Determination of Asphaltene Deposition Profile in a .... Appl. Environ. Biol. Sci., 7... ·...

J. Appl. Environ. Biol. Sci., 7(4)156-164, 2017

© 2017, TextRoad Publication

ISSN: 2090-4274 Journal of Applied Environmental

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*Corresponding Author: Tavakoldavani, M., Islamic Azad University, Omidiyeh branch, Department of Petroleum, Omidiyeh, Iran. Email: [email protected]

Determination of Asphaltene Deposition Profile in a Wellboresۥ Column of One Iranian Oil Reservoir

Tavakoldavani, M.¹* and Ashoori, S.²

¹Islamic Azad University, Omidiyeh branch, Department of Petroleum, Omidiyeh, Iran ²Petroleum University of Technology, Department of Petroleum Engineering, Ahwaz, Iran

Received: October 23, 2016

Accepted: February 18, 2017

ABSTRACT

Asphaltene deposition in oil production path from reservoir until surface facilities is an old problem. In this paper, we survey this problem specifically in wellbore’s column. The purpose of this study is to determine asphaltene deposition profile in wellboresۥ column. We used recombined sample and performed gravimetric experiments to measure asphaltene precipitation at different pressure (P) and temperature (T). P and T changes are corresponded to the variation in wellbore. We then used thermodynamic models for flash calculations and asphaltene precipitation of the oil samples. Then, we used the validated model to determine asphaltene deposition profile in a candid wellbore. And finally, we verified our model with good match with our experimental data. KEYWORDS: recombine, gravimetric experiments, thermodynamic models, flash calculation, candid wellbore

II- INTRODUCTION

Asphaltenes are heavy components of crude oil that are normally soluble in oil (like cholesterol, which is normally dissolved in the blood). During the production process and transport of oil because of changes in thermodynamic conditions (temperature, pressure and oil composition), these components precipitate as a solid phase from the solution. Asphaltene deposition in reservoir, wellboresۥ column, wellhead facilities and oil pipelines cause undesirable and costly operating complexities. Examples of these complexities are permeability impairments, hindered and blockage flow path in wellbore and wellhead and surface lines. The most likely location for the deposition is in wellboresۥ column, because of drastic changes in pressure, temperature and composition of the flowing oil. We found two works related to this study, one of them was one approach based on the combination of thermodynamic modeling of asphaltene precipitation with hydrodynamic well modeling. The developed model is capable to determine the asphaltene precipitation and deposition interval through the wellstring. Therefore, it could study the effect of hydrodynamic parameters such as wellhead pressure, well flow-rate and tubing size on the mitigation of asphaltene deposition. They developed the scale equation for asphaltene thermodynamic modeling in different pressure and temperature conditions. And they used Beggs & Brill correlation for hydrodynamic well modeling. The asphaltene precipitation well modeling was carried out with Matlab programming software. The results of the model in prediction of asphaltene precipitation depth was compared with the measured filed data of asphaltene deposition in various wells in same field and good agreement was observed. Results of modeling show that by reducing wellhead pressure and oil flow rate and increasing the tubing size the asphaltene precipitation decreases [1]. Another study is about asphaltene precipitation in high Gas-Oil Ratio (GOR). The high GOR is a consequence of gas coning/cresting in the wells. The free gas strips the asphaltenes from the crude that deposits in the wellbore. When gas is added to the crude, the composition of the crude changes and may lead to precipitation. A commercial PVT simulator (PVTsim by Calsep) was also used to simulate the asphaltene phase behavior and it was partially successful in providing precipitation trends. It can be a useful tool to estimate precipitation envelopes and trends. However, it needs to be tuned with some experimental data. Asphaltene precipitation onset starts at relatively low GOR (~625 scf/bbl). One Another factor that has kept the deposition under control is the high flow rates in these wells that prevent the asphaltene flocculation process and “carry” the asphaltenes to downstream processing facilities. The results of this study clearly indicate that asphaltene precipitation is a function of gas injection and increases with increasing GOR[2]. There are two major methods to remedy asphaltene problem; chemical and mechanical treatment which are expensive methods However, prevention is always better than treatment. We propose a methodology in this paper to prevent asphaltene precipitation in wellbore. Important questions in this regard are “when”, “where”, and “how much” asphaltene precipitate in the wellbore [3]. In this study, according to changes in thermodynamic conditions we can survey probability of asphaltene deposition in wellbore’s column. The difference between the proposed approach and old methods. In first study in second paragraph researchers study

