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

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1 J. Appl. Environ. Biol. Sci., 7(4) , , TextRoad Publication ISSN: Journal of Applied Environmental and Biological Sciences Determination of Asphaltene Deposition Profile in a Wellboreۥs 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 ABSTRACT Received: October 23, 216 Accepted: February 18, 217 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 wellboreۥs 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, wellboreۥs 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 wellboreۥs 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 *Corresponding Author: Tavakoldavani, M., Islamic Azad University, Omidiyeh branch, Department of Petroleum, Omidiyeh, Iran. masoud.davani@gmail.com 156

2 Tavakoldavani and Ashoori, 217 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. Va Va φa = exp 1 (δa δl) Vl RT 2 (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]. δɩ= H V RT V 1/ 2 (3) 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. (21) proposed a correlation (correlation 4) to calculate asphaltene solubility parameter [7] : 157

3 J. Appl. Environ. Biol. Sci., 7(4) , 217 a = ( T[ C]) Mpa.5 δ (4) We used a genetic algorithm to obtain the constants in Wang et al. (21) correleation for our reservoir of interest. Used a modified correlation for our study (correlation 5). δ = ( m nt[ C]) mpa.5 (5) a + Using the Genetic Algorithm for optimizing the precipitation model parameters, the following results are obtained: m and n are obtained to be 24. and respectively. So the solubility parameter of the asphaltene at each temperature can be calculated with correlation 6: ₐ= (6) The molar volume of asphaltene,, is fit to.6771 asphaltene in the liquid phase and solid phase are the same. That is: = IV- RESULTS AND DISCUSSION. It is assumed that the molar volume of 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 917 psia Reservoir Temperature F Bubble Point Pressure 4283 psia Solution Gas Oil Ratio 161 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 1 psia and 81 C. 15 liters of oil and 4 liters of gas from this separator were taking at constant pressure of 1 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.115 in the laboratory). Table 2: Thermodynamic and fluid properties of the sample fluids ad recombined samples Separator gas 1 psia Separator oil 1 psia Recombined oil 1 psia z-factor.7633 Rs (Scf/STB) Z-factor: compressibility factor Rs: solution gas oil ratio Table 3: Compositional analysis of the recombined oil Component Mole Percent H 2S.65 N 2.11 CO C C C i-c 4.66 n-c i-c 5.73 n-c C C C C C C C Total 1 158

4 Tavakoldavani and Ashoori, 217 Depth (m) Table 4: Determination of Asphaltene deposition in various depth of wellbore s column P (psi) T ( K ) V (m³/mol) δ (Mpa)½ δa(mpa)½ φa Calculated asphaltene oil density(lb/ft³) 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 Calculated asphaltene Depth (psia) Figure 1: Amount of asphaltene deposition in various depths of wellbore s column 159

5 J. Appl. Environ. Biol. Sci., 7(4) , 217 Calculated asphaltene Figure 2: Amount of asphaltene deposition in various pressure of wellbore s column Calculated asphaltene Temprature (K) Figure 3: Amount of asphaltene deposition in various temperature of wellbore s column.5 Asphaltene content Asphaltene content Figure 4: Amount of asphaltene content in various pressure of wellbore s column 16

6 Tavakoldavani and Ashoori, 217 Note, asphaltene solubility parameter,δₐ, in wellbore s column condition is obtained in the range of to (Mpa)½ which these values are consistent with the values that Verdier was obtained in 26. He was determined Asphaltene solubility parameter values in the range of 2 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, 12 and 9 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 9 C. V δ δa (Mpa)½ Φa Φ a Calculated asphaltene (m³/mol) (Mpa) P (psia) Experimental asphaltene 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 12 C. P (psia) V (m³/mol) δ (Mpa)½ δa (Mpa)½ Φa Φ a Calculated asphaltene precipitation (wt%) Experimental asphaltene precipitation (wt%) 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 161

7 J. Appl. Environ. Biol. Sci., 7(4) , 217 P (psia) Table 7: Asphaltene amounts obtained in the laboratory at constant temperature and various pressures at 143 C. V (m³/mol) δ (Mpa)½ δa (Mpa)½ Φa Φ a Calculated asphaltene 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 T=9 C Calculated asphaltene Experimental asphaltene Experimental asphaltene Figure 5: Comparison of calculated asphaltene precipitation with experimental asphaltene precipitation at 9 C. T=12 C Calculated asphaltene precipitation (wt%).14 Experimental asphaltene precipitation (wt%) Figure 6: Comparison of calculated asphaltene precipitation with experimental asphaltene precipitation at 12 C. 162

8 Tavakoldavani and Ashoori, 217 Figure 7: Comparison of calculated asphaltene precipitation with experimental asphaltene precipitation at 143 C. V- Conclusion: 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 to (Mpa)½ which this value is consistent with the values that Verdier obtained. VI- Recommendations: T=143 C Calculated asphaltene Experimental asphaltene Changes in amount of asphaltene deposition with changes in the velocity term in wellboreۥs 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 Hᵛ Heat of vaporization VII REFERENCES 1. Soltani Soulgani. B., Rashtchian, D., Tohidi, B., and Jamialahmadi, M., 21. A Novel Method for Mitigation of Asphaltene Deposition in the Wellstring, Iran. J. Chem. Chem. Eng., Vol. 29, No Kokal, S., Al-Ghamdi, A., and Krinis, D., Spring 25. Asphaltene Precipitation in High Gas-Oil Ratio Wells, Saudi Aramco Journal of Technology. 3. Ashoori, S., 25. Mechanism of asphaltene deposition in porous media, Ph.D. thesis, Department of Chemical and Process Engineering, University of Surrey, Guildford, UK. 163

9 J. Appl. Environ. Biol. Sci., 7(4) , Hirschberg, A., Dejong, L.N.J., Schipper, B.A., and Meijer, J.G, June Influence of Temperature and Pressure on Asphaltene Flocculation. SPE J., pp: Hildebrand, J.H., Scott, R.L., 195. The Solubility of Non-electrolytes, Reinhold Publishing, New York. 6. Verdier, S., 26. 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., Feb 21. An Experimental Approach to prediction of Asphaltene Flocculation. SPE paper, No , International Oilfield Chemistry Symposium, Houston. 164