Experimental Investigation and Application of the Asphaltene

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Experimental Investigation and Application of Asphaltene Precipitaion Envelope Hao Lei, Shenglai Yang, Kun Qian, Yanzhao Chen, Ying Li, and Quanzhen Ma Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.5b01237 • Publication Date (Web): 09 Oct 2015 Downloaded from http://pubs.acs.org on October 9, 2015

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Experimental Investigation and Application of Asphaltene Precipitaion Envelope Hao Lei,*’† Shenglai Yang;† Kun Qian,‡ Yanzhao Chen,† Ying Li,† Quanzhen Ma† † Key Laboratory of Petroleum Engineering of the Ministry of Education, China University of Petroleum, Beijing 102249, People’s Republic of China ‡ Xinjiang Oilfield Company, China National Petroleum Corporation (CNPC), Karamay 834000, People’s Republic of China ABSTRACT. In the production process, the asphaltene precipitation (AP) and deposition can not only inflict damage on reservoir stratum but also lead to the shut-in of well and incur the extra cost of remediation. In this study, the phase behavior of asphaltenes in live oil under high-temperature and high-pressure conditions were determined by using a modified solid (asphaltene) deposition laser detection apparatus. The test accuracy was greatly improved due to the increase of the laser power. The phase behavior of asphaltenes in live oil which characterized by the heavy components and dark color was evaluated. The oil sample was from Fahliyan oilfield in Iran, which is suffering big AP problem. In addition, the values of the bubble point pressure (BPP) obtained by this apparatus have proven to be well matched with that measured by constant composition experiment (CCE) test. Moreover, the equation of state (EOS) of the asphaltene and crude oil obtained by the fitting curve can be used to further optimize the mathematical prediction model. Furthermore, the phase diagram is completed in conjunction with the P-T curve to predict the deposition location of asphaltene in the well. For the example well, the predicted results at the depth of 1930 m are almost comparable to the results of the actual production process at the depth of 1845 m, which only has a difference of 2.1%. Accordingly, the addition of chemical inhibitors is recommended as an effective method to reduce the risk of AP in the example well.

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Asphaltene is the complex compound in the crude oil with strong polarity, large molecular weight and high aromatic-carbon rate,1-10 which generally defined as soluble in aromatic hydrocarbons such as benzene, toluene, and pyridine but insoluble in saturated hydrocarbons with low molecular weight usually as n-heptane or n-pentane.3,6,11 In order to establish the consistent and clear terminology, several terms (e.g., “deposition” and “precipitation”) which will be used in this paper are defined.12,13 Firstly, “precipitation” refers to the whole process of asphaltenes converting from stable conditions to the aggregation or precipitation of asphaltene in micron level. Secondly, “deposition” will be used to describe the suspended precipitated asphaltene detached from the crude oil and deposited in the solid-surface (e.g., the porous media).

The work of Buckly reported that the variations in pressure, temperature, and mixture composition, no matter where and when that happens during the process of development and production, will result in the change of asphaltenes solubility, and isolate the AP from crude oil.14 Simultaneously, most of the laboratory experiments and field results investigated that the effect of the pressure, temperature, and oil composition on AP are all important factors.12,15,16 Zendehoudi, S. et al found that the contribution of the temperature, pressure, and oil composition to the AP amount accounts for 37%, 36%, and 27%, respectively.18 In addition, for the actual oilfield, the operating pressure has significant impacts on the AP phenomenon during the process of primary oil recovery.15 In the process of gas injection, both temperature and oil composition (including the gas and asphaltene content) plays important role on the AP.

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In addition, the AP can not only block the pore structure and throat as well as reduce the effective permeability,16 but also clog the production well and reduce the oil throughput. Moreover, it will unavoidably increase the enormous cost related to asphaltene removal.18

Under the consideration of the problems mentioned above, the deposition conditions of asphaltene must be determined in the reservoir development and oil production processes. In order to reduce the adverse affect of the AP on oil production, these conditions can be used to optimize the design stage of reservoir recovery processes.17 Numerous researchers have launched extensive studies on the deposition conditions of asphaltene, including electrical conductivity, thermodynamic mathematical model, and optical microscopy, etc.19

There are a lot of methods to determine the onset conditions of AP. However, only two methods are widely used to predict the AP onset conditions under reservoir conditions.17,18,20,21 The first one is experimental method, as Mousavi-Dehghani, et al summarized.22 The methods involves the titration of the stock tank oil (STO) with an flocculant (e.g., alkane) and then determines the precipitation point by using the methods such as interfacial tension (IFT), viscosity, electrical conductivity, spectroscopy, and gravimetry.22,23 These are very easy and quick methods to investigate the properties and the depositional mechanism of AP due to the changes of composition. However, the accuracy is a very serious problem to predict the asphlatene precipitation under the reservoir conditions.23

