Research on Geological–Engineering “Double-Sweet Spots” Grading Evaluation Method for Low-Permeability Reservoirs with Multi-Parameter Integration

The development of low-permeability reservoirs offshore entails substantial investment and demands high production capacity for oil and gas. Consequently, the analysis and evaluation of key elements for integrated geological–engineering sweet spots have become essential. This study systematically establishes a coupled analysis methodology for geological and engineering parameters of low-permeability reservoirs, based on Offshore Oilfield A. A comprehensive evaluation framework for geological–engineering sweet spots is proposed, which applies grey relational analysis and the analytic hierarchy process. Twelve geological–engineering sweet spots were analysed, with corresponding parameter weightings determined. Geological sweet spots encompassed factors such as porosity, permeability, and oil saturation, and engineering sweet spots considered Young’s modulus, Poisson’s ratio, fracture factor, and brittleness index. Low-permeability reservoirs were categorised into Classes I, II, III, and IV by establishing indicator factors. Integrating seismic inversion and reservoir numerical simulation methods, we constructed an analysis model. This methodology resolves challenges in evaluating offshore low-permeability reservoirs, enabling rapid and precise sweet spot identification. It provides critical technological support for enhancing oil and gas production efficiency.

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Publication Details

Journal
Processes
Published
2025-09-17
DOI
https://doi.org/10.3390/pr13092967
Primary Topic
Hydraulic Fracturing and Reservoir Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on Geological–Engineering “Double-Sweet Spots” Grading Evaluation Method for Low-Permeability Reservoirs with Multi-Parameter Integration

Shuwen Guo, Yan Ge, Zhandong Li, Yihe Li et al.
Processes
Hydraulic Fracturing and Reservoir Analysis
article

Research on Geological–Engineering “Double-Sweet Spots” Grading Evaluation Method for Low-Permeability Reservoirs with Multi-Parameter Integration

Shuwen Guo, Yan Ge, Zhandong Li, Yihe Li, Haixiang Zhang, Lingtong Liu
article en

Abstract

The development of low-permeability reservoirs offshore entails substantial investment and demands high production capacity for oil and gas. Consequently, the analysis and evaluation of key elements for integrated geological–engineering sweet spots have become essential. This study systematically establishes a coupled analysis methodology for geological and engineering parameters of low-permeability reservoirs, based on Offshore Oilfield A. A comprehensive evaluation framework for geological–engineering sweet spots is proposed, which applies grey relational analysis and the analytic hierarchy process. Twelve geological–engineering sweet spots were analysed, with corresponding parameter weightings determined. Geological sweet spots encompassed factors such as porosity, permeability, and oil saturation, and engineering sweet spots considered Young’s modulus, Poisson’s ratio, fracture factor, and brittleness index. Low-permeability reservoirs were categorised into Classes I, II, III, and IV by establishing indicator factors. Integrating seismic inversion and reservoir numerical simulation methods, we constructed an analysis model. This methodology resolves challenges in evaluating offshore low-permeability reservoirs, enabling rapid and precise sweet spot identification. It provides critical technological support for enhancing oil and gas production efficiency.

ProcessesVol. 13(9)
Research Institute of Petroleum Exploration and Development (CN), Northeast Petroleum University (CN)
Natural Science Foundation of Hainan Province, Northeast Petroleum University
Openalex Percentile: Top 74%
Hydraulic Fracturing and Reservoir Analysis
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Research on Geological–Engineering “Double-Sweet Spots” Grading Evaluation Method for Low-Permeability Reservoirs with Multi-Parameter Integration — Shuwen Guo, Yan Ge, et al. · Processes (2025) | TGRS Research Map | TGRS