrations and % HCL: % HF ratio on sludging.

 Case A Case B Case C Case D

HCL,% 5 7.5 12 15

HF,% 0.8 1.5 3 5

[I.sub.2], ppm 5000 5000 5000 5000

[I.sub.3], ppm 10000 10000 10000 10000

ICD Citric Citric Citric Citric
 acid acid acid acid

I, % 25% 25% 25% 25%

Surfactant Type Non Non Non Non
 emulsifier emulsifier emulsifier emulsifier

Type of corrosion Class I Class I Class I Class I
Inhibitor

STO, wt % 3 3 3 3

Wt % of sludge 11.07 11.28 11.85 12.21

Table 6: Case studies data used for investigating the effect of
ferrous and ferric ion concentration on sludging.

 Case A Case B Case C Case D

HCL,% 15 15 15 15

HF,% 0 0 0 0

[I.sub.2], ppm 250 250 1000 1000

[I.sub.3], ppm 250 1000 1000 5000

ICD Erythorbi Erythorbi Erythorbi Erythorbi
 c c c c
 acid acid acid acid
I, % 2% 2% 2% 2%

Surfactant Fluoro Fluoro Fluoro Fluoro
Type surfactan surfactan surfactan surfactan
 t t t t

Type of Class I Class I Class I Class I
corrosion
Inhibitor

STO, wt % 3% 3% 3% 3%

Wt % of 0 0 0 1.05
sludge

 Case E Case F Case
 G

HCL,% 15 15 15

HF,% 0 0 0

[I.sub.2], ppm 5000 5000 10000

[I.sub.3], ppm 5000 10000 10000

ICD Erythorbi Erythorbi Eryth
 c c orbic
 acid acid acid
I, % 2% 2% 2%

Surfactant Fluoro Fluoro Fluor
Type surfactan surfactan o
 t t surfac
 tant

Type of Class I Class I Class
corrosion I
Inhibitor

STO, wt % 3% 3% 3%

Wt % of 1.11 4.74 2.22
sludge

Table 7: Case studies data used for investigating the effect of iron
control additives on sludging

 Case A Case B Case C

HCL,% 15 15 15

HF,% 0 0 0

[I.sub.2], ppm 5000 5000 5000

[I.sub.3], ppm 10000 10000 10000

ICD Citric EDTA NTA
 acid

I, % 5% 5% 5%

Surfactant Wett. Wett. Wett.
Type Agent Agent Agent

Type of Class III Class III Class III
corrosion
Inhibitor

STO, wt % 1.5 1.5 1.5

Wt % of 3.66 3.645 3.645
sludge

 Case D Case E Case F

HCL,% 15 15 15

HF,% 0 0 0

[I.sub.2], ppm 5000 5000 5000

[I.sub.3], ppm 10000 10000 10000

ICD Erythorbic Fe Erythorbic
 acid Extractant Extractant

I, % 5% 5% 5%

Surfactant Wett. Wett. Wett.
Type Agent Agent Agent

Type of Class III Class III Class III
corrosion
Inhibitor

STO, wt % 1.5 1.5 1.5

Wt % of 2.955 2.73 2.445
sludge

Table 8: shows that for the three surfactant types used
(Fluorosurfactant, non-emulsifier, wetting agent)

 Case A Case B Case C

HCL,% 15 15 15

HF,% 0 0 0

[I.sub.2], ppm 5000 5000 5000

[I.sub.3], ppm 10000 10000 10000

ICD EDTA EDTA EDTA

I, % 8% 8% 8%

Surfactant Fluoro Non Wetting
Type Surfactant Emulsifier Agent

Type of Class III Class III Class III
corrosion
Inhibitor

STO, wt% 2 2 2

Wt % of 5.66 5.7 5.68
sludge

Table 9: Case studiesdata used to investigate the effect of mutual
solvent concentration on sludging.

 Case A Case B Case C

HCL,% 15 15 15

HF,% 0 0 0

I2, ppm 5000 5000 5000

I3, ppm 10000 10000 10000

ICD Citric Citric Citric
 Acid Acid Acid

I, % 3% 5% 8%

Surfactant Non Non Non
Type Emulsifier Emulsifier Emulsifier

Type of corrosion Class I Class I Class I
Inhibitor

STO, wt% 3 3 3

Wt % of sludge 5.88 5.91 7.14

 Case D Case E

HCL,% 15 15

HF,% 0 0

I2, ppm 5000 5000

I3, ppm 10000 10000

ICD Citric Citric
 Acid Acid

I, % 10% 15%

Surfactant Non Non
Type Emulsifier Emulsifier

Type of corrosion Class I Class I
Inhibitor

STO, wt% 3 3

Wt % of sludge 8.28 9.9

Table 10: Case studies data used to investigate the effect of
corrosion inhibitor on sludging.

 Case A Case C

HCL,% 15 15

HF,% 0 0

[I.sub.2], ppm 5000 5000

[I.sub.3], ppm 10000 10000

ICD Citric Acid Citric Acid

I, % 5% 5%

Surfactant Type Non Emulsifier Non Emulsifier

Type of corrosion Inhibitor Class I Class III

STO, wt% 3 3

Wt % of sludge 5.91 7.35

Table 11: Endicott-field validation data.

 Case A Case B

C: HCL% concentration by volume 15 12

HF % 0 3

[I.sub.2] in PPM 5000 5000

[I.sub.3] in PPM 0 5000

ICD: type of ion control additive Citric Acid Citric Acid

Surfactant type Non-emulsifier Non-emulsifier

I: mutual solvent concentration in % 20% 20%

Type of corrosion inhibitor Class# I Class# I

STO wt% 1 1

 wt% sludge 0 0.46
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Author:Garrouch, Ali A.; Malallah, Adel H.
Publication:International Journal of Petroleum Science and Technology
Article Type:Technical report
Geographic Code:7KUWA
Date:Jun 1, 2007
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