The second method is to use the thermodynamic models, such as solubility model, solid model, colloidal model, and EOS model, to predict AP under reservoir conditions.17,18,23 Through the experimental results, however, most of these models have been improved to 3


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predict the deposition conditions of AP. For the process of CO2 injection or not, Zendehboudi et al reported that the AP and deposition conditions were determined by imperialist competitive algorithm-artificial neural network (ICA-ANN) model under the broad changes in thermodynamics, which has very high reliability and accuracy.24 Also, this model has been improved and verified through the phase properties of asphaltene [e.g., asphaltene precipitation onset pressure (AOP)] and the properties of crude oil under static conditions. In addition, there are some other thermodynamic models which can simulate the AP and its factors in the production operation.25-27 However, it should be noted that the basic parameters and the phase properties of those models were mostly determined by the experiment.

The phase diagram of AP is a quick and intuitive approach to obtain the phase behavior of asphaltene, which is also an essential design factor in implementation of any field development process. It can not only obtain the asphaltene phase behavior at any temperature and pressure but also determine the basic parameters of mathematical model.28

So far, the solids detection system (SDS) is still regarded as the main method to investigate the phase properties of AP.1 In this study, a solid (asphaltene) deposition laser detection system is proposed to investigate the phase behavior of saturated fluid under realistic reservoir conditions of pressure and temperature. Similar to the previous SDS,1,29-33 the phase transition of asphaltene in this paper can be indicated by the changes of attenuation of the laser beam through the crude oil. However, this apparatus has a high reliability and accuracy to determine the phase behavior of the darker and heavier crude oil by increasing the laser power that was enhanced nearly 1000 times in comparison with previous SDS.1,16 The

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crude oil sample used in this study is from an Iran oilfield, which has a serious AP problem. The isothermal pressure depletion experiments were conducted at temperatures from wellhead conditions to the reservoir conditions (44 oC, 60 oC, 80 oC, 100 oC, and 123 oC) for live oil. The experiment was performed to determine the phase behavior of crude oil and asphaltene, such as the asphaltene onset point, the re-dissolution point, and the bubble-point. In addition, to prove the reliability and accuracy of the laser detection system, the measured values and its application results were compared to results from CCE tests and the actual reservoir results, respectively. 2.1 Materials. The representative crude oil sample used in this investigation was collected from Fahliya reservoir of South Azadegan oilfield in Iran, which has 1.4% n-heptane asphaltenes. The production well WI-11 has been closed due to a serious AP problem. The reservoir pressure and temperature are 62.4 MPa and 123.6 oC, respectively. 2.2 Gas Chromatography and SARA Analysis. The liquid components of the sample were analyzed by high temperature gas chromatography (HTGC) apparatus.34 A high temperature gas chromatography (Agilent, model 7890, and the operating temperature is from 40 oC to 350 oC) was used to analyze the fraction from C1 to C36+ of the degassed crude with hydrogen flame ionization detectors (FID) and full-automatic sampler (model 7683B). On the basis of total mass of each fraction and gas-oil ratio (GOR), the composition of the formation crude was calculated by means of mass conservation. Compositions of the crude oil (e.g., STO) samples are shown in Table 1. The SARA (including saturates, aromatics, colloid and asphaltene) of the STO were analyzed using high performance liquid chromatography (HPLC) (Agilent, model 1200, and the operating temperature is from 4 oC to 40 oC). Meanwhile the content of asphaltene was 5


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determined by using the standard ASTM D3279-97 method. The results are provided in Table 2. 2.3 Instrumentation. An experimental apparatus has been used in this investigation, which was a solid (asphaltene) deposition laser detection system designed by staffs in CUPB (China University of Petroleum, BEIJING). The schematic of this experimental apparatus is shown in Figure 1. This apparatus is made up of three parts. The first part is RUSKA-PVT measurement, which mainly consists of a visual variable FC kettle and a visual variable FPC kettle. This apparatus can be operated within the temperature range of 20-150 oC and at a maximum pressure of 70 MPa. The PVT part was used in this work to recombine oil under the reservoir conditions. The second part is an adjustable laser-transmitting and receiving device, which has the tunable laser with the maximum power of 700 mw. The laser wavelength is 1550 nm and the optical fiber output is SMA905. The receiving part is connected to the full-wave optical power meter, and the optical signals are recorded and converted by a data acquisition and analyzer system. This device was a solid detection system utilized to measure the asphaltene precipitation envelope (APE) as well as the BPP. The third part is the AP device with thickness of 5 mm, and the maximum working pressure and temperature of 70 MPa and 150 oC, respectively. This device was used to measure the AP in the crude oil of the experiment. The transmission of light in the crude oil was measured by the laser light at different wavelengths. The previous result shows that it seems more appropriate to use the near-infrared laser light in this paper. 2.4 Equal-Time-Stepwise Depressurization Approach. The objective of Equal-Time-Stepwise Depressurization Approach was to reduce the time consuming for achieving the equilibrium in the experimental process.35 A new equilibrium pressure condition 6


