A new insight into the modeling of asphaltene precipitation in crude oils using PC-SAFT equation of state

Khaleel, Aisha; Abutaqiya, Mohammed I. L.; Tavakkoli, Mohammad; Vargas, Francisco M.

doi:10.1190/rdp2018-41754282.1

Cited by 4 publications

(9 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, methods based on the saturates, aromatics, resins, and asphaltenes (SARA) analysis were developed. − Most of the crude oil modeling work performed using PC-SAFT makes use of the SARA analysis to characterize the dead oil. ,,− , The asphaltene pseudo-fraction is either treated as a monodisperse mixture , or a polydisperse mixture. , For purposes of modeling the asphaltene onset pressure (AOP), treating asphaltenes as a monodisperse fraction is sufficient to capture the phase behavior. However, if the objective is to study the amounts of precipitated asphaltenes, it is necessary to characterize asphaltenes as a polydisperse mixture. , …”

Section: Introductionmentioning

confidence: 99%

“…However, if the objective is to study the amounts of precipitated asphaltenes, it is necessary to characterize asphaltenes as a polydisperse mixture. 61,62 Yarranton and co-workers 63−65 extended the use of the Γ distribution to characterize the mass distribution of polydisperse asphaltenes and preformed the modeling using the advanced Peng−Robinson 66 EOS. Tavakkoli et al 49 extended the PC-SAFT characterization method of Punnapala and Vargas 38 to account for asphaltene polydispersity through the implementation of a Γ distribution function.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Systematic Investigation of Asphaltene Deposition in the Wellbore and Near-Wellbore Region of a Deepwater Oil Reservoir Under Gas Injection. Part 1: Thermodynamic Modeling of the Phase Behavior of Polydisperse Asphaltenes

et al. 2019

Self Cite

View full text Add to dashboard Cite

Thermodynamic modeling is conducted for a high-asphaltene, high-resin crude oil produced from a deepwater reservoir using the perturbed-chain statistical associating fluid theory (PC-SAFT). The asphaltenes are characterized as a polydisperse fraction following a three-parameter Γ distribution function with resins included as the lightest cut of the asphaltene distribution. Modeling results with 55 mol % injection indicate that the driving force of precipitation is sufficiently large that a significant amount of non-asphaltene components co-precipitate with asphaltenes. As pressure decreases from the upper asphaltene onset pressure (UAOP) to the bubble pressure (BP), the amount (by weight) of the asphaltene-rich phase surpasses the amount of the asphaltene-lean phase. Interestingly, as pressure decreases below the BP, the asphaltene-lean phase dissolves into the asphaltene-rich phase until the pressure reaches the lower onset pressure, where the lean phase is completely dissolved. As a result of the high driving force of precipitation, all asphaltenes precipitate out of solution before the BP and significant amounts of the other pseudo-fractions also co-precipitate. This causes the composition of asphaltenes in the asphaltene-rich phase to decrease as the pressure decreases, and the asphaltene composition in the asphaltene-rich phase at the upper onset is 23.6 wt %, which is uncommonly low for a precipitating phase. Experimental images from high-pressure microscopy show that the shape of the formed asphaltene-rich phase changes from a rigid solid-like structure near the UAOP to a soft liquid-like structure as the pressure decreases. This indicates a decrease in asphaltene composition during depressurization, similar to the simulation results produced by PC-SAFT. A sensitivity analysis is performed to evaluate the assumption of poly- and monodisperse asphaltenes from a modeling perspective and the effect of the Γ distribution parameters.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Systematic Investigation of Asphaltene Deposition in the Wellbore and Near-Wellbore Region of a Deepwater Oil Reservoir Under Gas Injection. Part 1: Thermodynamic Modeling of the Phase Behavior of Polydisperse Asphaltenes

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Similar to SAFT, PC-SAFT has accurately predicted the properties of various associating and nonassociating complex systems. ,− This work focuses on the phase behavior of asphaltene containing crudes where lots of work has been done using PC-SAFT equation of state either directly ,− or indirectly . Moreover, its prediction have been compared against cubic , and noncubic equations of state …”

Section: Application Of Saft Eosmentioning

confidence: 99%

Role of Characterization in the Accuracy of PC-SAFT Equation of State Modeling of Asphaltenes Phase Behavior

