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Atomistic insight into salinity dependent preferential binding of polar aromatics to calcite/brine interface: implications to low salinity waterflooding.

ABSTRACT: This paper resolve the salinity-dependent interactions of polar components of crude oil at calcite-brine interface in atomic resolution. Molecular dynamics simulations carried out on the present study showed that ordered water monolayers develop immediate to a calcite substrate in contact with a saline solution. Carboxylic compounds, herein represented by benzoic acid (BA), penetrate into those hydration layers and directly linking to the calcite surface. Through a mechanism termed screening effect, development of hydrogen bonding between -COOH functional groups of BA and carbonate groups is inhibited by formation of a positively-charged Na⁺ layer over CaCO₃ surface. Contrary to the common perception, a sodium-depleted solution potentially intensifies surface adsorption of polar hydrocarbons onto carbonate substrates; thus, shifting wetting characteristic to hydrophobic condition. In the context of enhanced oil recovery, an ion-engineered waterflooding would be more effective than injecting a solely diluted saltwater.

SUBMITTER: Koleini MM

PROVIDER: S-EPMC8184864 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Atomistic insight into salinity dependent preferential binding of polar aromatics to calcite/brine interface: implications to low salinity waterflooding.

Koleini Mohammad Mehdi MM Badizad Mohammad Hasan MH Mahani Hassan H Dastjerdi Ali Mirzaalian AM Ayatollahi Shahab S Ghazanfari Mohammad Hossein MH

Scientific reports 20210607 1

This paper resolve the salinity-dependent interactions of polar components of crude oil at calcite-brine interface in atomic resolution. Molecular dynamics simulations carried out on the present study showed that ordered water monolayers develop immediate to a calcite substrate in contact with a saline solution. Carboxylic compounds, herein represented by benzoic acid (BA), penetrate into those hydration layers and directly linking to the calcite surface. Through a mechanism termed screening eff ...[more]

PMID: 34099800

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Project description:Low salinity waterflooding has proven to accelerate oil production at core and field scales. Wettability alteration from a more oil-wetting to a more water-wetting condition has been established as one of the most notable effects of low salinity waterflooding. To induce the wettability alteration, low salinity water should be transported to come in contact with the oil-water interfaces. Transport under two-phase flow conditions can be highly influenced by fluids topology that creates connected pathways as well as dead-end regions. It is known that under two-phase flow conditions, the pore space filled by a fluid can be split into flowing (connected pathways) and stagnant (deadend) regions due to fluids topology. Transport in flowing regions is advection controlled and transport in stagnant regions is predominantly diffusion controlled. To understand the full picture of wettability alteration of a rock by injection of low salinity water, it is important to know i) how the injected low salinity water displaces and mixes with the high salinity water, ii) how continuous wettability alteration impacts the redistribution of two immiscible fluids and (ii) role of hydrodynamic transport and mixing between the low salinity water and the formation brine (high salinity water) in wettability alteration. To address these two issues, computational fluid dynamic simulations of coupled dynamic two-phase flow, hydrodynamic transport and wettability alteration in a 2D domain were carried out using the volume of fluid method. The numerical simulations show that when low salinity water was injected, the formation brine (high salinity water) was swept out from the flowing regions by advection. However, the formation brine residing in stagnant regions was diffused very slowly to the low salinity water. The presence of formation brine in stagnant regions created heterogeneous wettability conditions at the pore scale, which led to remarkable two-phase flow dynamics and internal redistribution of oil, which is referred to as the "pull-push" behaviour and has not been addressed before in the literature. Our simulation results imply that the presence of stagnant regions in the tertiary oil recovery impedes the potential of wettability alteration for additional oil recovery. Hence, it would be favorable to inject low salinity water from the beginning of waterflooding to avoid stagnant saturation. We also observed that oil ganglia size was reduced under tertiary mode of low salinity waterflooding compared to the high salinity waterflooding.

Project description:Low salinity waterflooding (LSWF) and its variants also known as smart water or ion tuned water injection have emerged as promising enhanced oil recovery (EOR) methods. LSWF is a complex process controlled by several mechanisms and parameters involving oil, brine, and rock composition. The major mechanisms and processes controlling LSWF are still being debated in the literature. Thus, the establishment of an approach that relates these parameters to the final recovery factor (RFf) is vital. The main objective of this research work was to use a number of artificial intelligence models to develop robust predictive models based on experimental data and main parameters controlling the LSWF determined through sensitivity analysis and feature selection. The parameters include properties of oil, rock, injected brine, and connate water. Different operational parameters were considered to increase the model accuracy as well. After collecting the relevant data from 99 experimental studies reported in the literature, the database underwent a comprehensive and rigorous data preprocessing stage, which included removal of duplicates and low-variance features, missing value imputation, collinearity assessment, data characteristic assessment, outlier removal, feature selection, data splitting (80-20 rule was applied), and data scaling. Then, a number of methods such as linear regression (LR), multilayer perceptron (MLP), support vector machine (SVM), and committee machine intelligent system (CMIS) were used to link 1316 data samples assembled in this research work. Based on the obtained results, the CMIS model was proven to produce superior results compared to its counterparts such that the root mean squared rrror (RMSE) values for both training and testing data are 4.622 and 7.757, respectively. Based on the feature importance results, the presence of Ca2+ in the connate water, Na+ in the injected brine, core porosity, and total acid number of the crude oil are detected as the parameters with the highest impact on the RFf. The CMIS model proposed here can be applied with a high degree of confidence to predict the performance of LSWF in sandstone reservoirs. The database assembled for the purpose of this research work is so far the largest and most comprehensive of its kind, and it can be used to further delineate mechanisms behind LSWF and optimization of this EOR process in sandstone reservoirs.

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Atomistic insight into salinity dependent preferential binding of polar aromatics to calcite/brine interface: implications to low salinity waterflooding.

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Atomistic insight into salinity dependent preferential binding of polar aromatics to calcite/brine interface: implications to low salinity waterflooding.

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