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was obtained by the large depressurization rate and then maintained constant for a certain period of time to enable the system to be stable. Then decrease the pressure until it reaches the target pressure. In this study, the depressurizing rate of 0.35 MPa/min and self stabilizing time of 30 minutes are used to determine the AOP, BPP, and ARP. The schematic of the Equal-Time-Stepwise depressurization approach is shown in Figure 2. 2.5 Experimental Procedures.

2.5.1 Phase diagram of asphaltene. Initially, the degassed crude must be filtered by 0.5 µm stainless steel filter before being injected into the PVT to make sure that there are no foreign solid particles to affect the follow-up experiment. The major portion of the filtered solid was insoluble in hot-toluene. In addition, the content of asphaltene (using ASTM D3279-97) in crude oil was almost unchanged before and after the experiments, which indicates that the filtration will not affect the ensuing experimental results. The degassing crude oil was injected into the PVT visual cell to determine the appropriate wave length of optimal translucent. On the basis of earlier experiments, it is set at 1550 nm. Then, firstly, the volumes of the degassed oil and the dissolved gas were calculated according to the actual GOR. Secondly, 150 ml degassed oil was injected into the PC kettle at the constant temperature, and the pressure of the PC kettle was increased to 2 MPa to release the air by ISCO pump. The degassed oil of PC kettle was injected into FPC kettle, and then the valve of PC kettle was closed. Thirdly, 192.8 ml dissolved gas was injected into the PC kettle under 10MPa. Then the valve of the PC kettle was opened, the mixed oil and gas were fully stirred until the gas was completely dissolved in the oil. The recombined live oil was continuously equilibrated for 7 to 10 days at the constant temperature and reservoir pressure to ensure the homogeneity of the oil sample that has 7


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restored to its original reservoir conditions. In the equilibrium process, the light transmittance of the crude oil was tested every 24 hours for actual changes in order to determine the time for the optimal mixture. After that, the live oil was depressurized in the isothermal condition to measure the changes of light transmittance in the crude oil of PVT, and the initial precipitation pressure and the re-dissolution pressure of asphaltene as well as the BPP of the crude oil were determined. In addition, through the variation of volume, the CCE was used to measure the BPP of the crude sample as well as its temperature during isothermal pressure depletion. In general, the AOP, the ARP, and the BPP of the crude oil were measured in this study at temperatures from the wellhead conditions to the initial reservoir conditions (44 oC, 60 oC, 80 o

C, 100 oC, and 123 oC). And then the APE (including the upper boundary and the lower

boundary) and the BPP curve were plotted by the measured values. 2.5.2 Prediction of the AP. Initially, the BPP curve, as well as the APE upper and lower boundaries, which is consist of the phase diagram of asphaltene, were plotted by the experimental values. Then, the intersection point of the P-T curve with the APE represents the deposition conditions (eg,. the pressure and temperature) of asphaltene in the sample well of WI-11. Finally, through the deposition conditions of asphaltene, the location of the precipitated asphaltene was determined by Pressure-Depth curve in the well. 2.5.3 Classification of errors. In this study, the errors of experiment include systematic errors, random errors, and gross errors, which are shown in Table 3. The systematic errors were caused by the apparatus itself and the experimental environment, which were inevitable. Moreover, it was also inevitable to reduce random errors in this paper because a huge number of experiments were required. However, there was no evidence of gross errors in this experiment because the results were saved by the computer. 8


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3.1 Recombination of crude oil. In this study, a solid (asphaltene) deposition laser detection system was designed to determine the power of transmitted light (PTL) of recombined oil under reservoir conditions. The results are used to estimate the stability of the recombined oil and determine whether the oil can be recovered to its initial state. This is very useful to simulate the experiment related to the oil properties at the reservoir conditions, which can affect the accuracy and reliability of the simulated tests.