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Tavakoldavani and Ashoori, 2017

the effect of hydrodynamic parameters such as wellhead pressure, well flow-rate and tubing size on the mitigation of asphaltene deposition. And they used the scale equation for asphaltene thermodynamic modeling in different pressure and temperature conditions. . Another study is about asphaltene precipitation in high GOR And they used PVTsim by Calsep for to simulate the asphaltene phase behavior. The scientific contribution of this paper are: 1) Masoud Tavakoldavani 2) Dr. Siavash Ashoori 3) Mohammad Baghal shooshtari. The remainder of the paper was organized as follows: Section I is Abstract, this section cover the problem, the goal of the paper, the proposed method and the results. Section II is Introduction, this section is brief explain about this study. Section III is Material and methods, this section is about methods, correlations and models that use for survey of this study. Section IV is Results and Discussion, this section covers the obtain results from software and correlations. Section V is Conclusion, this section shows four conclusions obtained from this study. Section VI is Recommendations, in this section the authors present two recommends. Finally in section VII References are present.

III- MATERIAL AND METHODS

Thermodynamic model of asphaltene deposition in wellbore Asphaltene deposition in wellbore is controlled by P, T, and fluid composition. We first devise a thermodynamic model to predict fluid composition with P and T corresponding to wellbore depth. We first perform Flash calculations using Peng-Robinson EOS (Winprop software). Then we use the Thermodynamic model of Hirschberg et al. (1984) to predict asphaltene precipitation (correlation 1) [4]. We used this because this model is simple and useful for determination of asphalten deposition.

−−−=φ 2

laa

l

aa )δ(δ

RT

V1

V

Vexp

(1)

Where φₐ is volume fraction of solution asphaltene, Vₐ and Vɩ are asphaltene and solvent molar volume respectively, R is the gas constant and T is the absolute temperature.

And δₐ and δɩ are asphaltene and solvent solubility parameter respectively. We can see conversion of volume fraction of asphaltene to weight fraction in correlation 2: Φₐ = wₐ ρₒ/ρ (2) Solubility parameter of the solvent We use Hildebrand et al. (1984) -correlation 3- in this research to obtain solubility parameter [5].

(3)

2/1

−∆V

RTH V

= ɩδ

Where ∆Hᵛ is a liquid heat of vaporization.

It is noteworthy the effects of temperature and pressure on solubility parameter. Solubility parameter decreases with decreasing pressure until reaches to the bubble point pressure. This reduction resulted from a reduction in oil density. For pressures lower than bubble point pressure, solution gas in oil is released and the remaining liquid contains heavier compounds, which cause an increase in solubility parameter of the liquid mixture. In liquids, temperature variation affects internal energy of vaporization and density. Solubility parameter increases with reduction in temperature

Genetic algorithm to calculate asphaltene molar volume and solubility parameter In the computer science field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics, physics, pharmacometrics and other fields. Wang et al. (2001) proposed a correlation (correlation 4) to calculate asphaltene solubility parameter [7] :

157


5.0])[0214428.004.20( MpaCTa −=δ (4)

We used a genetic algorithm to obtain the constants in Wang et al. (2001) correleation for our reservoir of interest. Used a modified correlation for our study (correlation 5).

5.0])[( mpaCTnma +=δ (5)

Using the Genetic Algorithm for optimizing the precipitation model parameters, the following results are obtained: m and n are obtained to be 24.00 and -0.009165 respectively. So the solubility parameter of the asphaltene at each temperature can be calculated with correlation 6: �ₐ = 24.00 − 0.009165 � (6)

The molar volume of asphaltene, ��, is fit to 0.00060771 ��

��. It is assumed that the molar volume of

asphaltene in the liquid phase and solid phase are the same. That is:

�� = ��

�

IV- RESULTS AND DISCUSSION

Sample preparation The reservoir of interest is Layer 2 in Fahliyan formation with reported asphaltene problems. The initial reservoir pressure and temperature conditions as well as bubble point and GOR are presented in Table 1.