AlHammadi

AlBlooshi

2019

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

The ability to capture asphaltene precipitation conditions is key to minimize costs associated with production caused by asphaltene depositing and blocking wellbores and pipelines. In this work, modeling of asphaltene precipitation of crude oils is performed using the perturbed chain form of the statistical associating fluid theory (PC-SAFT) equation of state (EoS). The characterization of choice is crucial to the accuracy obtained from any equation of state. Therefore, an alternative characterization is proposed where the molecular weight of asphaltenes is assumed to be temperature-dependent. This allows more flexibility in matching experimental data. Moreover, it compensates for deficiencies of near-infrared (NIR) spectroscopy and high-pressure microscopy (HPM) techniques used to measure asphaltene onset pressure (AOP). Results from six crude oils ranging from Middle East to Gulf of Mexico with varying gas injections are shown and compared. The proposed characterization shows some advantage over the original characterization especially in the low-temperature region. Most importantly, it illustrates that better accuracy can be obtained without the need to consider association as proposed by some. In general, both characterizations give asphaltene precipitation tendency predictions within acceptable range of error. However, the modified characterization can be most beneficial when high accuracy is needed such as in calculating the amount of asphaltene anticipated to deposit.

show abstract

“…= mix onset (1) Thus, the driving force for asphaltene precipitation can be controlled by maintaining the same Δδ under different experimental conditions. 30 The solubility parameter can be obtained from Wang and Buckley's correlation (eqs 2 and 3), where they have presented a correlation between the solubility parameter and a function of the refractive index (F RI ) for nonpolar hydrocarbons.…”

Section: Introductionmentioning

confidence: 99%

“…Modeling asphaltene as a monodisperse fraction is often sufficient to accurately predict the asphaltene onset pressure (AOP). However, because asphaltene deposition is the primary concern, for such models the amount of asphaltene precipitated is an important input parameter, 1 and asphaltene polydispersity is a crucial element for understanding and accurately predicting asphaltene deposition and needs to be better understood.…”

mentioning

confidence: 99%

An Investigation of the Effect of Asphaltene Polydispersity on Asphaltene Precipitation and Deposition Tendencies

Khaleel

Sisco²,

Tavakkoli³

et al. 2022

Energy Fuels

Self Cite

View full text Add to dashboard Cite

It is well-known that asphaltenes are a polydisperse fraction present in crude oil with a broad distribution of sizes and molecular characteristics. However, in practice, asphaltenes are often treated both in the laboratory and in modeling work as a monodisperse fraction. In this work, asphaltene deposition tests with two model oils with the same total amount of asphaltenes but with different asphaltene polydispersity distributions were conducted using a high-pressure, high-temperature packed-bed deposition column. Although the asphaltenes used to prepare the two oils were extracted from the same source, a drastic difference in the amount of asphaltene deposited was observed, which is attributed to the difference in the asphaltene polydispersity between the two samples. Additionally, using UV−visible spectroscopy, it is possible to observe some similarities between the aromaticity of asphaltene subfractions obtained from different geographical locations. Modeling results provide additional insights into the impact of asphaltene polydispersity on the onset and the amount of asphaltene precipitation. The results presented in this work suggest that asphaltene polydispersity plays a major role in determining asphaltene precipitation and deposition tendencies observed in different oils.

show abstract

A new insight into the modeling of asphaltene precipitation in crude oils using PC-SAFT equation of state

Cited by 4 publications

References 17 publications

Systematic Investigation of Asphaltene Deposition in the Wellbore and Near-Wellbore Region of a Deepwater Oil Reservoir Under Gas Injection. Part 1: Thermodynamic Modeling of the Phase Behavior of Polydisperse Asphaltenes

Systematic Investigation of Asphaltene Deposition in the Wellbore and Near-Wellbore Region of a Deepwater Oil Reservoir Under Gas Injection. Part 1: Thermodynamic Modeling of the Phase Behavior of Polydisperse Asphaltenes

Role of Characterization in the Accuracy of PC-SAFT Equation of State Modeling of Asphaltenes Phase Behavior

An Investigation of the Effect of Asphaltene Polydispersity on Asphaltene Precipitation and Deposition Tendencies

Contact Info

Product

Resources

About