Figure 3 shows the changing features of the PTL in the recombination process of live oil at the reservoir pressure of 55.2 MPa and different temperatures of 44 oC, 60 oC, 80 oC, 100 o

C, and 123 oC, respectively. It is observed that the PTL of the oil increased as the increase of

mixing time. It indicates that the solid asphaltene particles in the dispersion state re-dissolved in the crude oil. The PTL of the live oil system almost remains unchanged after equilibrating 7 days. This shows that the properties of the crude oil are stable after a week. In this study, the recombined live oil has been equilibrated for 10 days to ensure the complete dissolution of asphaltene.

3.2 Deposition Detection and CCE Test. Figure 4a shows that the PTL is a function of the pressure for the reservoir oil (live oil) at the temperature of 123 oC, and Figure 4b shows that the P-V diagram of the reservoir fluid sample at the temperature of 123 oC. A series of the PTL curves at different temperatures ranging from wellhead conditions to reservoir conditions (44 oC, 60 oC, 80 oC, 100 oC, and 123 oC) are depicted in Figure 5. It can be seen in Figure 4a, the value of PTL of the reservoir fluid increases as the system pressure increases. However, in the pressure depletion process, there are three turning points in the PTL curve, whose

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corresponding pressures are 35.2 MPa, 27.4MPa, and 22.8 MPa, respectively. These values of the turning points undergoing a slope change are representative of the AOP, the BPP, and the ARP, respectively. The reasons are listed as follows.

The overall PTL of the crude oil system drops sharply at its first turning point when system pressure drops to 35.2 MPa. The main reason is that in the system, the asphaltene solid particles or colloidal particles come into being by the aggregation of asphaltene and suspended in crude oil, which causes an increase in light scattering effects, and then offsets the increase of light transmittance resulting from the crude oil expansion. Therefore, the first turning point turns to be the initial pressure point of the AP.

The second turning point of light transmittance appears when the system pressure drops to 27.4 MPa. This point represents the BPP of crude oil. The results are explained by Hammami et al.1 As the crude oil starts degassing at the second turning point, the crude oil becomes denser with the increase of liquid crude oil density, and the optical refraction of the system grows stronger. Meanwhile, crude oil has been transformed from original two phases in the liquid and solid state into three phases, namely gas, liquid and solid. In addition, the PTL of the system drops sharply with the rapid increase of system volume at this point. As shown in Figure 4b, it can be seen from the P-V relation curve of CCE test that the volume of crude oil system rapidly increases at 26.9 MPa, which indicates the BPP of crude oil. This is attributed to the quick degasification of crude oil, which leads to a rapid expansion of the volume under the BPP. By comparing Figure 4a and 4b, it can be seen that the measured results have the difference of 1.8% when two methods are used to measure the BPP of crude

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oil. It proves that the light transmittance method is more reliable.

The third turning point of light transmittance appears when system pressure drops to 22.8 MPa, and this pressure represents the ARP of crude oil. At this point, the number of suspended solid particles declines in the system and the optical refraction weakens as the asphaltene re-dissolves. However, the third turning point of light transmittance is not as obvious as the other two turning points in mutation rate because the asphaltene re-dissolves at a relatively slower rate under this pressure.

Table 4 shows that the AOP and the ARP decreases as the temperature increases, but the BPP of the crude oil increases as the temperature increases at the range from the wellhead conditions (44 oC) to the reservoir conditions (123 oC). The comparison between literature results,18 and the variation trends of the AOP and BPP are similar.

3.3 Phase diagram of asphaltene. Figure 6 depicts the AOP, BPP, and ARP curves of crude oil. Three regions, namely Region I-stable asphaltene region, Region II-AP region and Region III-asphaltene re-dissolution region, are divided by the APE curve (within the temperature range of 44-123 oC) and the BPP curve (within the temperature range of 44-123 o

C). In Region I, AP will not occur in the crude oil. Meanwhile, because the thermodynamic

properties of the crude oil are stable, the system is in the state of homogeneous phase; In Region II, AP begins to occur in the system. Then as the temperature and pressure decline continuously, more asphaltenes precipitate. After that, when the pressure reaches BPP, gas is separated from the solution. At this moment, the system is consisted of three phases, namely, the liquid oil, the solid-phase asphaltene, and the dissolved gas, because the thermodynamic 11


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equilibrium of the system is broken. Furthermore, this point is that the amount of AP in the crude oil reaches its maximum.36 In Region III, the precipitated asphaltene in the crude oil is re-dissolved by virtue of the dissolved gas and the light hydrocarbons. This indicates that the amount of AP in the crude oil begins to reduce when the thermodynamic properties of the crude oil are in the lower boundary of the APE curve.36 However, AP will not completely re-dissolve in the crude oil at the actual operation. This is due to the relatively slower rate of dissolution and different flow rate of oil and gas. Consequently, the amount of AP remains unchanged from range of the BPP to the ARP (the lower boundary of the APE).