Table 1: Initial reservoir conditions and fluid properties in Layer 2 of Fahlyian formation

Initial Static Pressure 9170 psia

Reservoir Temperature 289.4 ̊ F

Bubble Point Pressure 4283 psia

Solution Gas Oil Ratio 1610 SCF/STB

Rather taking bottom hole fluid samples we used oil and gas samples from the surface separators to recombined oil sample for our tests. Fluid samples were taken from the first stage separator at 1000 psia and 81°C. 15 liters of oil and 40 liters of gas from this separator were taking at constant pressure of 1000 psia and transfer to the laboratory for experimental tests. Thermodynamic and fluid properties of the sample fluids ad recombined samples are presented in Table 2. And compositional analysis of the recombined oil is presented in Table 3. Now with the above correlations, asphaltene content and asphaltene precipitation can be obtained at various depths in wellbore column. These calculations was presented in Table 4. (Note, total asphaltene precipitation weight fraction is obtained 0.0115 in the laboratory). Table 2: Thermodynamic and fluid properties of the sample fluids ad recombined samples Separator gas

1000 psia Separator oil

1000 psia Recombined oil

10000 psia z-factor 0.7633

Rs (Scf/STB) 416.75 1600

Z-factor: compressibility factor Rs: solution gas oil ratio

Table 3: Compositional analysis of the recombined oil Mole Percent Component

0.65 S2H 0.11 2N 2.30 2CO

53.13 1C

6.58 2C 3.90 3C 0.66 4C-i 1.59 4C-n 0.73 5C-i 1.06 5C-n 2.94 6C

3.30 7C 2.85 8C 2.02 9C 2.52 10C 1.97 11C

13.36 12+C 100 Total

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Table 4: Determination of Asphaltene deposition in various depth of wellbore’s column Depth (m)

P (psi) T ( K ) V�(m³/mol) δ� (Mpa)½ δa(Mpa)½ φa Calculated asphaltene precipitation (wt.%)

oil density(lb/ft³)

7.6 2877.6 356.55 0.00012879 16.560667 23.2356 0.0044477 0.296905 39.057261

300 3110.2 361.15 0.000127258 16.295287 23.1935 0.0028636 0.593042 38.51714

600 3353.6 366.35 0.000125626 16.017278 23.1458 0.0018337 0.788 37.9475

900 3598.7 371.35 0.000123874 15.727802 23.1 0.0012133 0.90663 37.3469

1200 3848.6 377.25 0.000121946 15.42872 23.0459 0.0007022 1.00673 36.71742

1500 4100.7 385.25 0.00011993 15.122587 22.9726 0.00048825 1.04861 36.0735

1800 4356.4 391.25 0.000117722 14.798778 22.9176 0.00028808 1.089 35.37858

2100 4614.4 397.05 0.000115912 14.5202 22.8644 0.00018879 1.10935 34.79018

2400 4873.9 401.75 0.000114896 14.322077 22.8214 0.0001473 1.117935 34.41482

2700 5132.7 406.75 0.000114502 14.2489 22.7756 0.0001572 1.11565 34.28634

3000 5395.8 410.55 0.00011452 14.218191 22.7407 0.0001795 1.110766 34.2813

3300 5658.6 414.45 0.000114388 14.20939 22.705 0.0002212 1.101721 34.31964

3600 5921.6 417.95 0.000113345 14.209207 22.6729 0.0002838 1.088145 34.37584

3700 6012.6 418.75 0.000112487 14.21488 22.6656 0.0003149 1.0814365 34.40648

3800 6103.1 420.45 0.000112925 14.22056 22.65 0.0003566 1.072423 34.43712

3900 6193.4 420.35 0.000113362 14.22624 22.6509 0.00034188 1.0757 34.46776

4000 6258 421.05 0.0001138 14.23192 22.6445 0.0003541 1.073101 34.4984

4100 6376.7 421.55 0.000113657 14.24423 22.6399 0.00038002 1.06758 34.5416

4200 6467.2 422.05 0.000113486 14.26092 22.6353 0.00041348 1.06046 34.59333

P: pressure T: temperature K: Kelvin (unit of temperature) Vɩ: solvent molar volume

δɩ: solvent solubility parameter

δa: asphaltene solubility parameter φa : volume fraction of solution asphaltene wt.%: weight percent

Figure 1: Amount of asphaltene deposition in various depths of wellbore’s column

0

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0.8

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1.2

0 600 1200 1800 2400 3000 3600 4200

Asp

ha

lte

ne

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ita

tio

n (

wt.

