An improved hybrid screening framework for reservoir selection in CO₂-Enhanced oil recovery

Abstract

The oil and gas industry increasingly employs advanced engineering solutions to optimize enhanced oil recovery (EOR). A systematic and effective screening process, supported by multi-criteria decision-making (MCDM) techniques, is essential for selecting appropriate reservoirs and EOR strategies toward production optimization. This study introduces a screening framework designed to identify the most suitable EOR alternative. The proposed approach integrates a coupled objective-subjective weighting method to assign criteria weights, followed by a refined, data-driven, non-linear scoring procedure and an improved approach for prioritizing EOR alternatives. A distance-based scoring method is developed to evaluate alternatives against a desired screening interval, utilizing the full consistency method (FUCOM) and simultaneous evaluation of criteria and alternatives (SECA) model for weighting criteria and subsequently integrating them into a unified assessment. The ranking of alternatives is performed using a modified version of the approach introduced by Dickson et al. (2010). The applicability of the proposed framework is demonstrated through two CO₂-EOR case studies, while its reliability is assessed through technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The Spearman's rank correlation coefficient for three ranking methods was over 0.982 for Iran's CO₂-EOR screening case and above 0.943 for Canada's, showing the robustness and consistency of the ranking results. The findings confirm the effectiveness of the developed hybrid decision-support framework in optimizing EOR strategy selection, thereby contributing to more efficient hydrocarbon recovery in line with carbon capture and storage objectives.

Keywords

Enhanced oil recovery / Carbon storage / Screening / Multi-criteria decision-making / Reservoir selection

CRediT authorship contribution statement

Milad Ghafoori: Writing – original draft, Software, Methodology, Investigation, Formal analysis. Shahin Kord: Writing – review & editing, Supervision, Investigation, Conceptualization. Amin Daryasafar: Writing – original draft, Software, Methodology, Conceptualization. Hao Chen: Writing – review & editing, Validation, Supervision, Investigation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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