Evidence map›Paper›PMID 41145542›Full record

ArticleScientific reports2025

Experimental study and geochemical modeling of the effect of asphaltene during smart water flooding in carbonate reservoirs.

Maryam Ghorbani-Bavariani, Arezoo Rezaei, Mohammad Ahmadi, Hamid Vatanparast, Abdolhossein Hemmati-Sarapardeh

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Maryam Ghorbani-BavarianiPetroleum and GeoEnergy Engineering Department, Amirkabir University of Technology, Tehran, Iran. m_ghorbany@aut.ac.ir.
Arezoo RezaeiPetroleum and GeoEnergy Engineering Department, Amirkabir University of Technology, Tehran, Iran. a_rezaei@aut.ac.ir.
Mohammad AhmadiPetroleum and GeoEnergy Engineering Department, Amirkabir University of Technology, Tehran, Iran.
Hamid VatanparastPetroleum Engineering Research Division, Research Institute of Petroleum Engineering, Tehran, Iran.
Abdolhossein Hemmati-SarapardehDepartment of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the role of crude oil properties, especially the asphaltene content of crude oil is crucial for enhancing the efficiency of smart water flooding, as it significantly impacts wettability and recovery factors. This study evaluates the predictive capabilities of a developed geochemical model for predicting wettability alteration during smart water flooding in carbonate reservoirs. Three types of oil samples with varying asphaltene content were employed: crude oil (8.5% asphaltene), deasphalted oil (1.8% asphaltene), and asphaltene-enriched toluene (98% asphaltene). Core flooding experiments were conducted using five types of brines: seawater, twice the sulfate concentration (2SO₄), four times the sulfate concentration (4SO₄), four times the calcium concentration (4Ca), and four times the magnesium concentration (4Mg). The model integrates DLVO (Derjaguin, Landau, Verwey, and Overbeek) theory and calculates zeta potential and disjoining pressure based on the crude oil/brine/rock (COBR) system properties such as ionic composition and oil properties. Recovery factor measurements and contact angle analyses confirmed the model's accuracy, with seawater injection in asphaltene-rich oil resulting in the most negative electrical double layer (EDL) pressure (- 350 MPa) and a recovery factor of 10%. Conversely, 4Mg brine demonstrated superior performance in promoting water-wet conditions for both crude oil (21.34% recovery factor) and deasphalted oil (18.41% recovery factor). This study underscores the critical role of brine composition and crude oil properties in optimizing smart water flooding strategies and validates the geochemical model as a robust tool for tailoring brine compositions to enhance oil recovery in carbonate reservoirs.

Indexed as

Asphaltene contentBrine compositionGeochemical modelSmart water injectionZeta potential

Identifiers

PMID41145542
PMCPMC12559737

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.