%)

Depth (psia)

Calculated asphaltene precipitation (wt.%)

159


Figure 2: Amount of asphaltene deposition in various pressure of wellbore’s column

Figure 3: Amount of asphaltene deposition in various temperature of wellbore’s column

Figure 4: Amount of asphaltene content in various pressure of wellbore’s column

0

0.2

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0.8

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1.2

2800 3800 4800 5800 6800

Asp

ha

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%)

Pressure (psia)


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1.2

350 360 370 380 390 400 410 420Asp

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%)

Temprature (K)


0

0.001

0.002

0.003

0.004

0.005

2800 3300 3800 4300 4800 5300 5800 6300 6800

Asp

ha

lte

ne

co

nte

nt

Pressure (psia)

Asphaltene content

160


Note, asphaltene solubility parameter ,δₐ, in wellbore’s column condition is obtained in the range of 22.6353 to 23.2356 (Mpa)½ which these values are consistent with the values that Verdier was obtained in 2006. He was determined Asphaltene solubility parameter values in the range of 20 to 23 (Mpa)½ [6].

Measuring Accuracy of thermodynamic model selected Here we want to measure the accuracy of thermodynamic model by which we measured the amount of asphaltene at different depths. For this, we compare the amount of asphaltene which was obtained in a specific pressure and temperature during the experiments in vitro, with the value calculated with Hirschberg thermodynamic model in same temperature and pressure. Thus, again, base on initial characteristics of the fluid which we had and testing conditions in the laboratory with constant temperature and variable pressure, we do flash calculations by Winprop software to obtain fluid composition in this condition, and with this information we can calculate the amount of asphaltene deposition, using the model.

Asphaltene values obtained in the laboratory at different temperatures and pressures The most important thermodynamic parameters which has effect on asphaltene deposition in primary depletion condition from oil reservoirs, is the pressure of reservoirs. Effect of Pressure on amount of asphaltene deposition at three temperatures 143, 120 and 90 ° C were studied. Amount of asphaltene deposition in the oil increases with reduction pressure than the initial reservoir pressure. The increasing trend would continue to the saturation pressure of reservoir (bubble point pressure) due to a decrease in density of the oil of reservoir. With keeping the reduction pressure below the saturation pressure of oil, amount of asphaltene deposition decreases. In other words, the most amount of asphaltene deposition in oil is in oil saturation pressure. This result was achieved in all three temperatures. Also, amount of asphaltene deposition in live oil increased with temperature reduction. Table 5: Asphaltene amounts obtained in the laboratory at constant temperature and various pressures at 90 ° C.

P (psia)

V� (m³/mol)

δ� (Mpa)

δa (Mpa)½ Φa

Φ΄a


Experimental asphaltene precipitation (wt.%)

7722 0.000103 15.94 23.17515 0.00351676 0.01139718 0.010282 0

6500 0.000105 15.9547 23.17515 0.00330095 0.01089466 0.060534 0.04

5500 0.000107 15.9757 23.17515 0.00316446 0.0106339 0.08661 0.06

4500 0.000113 16.0745 23.17515 0.00315494 0.01060274 0.089726 0.1

4000 0.000119 16.1934 23.17515 0.00327335 0.01078356 0.071644 0.07

3500 0.000127 16.3124 23.17515 0.00341981 0.01105504 0.044496 0.05

3000 0.000134 16.4344 23.17515 0.00360835 0.011451862 0.048138 0.04

2125 0.000151 16.6289 23.17515 0.00374318 0.0115 0 0

P: pressure Vɩ: solvent molar volume δɩ: solvent solubility parameter δa: asphaltene solubility parameter Φa: volume fraction of solution asphaltene Φ΄a: weight fraction of solution asphaltene wt.%: weight percent

Table 6: Asphaltene amounts obtained in the laboratory at constant temperature and various pressures at 120 ° C.

P (psia) V�(m³/mol) δ� (Mpa)½

δa (Mpa)½

Φa

Φ΄a

Calculated asphaltene precipitation (wt%)

Experimental asphaltene precipitation (wt%)

7630 0.000107 15.42133 22.9002 0.003316 0.01111711 0.00038289 0

7000 0.000108 15.43227 22.9002 0.003209 0.01087908 0.00062092 0.0003

6000 0.00011 15.45727 22.9002 0.003068 0.01061618 0.00088382 0.0007

4800 0.000116 15.54656 22.9002 0.002977 0.104873 0.0010127 0.0012

4000 0.000126 15.72305 22.9002 0.003139 0.01068595 0.00081405 0.0008

3000 0.000143 15.97345 22.9002 0.003466 0.01129616 0.00020384 0.0004

2182 0.000159 16.16483 22.9002 0.003648 0.0115 0 0


161


Table 7: Asphaltene amounts obtained in the laboratory at constant temperature and various pressures at 143 ° C. P (psia)