In this study, the measured results of AOP, BPP, and ARP under five different temperature conditions were fitted by the cubic polynomial curve-fitting model and then three equations were obtained. The cubic polynomial fitted equations of the APE curve (including the upper and lower boundaries within the temperature range of 44-123 oC) and the BPP curve (within the temperature range of 44-123 oC) can be written as:

Pau = 57.140 − 0.440T + 0.00385T 2 − 1.400 × 10 −5 T 3

（1）

Pal = 24.697 − 0.0174T − 1.109 ×10 −4 T 2 + 1.031×10 −6 T 3

（2 ）

Pb = 18.702 + 0.187T − 0.00155T 2 + 4.968 ×10 −6 T 3

（3 ）

Where, Pau , Pal , Pb are the AOP, the ARP, and the BPP, respectively, and T represents temperature. According to the literature,17,37-39 estimation of the effectiveness of this model depends on the R2 (performance coefficient), MSE (mean square error), MAAPE (maximum absolute percentage error), and MIAPE (minimum absolute percentage error). The MSE of this work is 12


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calculated through Eq 4.

MSE =

1 m n ∑ ∑[ X i ( j ) − Yi ( j )]2 2 j =1 i =1

(4)

In Eq 4, m refers to the number of tests and n is the number of experimental values. Xi(j) and Yi(j) are the forecasted values by equations 1, 2, and, 3 and experimental values, respectively. As shown in Table 5, the results of those parameters are determined using equation 1, 2, and 3. It indicates that the cubic polynomial fitting could be well applied in the fitting of these curves.

3.4 Prediction Method. The deposition pressure and temperature range of asphaltene in the well WI-11 are shown in Figure 7. In this study, the P-T curve is plotted by actual production data. This curve is intersected with the APE Upper Boundary representing the AOP (the pressure and temperature related to asphaltene are 38.3 MPa, and 93.8 oC, respectively), as well as is intersected with APE Lower Boundary representing the ARP (23.5 MPa, 65.0 oC). The reason is that the behavior of asphaltene is over-saturated in system when the thermodynamic point of system is located in the APE Upper Boundary. As the decline of system pressure, the thermodynamic equilibrium of system is destroyed, which leads to the precipitation of asphaltene. In addition, the behavior of asphaltene is under-saturated and re-dissolved in system when the thermodynamic reference point of system is located in the APE Lower Boundary.

Figure 8 shows the schematic diagram of deposition area in the well WI-11. It is obvious that by using this prediction method, the asphaltene deposition for the well initiates at a depth of 1930m, while the re-dissolution location is at a depth of 325m. Therefore, it can be concluded that the deposition range of asphaltene is from 325m to 1930m (at the temperature 13


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range of 65-93.8 oC and the pressure range of 23.5-38.3 MPa). In addition, in actual process, the initial deposition location for the well WI-11 is 1845 m, The length of the pipe in this case is 4093m, and thus the difference in the predicted values is about 2.1%. The parametric sensitivity analysis studies reported by Ramirez-Jaramillo et al.18 As the diameter of pipe decreases, the deposition layer is moving to a deeper depth, and vice versa. In addition, as the flow rate changes, the predicted behavior of deposition layer is similar to that when the diameter changes. Moreover, the mean width of the deposition will remain almost unchanged over the flow rate.

In summary, a valid method for AP prediction has been introduced. Thus, for the oil production operation, adding the chemical inhibitors or just maintaining the producing pressure above the predicted AOP may reduce the risk of asphaltene deposition and then reduce the total costs related to the removal of asphaltene blockage.

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A newly modified deposition laser detection apparatus was designed to investigate the phase behavior of asphaltene in live oil with high content of heavy hydrocarbons. Also, it was useful and reliable to verify the results determined by conventional CCE test. In addition, the depositional conditions of asphaltene in the well could also be determined, and the obtained result was consistent with the actual result. The following conclusions have been provided.

First of all, a detection system has been improved by increasing the laser power, which has higher accuracy and reliability. It is suitable for obtaining the phase behavior of asphaltene in heavier and darker crude. Secondly, the obtained values are comparable to results from CCE experiment with a relative error of only 1.8% for the Iran oil samples. Thirdly, for the well WI-11, the prediction results under live conditions almost matches the actual results with a deviation of 2.08%. What is more, from the phase diagram, the correlation equation of phase behavior can not only be used to determine the essential parameters of reservoir numerical simulation but also be used to optimize the mathematical prediction model of AP.

