Implementation of PC-SAFT Equation of State Into MRST Compositional for Modelling of Asphaltene Precipitation

Masoudi, Mohammad; Parvin, Salina; Miri, Rohaldin; Kord, Shahin; Hellevang, Helge

doi:10.3997/2214-4609.202011432

Cited by 4 publications

(3 citation statements)

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“…The perturbedchain (PC) extension of SAFT proposed by Gross and Sadowski [15], in which the spherical particles of the original SAFT EoS are replaced by a hard-chain fluid, has become particularly popular. In recent work, Masoudi et al [24,25] used MRST to extend PC-SAFT to also include ionic interactions (electrolyte PC-SAFT or simply ePC-SAFT), and work is underway to include this EoS in the public release.…”

Section: Equation Of Statementioning

confidence: 99%

“…Cubic EoS are generally favored for their efficiency and limited number of parameters, but significant interest has also been devoted to PC-SAFT-type equations [15] derived from statistical mechanics. The official release of MRST will soon include the ePC-SAFT version [24,25], which requires five molecular-based parameters per component for associating fluids and only three for nonassociating ones. Generally, PC-SAFT-type equations describe liquid systems better than traditional cubic EoS.…”

Section: Limitations and Caveatsmentioning

confidence: 99%

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Compositional Simulation with the AD-OO Framework

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Section: Equation Of Statementioning

confidence: 99%

Section: Limitations and Caveatsmentioning

confidence: 99%

Compositional Simulation with the AD-OO Framework

Møyner

2021

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“…This chemical incompatibility between the in-situ formation brine and injected aqueous phase could result in inorganic scale precipitation, which could ultimately cause scale deposition in the near wellbore region as well as deep into the reservoir, depending on the flow dynamics and rock and fluid properties (Mackay 2003). This could result in potential permeability impairment, flow diversion, injectivity reduction and loss of oil production which negatively impact the economics of oil production (Bajammal et al 2013;Bedrikovetsky et al 2009a, b;Bedrikovetsky et al 2004;Bedrikovetsky et al 2009a, b;Haghtalab et al 2014;Hajirezaie et al 2017;Hajirezaie et al 2019;Mackay et al 2003b;Masoudi et al 2020;Moghadasi et al 2006;Parvin et al 2020;Rocha et al 2001). Reduction of well injectivity/productivity is a common problem when it comes to incompatible water injection scenarios (Jordan et al 2008;Mackay et al 2003a).…”

Section: Introductionmentioning

confidence: 99%

Reactive transport modeling of scale precipitation and deposition during incompatible water injection in carbonate reservoirs

Shojaee,

Kord,

Miri

et al. 2023

J Petrol Explor Prod Technol

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Seawater injection is an efficient enhanced oil recovery (EOR) method that capitalizes on the chemical composition differences between the injecting seawater and in-situ formation water, which leads to physicochemical interactions between the rock and fluids. These rock and fluid interactions result in changes of rock wettability and subsequent improved microscopic sweep efficiency. However, the ion imbalance resulting from seawater injection and its incompatibility with the in-situ formation water may interfere with the rock and fluids equilibrium state, causing scale precipitation and subsequent deposition which can negatively impact rock quality, well productivity and reservoir performance. In this study, an accurate, robust, and general approach is presented by coupling a geochemical module with a compositional two-phase fluid flow model to handle reactive transport in porous media. The proposed coupled model, so-called ad-scale model, is capable of simulating carbonate rock dissolution and sulfate scale formation/deposition for evaluating reservoir performance under incompatible water injection. The model predictions were validated using experimental data. This model was also utilized to predict water injection rate into a carbonate formation. It was obtained that both the reacting and non-reacting component profiles were accurately predicted using the proposed coupled model. The water injection rate prediction was also validated and showed high accuracy with absolute error and coefficient of determination values of 9.02% and 0.99, respectively. In addition, a sensitivity analysis was performed on water composition, which showed a strong dependence of reservoir and well performance on water composition. Graphical abstract This diagram elucidates what exactly happens during incompatible water injection in the mixing zones near the injection well (right half of the figure) or production well (left half of the figure) where most of the geochemical phenomena occur.

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Comparative study of machine learning algorithms in predicting asphaltene precipitation with a novel validation technique

Khalighi,

Cheremisin

2023

Earth Sci Inform

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Implementation of PC-SAFT Equation of State Into MRST Compositional for Modelling of Asphaltene Precipitation

Cited by 4 publications

References 0 publications

Compositional Simulation with the AD-OO Framework

Compositional Simulation with the AD-OO Framework

Reactive transport modeling of scale precipitation and deposition during incompatible water injection in carbonate reservoirs

Comparative study of machine learning algorithms in predicting asphaltene precipitation with a novel validation technique

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