V�(m³/mol) δ� (Mpa)½ δa (Mpa)½ Φa

Φ΄a



7533 0.00010989 15.03434221 22.68787445 0.003170615 0.01093621 0.00056379 0

7000 0.00011112 15.04704984 22.68787445 0.003085869 0.01076304 0.00073696 0.0004

6000 0.00011381 15.07871031 22.68787445 0.002951568 0.01054383 0.00095617 0.0009

4800 0.00011893 15.15033319 22.68787445 0.002837496 0.0104266 0.0010734 0.0017

4000 0.00013151 15.36188026 22.68787445 0.003022737 0.01060175 0.00089825 0.001

3000 0.0001493 15.61879109 22.68787445 0.003336172 0.01114117 0.00035883 0.0005

2316 0.00016356 15.78900327 22.68787445 0.003551446 0.0115 0 0


Figure 5: Comparison of calculated asphaltene precipitation with experimental asphaltene precipitation at 90 ° C.


0

0.02

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0.06

0.08

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0.12

1000 2000 3000 4000 5000 6000 7000 8000 9000Asp

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%)

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T=90 ̊C



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T=120 ̊CCalculated asphaltene precipitation (wt%)

Experimental asphaltene precipitation (wt%)

162



V- Conclusion: 1 - Acceptable compliance of experimental data and the data from model. 2 - Decrease in temperature increases the solubility parameter and as a result, higher deposition amounts to remains dissolved in the oil. 3 – Solubility parameter decreases with decrease in pressure to reach bubble point pressure, and it increases with further reduction of pressure below the bubble point. 4 - Asphaltene solubility parameter ,δₐ, in well’s column was found in the range of 22.6353 to 23.2356 (Mpa)½ which this value is consistent with the values that Verdier obtained. VI- Recommendations: 1 - Changes in amount of asphaltene deposition with changes in the velocity term in wellboresۥ column is studied. 2 - The results of this study with other thermodynamic models should be studied. Acknowledgements This paper was taken from M.Sc. Thesis of Masoud Tavakol Davani, with title “Determination of Asphaltene Deposition Profile in a Wellbore’s Column of One Iranian Oil Reservoir”. Here authors acknowledged the Islamic Azad University, Omidiyeh branch, Department of Petroleum, Omidiyeh, Iran for its total supports.

Nomenclature φₐ Volume fraction of Asphaltene content δₐ Asphaltene solubility parameter δɩ Liquid solubility parameter Vɩ Liquid molar volume Vₐ Asphaltene molar volume

Heat of vaporization ᵛH∆

VII – REFERENCES

1. Soltani Soulgani. B., Rashtchian, D., Tohidi, B., and Jamialahmadi, M., 2010. A Novel Method for Mitigation

of Asphaltene Deposition in the Wellstring, Iran. J. Chem. Chem. Eng., Vol. 29, No.2.

2. Kokal, S., Al-Ghamdi, A., and Krinis , D., Spring 2005. Asphaltene Precipitation in High Gas-Oil Ratio

Wells, Saudi Aramco Journal of Technology.

3. Ashoori, S., 2005. Mechanism of asphaltene deposition in porous media, Ph.D. thesis, Department of

Chemical and Process Engineering, University of Surrey, Guildford, UK.

0

0.0005

0.001

0.0015

0.002

1000 2000 3000 4000 5000 6000 7000 8000

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T=143 ̊CCalculated asphaltene precipitation (wt.%)


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4. Hirschberg, A., Dejong, L.N.J., Schipper, B.A., and Meijer, J.G, June 1984. Influence of Temperature and

Pressure on Asphaltene Flocculation. SPE J., pp: 283-293.

5. Hildebrand, J.H., Scott, R.L., 1950. The Solubility of Non-electrolytes, Reinhold Publishing, New York.

6. Verdier, S., 2006. Experimental Study and modelling of Asphaltene Precipitation Caused by Gas Injection,

PhD Thesis, Technical University of Denmark, Lyngby, Denmark.

7. J.X. Wang and J.S. Buckley., 13-16 Feb 2001. An Experimental Approach to prediction of Asphaltene

Flocculation. SPE paper, No. 64994, International Oilfield Chemistry Symposium, Houston.

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