In addition, there are three regions divided by the APE curve and the BPP curve within the experimental temperature range of 44-123 oC, which include Region I-stable asphaltene region, Region II-AP region and Region III-asphaltene re-dissolution region.

Furthermore, the range of deposition zone of asphaltene in the well depends upon the variation range of temperature and pressure, which determined by producing P-T curve passed through the Region II-AP region. Meanwhile, for the AP problem, it can be concluded that adding certain chemical inhibitors in the crude oil at the Region I-asphaltene stable region 15


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(e.g., before the pressure of 32 MPa and temperature of 80 oC) to prevent or reduce the risk of AP is the most cost-effective way.

AUTHOR INFORMATION Corresponding Author *Telephone：+86-151-1694-6951. E-mail：[email protected] Present Address Now with China University of Petroleum, BEIJING, China. Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS The authors express their special thanks of gratitude to Prof. Yang and Dr. Qian for their help on asphaltene precipitation experimental. We also thank the CUPB to build the solid (asphaltene) deposition laser detection apparatus.

NOMENCLATURE Acronyms AP = asphaltene precipitation APE = asphaltene precipitation envelope AOP = asphaltene precipitation onset pressure ANN = artificial neural network ARP = asphaltene re-dissolution pressure BPP = bubble point pressure CCE = constant composition experiment CUPB = China University of Petroleum, BEIJING EOS = equation of state GOR = gas-oil ratio HTGC = high temperature gas chromatography

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HPLC = high performance liquid chromatography FID = flame ionization detectors PTL = power of transmitted light STO = stock tank oil SARA = saturates, aromatics, colloid and asphaltene SDS = solids detection system PVT = pressure-volume-temperature ICA = imperialist competitive algorithm IFT = interfacial tension R2 = performance coefficient MSE = mean square error MAAPE = maximum absolute percentage error MIAPE = minimum absolute percentage error

Variables Pau = asphaltene precipitation onset pressure

Pal = asphaltene re-dissolution pressure Pb = bubble point pressure T = temperature m = number of tests n = number of experimental values Xi(j) = forecasted values Yi(j) = experimental values

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REFERENCES (1) Hammami, A.; Phelps, C. H.; Monger-McClure, T.; Little, T. M. Energy Fuels 2000, 14, 14-18. (2) Hammami, A.; Chang-Chen, D.; Nighswander, J. A.; Stange, E. Fuel Sci. Technol. Int 1995, 13(9), 1167-1184. (3) Long, R. B. Adv. Chem. Ser. 1981, 195, 210-227. (4) Rana, M. S.; Samano, V.; Ancheyta, J.; Diaz, J. A. I. Fuel 2007, 86, 1216-1231 (5) Hirschberg, A.; De Jong, L. N. J.; Schiper, B. A.; Meiers, J. G. Influence of Temperature and Pressure on Asphaltene Flocculation. SPE J. 1984, 24, 283-293. (6) Buenrostro-Gonzales, E.; Groenzin, H.; Lira-Galeana, C.; Mullins, O. C. Energy Fuels 2001, 15, 972-978. (7) Irwin, A. Wiehe. Energy Fuels 2012, 26, 4004-4016. (8) Mullins, O. C. Energy Fuels 2010, 24, 2179-2207. (9) Liu, P.; Shi, Q.; Chung, K. H.; Xu, C. Energy Fuels 2010, 24, 2545-2553. (10) Schabron, J. F.; R, J. F., Jr.; Sanderson, M. M.; Loveridge, J. L.; Nyadong, L.; McKenna, A. M.; Marshall, A. G. Energy Fuels 2012, 26, 2256-2268. (11) Soorghali, F.; Zolghadr, A.; Ayatollahi, S. Energy Fuels 2014, 28, 2415-2421. (12) Hoepfner, M. P.; Limsakoune, V.; Chuenmeechao, V. et al. Energy Fuels, 2013, 27, 725-735. (13) Jamialahmadi, M.; Soltani, B.; M ü ller-Steinhagen, H.; Rashtchian, D. International Journal of Heat and Mass Transfer. 2009, 52, 4624-4634. (14) Buckley, S. J. Energy Fuels 2012, 26, 4086-4090. (15) Haskett, C. E.; Tartera, M. J. Pet. Technol. 1965, 17, 387-391. (16) Mendoza de la Cruz, J. L.; Argüelles-Vivas, F. J.; Matías-Pérez, V. Energy Fuels, 2009, 23, 5611-5625. (17) Zendehboudi, S.; Ahmadi, M. A.; Mohammadzadeh, O. Industrial & Engineering Chemistry Research, 2013, 52, 6009-6031. (18) Ramirez-Jaramillo, E.; Lira-Galeana, C.; Manero, O. Energy Fuels, 2006, 20, 1184-1196. (19) Donaggio, F.; Correra, S.; Lockhart, T. P. Pet. Sci. Technol. 2001, 19, 129-142. (20) Maqbool, T.; Balgoa, A. T.; Fogler, H. S. Energy Fuels, 2009, 23, 3681-3686. (21) Gonzalez, D. L.; Hirasaki, G. J.; Greek, J.; Chapman, W. G. Energy Fuels, 2007, 21, 1231-1242. (22) Mousavi-Dehghani, S. A., Riazi, M. R., Vafaie-Sefti, M., Mansoori, G. A. Journal of Petroleum Science & Engineering, 2004, 42, 145-156. (23) Kraiwattanawong, K.; Fogler, H. S.; Gharfeh, S. G.; Singh, P.; Thomason, H. W.; Chavadej, S. Energy Fuels, 2007, 21, 1248-1255. (24) Zendehboudi, S., Shafiei,A., Bahadori, A., James, L. A., Elkamel, A., Lohi, A. Chemical Engineering Research and Design. 2014, 92(5), 857-875. 18


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Energy & Fuels

(25) Riazi, M. R. "Characteristics of asphaltenic and waxy oils", 2013 Annual AIChE Meeitng, Session on Heavy Oil and Flow Assurance, San Francisco, USA, November 5, 2013. (26) Nghiem, L. X., Coombe, D. A. "Compositional simulation of asphaltene deposition and plugging", In: SPE annual technical conference and exhibition, New Orleans, Louisiana, 27–30 September, 1998. (27) Al-Sahhaf, T. A., Fahim, M. A., Elkilani, A. S. Fluid Phase Equilibria. 2002, 1045–1057. (28) Zhang Xiaohong, Pedrosa, N.; Moorwood, T. Energy Fuels, 2012, 26, 2611-2620. (29) Ghloum, E. F.; Oskui, G. P. Pet. Sci. Technol. 2004, 22, 1097-1117. (30) Aquino-Olivos, M. A.; Buenrostro-Gonzales, E.L.; Andersen, S. I.; Lira-Galeana, C. Energy Fuels, 2001, 15, 236-240. (31) Aquino-Olivos, M. A.; Andersen, S. I.; Lira-Galeana, C. Pet. Sci. Technol. 2003, 21, 1017-1041. (32) Jamaluddin, A. K. M.; Creek, J.; Kabir, C. S.; McFadden, J. D.; D’Cruz, D. A comparison of various laboratory techniques to measure thermodynamics asphaltene instability. In SPE 72154 presented at the Asia Pacific Improved Oil Recovery Conference held in Kuala Lumpur, Malaysia, October 8-9, 2001; p 1. (33) Jamaluddin, A. K. M.; Joshi, N.; Iwere, F.; Gurpinar, O. An investigation of asphaltene instability under nitrogen injection. In SPE 74393 presented at the SPE International Petroleum Conference and Exhibition in Mexico held in Villahermosa, Mexico, February 10-12, 2002; p 1. (34) Buenrostro-Gonzalez, E.; Espinosa-Peña, M.; Andersen, S. I.; Lira-Galeana, C. Pet. Sci. Technol. 2001, 19 (3&4), 299–316. (35) Zhou Y. In SPE 161147 presented at the International Petroleum Exhibition & Conference in Abu Dhabi, UAE, November 11-14, 2012. (36) Jamaluddin, A. K. M.; Creek, J.; Kabir, C. S. Journal of Canadian Petroleum Technology, 2002, 41(7):44-52. (37) Zendehboudi, S., Chatzis, I., Mohsenipour, A. A., Elkamel, A. Energy Fuels, 2011, 25 (4), 1731–1750. (38) Shafiei, A., Dusseault, M. B., Zendehboudi, S., Chatzis, I. Fuel, 2013, 108, 502-514. (39) Montgomery, D. C. Design and Analysis of Experiments, 7th ed., Wiley, New York, 2008.

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Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Carbon no. CO2 N2 C1 C2 C3 iC4 nC4 iC5 nC5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17

Page 20 of 25

Table 1. Compositional Analysis Result of Iran Crude Oil mol % Carbon no. 0 C18 0 C19 0 C20 0 C21 0.09 C22 0.07 C23 0.33 C24 0.34 C25 0.56 C26 1.3 C27 1.66 C28 7.21 C29 6.66 C30 5.8 C31 5.35 C32 4.75 C33 4.37 C34 4.02 C35 3.57 C36+ 3.1 合计 2.86

mol % 2.29 2.18 1.93 1.83 1.56 1.45 1.27 1.21 1.1 1.06 0.96 0.92 0.79 0.75 0.66 0.62 0.56 0.54 26.28 100

Table 2. SARA Analysis of the Crude Oil Samples (STO) SARA Contents

Weight percent (wt %)

Saturates

58.6

Aromatics

27.5

Resins

12.5

Asphaltenes

1.4

Table 3. Classification of Errors in the Experiment Classification of errors

Impact on the result

systematic errors

inevitability

random errors

inevitability

gross errors

virtually nonexistent

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

o

o

o

o

Table 4. Measured BPP, AOP, and ARP at different constant temperature (44 C, 60 C, 80 C, 100 C, o 123 C). Temperature( BPP(MPa) AOP(MPa) ARP(MPa) C) 44 24.3 44.1 23.8 60 25.5 41.3 23.5 80 26.1 39.7 23.1 100 26.9 37.4 22.9 123 27.4 35.2 22.8 Table 5. Performance of the AOP, BPP, and ARP model based on the experimental datas and prediction results calculated by equation 1, 2, and 3. Model

R2

MSE

MAAPE(%)

MIAPE(%)

AOP

0.9955

0.511

2.1078

0.2324

BPP

0.9928

0.000778

0.1001

0.01076

ARP

0.9979

0.0274

0.7112

0.1115

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Energy & Fuels

Figure 1. Schematic diagram of a solid (asphaltene) deposition laser detection system 60.0 55.0 pressure/MPa

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 25

50.0 45.0 40.0 35.0 30.0 25.0 20.0 0

500

1000

1500

2000

2500

Time/min

Figure 2. Schematic diagram of equal-time-stepwise depressurization approach

22


3000

30

29

29

28

28

27

27

26

26

25

25

24

24

23

23

22

44℃ 60℃ 80℃ 100℃ 123℃

20 19

22 21

Stabilized of the PTL

1

2

3

4

5

20 19

18 0

PTL(mW)

30

21

6

7

8

9

10

18 11

Time(D) Figure 3. PTL-T curve of the recombined live oil at different constant temperatures and

pressure of 55.2 MPa.

Volume(ml)

71

Bubble point

70 69

Figure 4a

68 28

20

25

30

35

40

Pressure/Mpa

45

50

55

60

27 26

PTL(mw)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

PTL(mW)

Page 23 of 25

25

Re-dissolution point

24

Onset Point

23 Bubble point

22

Figure 4b

21 20

25

30

35

40

45

50

55

60

Pressure(MPa)

Figure 4. Comparsion between the PTL and Volume as a function of the pressure depletion process at temperature of 123 oC 23


29.5

29.0

29.0

28.5

28.5

28.0

28.0

27.5

27.5

27.0

27.0

26.5

26.5

26.0

26.0

25.5

25.5

PTL(mW)

Page 24 of 25

29.5

25.0

25.0

44 ℃ 60 ℃ 80 ℃ 100 ℃ 123 ℃

24.5 24.0 23.5 23.0

24.5 24.0 23.5 23.0 22.5 60

22.5 20

25

30

35

40

45

50

55

Pressure(MPa)

Figure 5. PTL-P curve of the live oil at different constant temperature.

46 44

Bubble-point pressure curve

Ⅰ

Oil

42

APE Upper boundary APE Lower boundary

40 38

Pressure( MPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

PTL(mW)

Energy & Fuels

36 34

Ⅱ

32

Oil and Asphaltene

30 28 26

Oil , Gas and Asphaltene

24 22

Ⅲ

20

Oil and Gas

18 40

60

80

100

120

Temperature(℃)

Figure 6. P-T diagram of the crude oil. The points are obtained by experimental measurement and the curve is fitted by using polynomial fit technique. 24


Page 25 of 25

60

P-T Curve Bubble point Curve Upper boundary of APE Lower boundary of APE

Ⅰ

55

Pressure(MPa)

50 45

P=38.3MPa T=93.8℃

40

Ⅱ

35 30 25 20

P=23.5MPa T=65.0℃

Ⅲ

15 30

40

50

60

70

80

90

100

110

120

130

Temperature(℃) Figure 7. The deposition conditions of asphlatene for the WI-11 well.

0

0

500 P=23.5 MPa 1000

500

Deposit area of asphaltene

D=325 m

1000

1500

Depth(m)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

1500

P=38.3 MPa D=1950 m

2000

2000

2500

2500

3000

3000

3500

3500

4000

4000

4500

4500 20

25

30

35

40

45

50

55

60

Pressure(MPa)

Figure 8. The schematic diagram of deposition location of the asphaltene in the well.

25


Experimental Investigation and Application of the Asphaltene

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