Co‐optimization of CO 2 flooding and storage technology in low permeability reservoir
低浸透性貯留層におけるCO2圧入・貯留技術の同時最適化 (AI 翻訳)
Jiatie Cai, Di Wu, Xing Xu, Ruotong Wang, Huiyang Ma, Yi Pan
🤖 gxceed AI 要約
日本語
低浸透性貯留層を対象に、CO2圧入・貯留プロセスの数学的・物理的モデルを構築し、動的進化特性を解析。多目的粒子群最適化アルゴリズムを用いて、原油回収と炭素貯留の二目的最適化を実施。提案手法によりCO2回収率9.7%向上、貯留率16.67%向上、NPV66.5%増加を達成。
English
This study develops a mathematical and physical model for CO2 flooding and storage in low-permeability reservoirs, analyzes dynamic evolution, and uses multi-objective particle swarm optimization to optimize injection parameters. Results show a 9.7% increase in CO2 recovery rate, 16.67% increase in storage rate, and 66.5% increase in NPV, providing technical support for CCUS optimization.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のGX戦略ではCCUSは重点分野であり、本論文は低浸透性貯留層におけるCO2圧入・貯留の最適化手法を提供する点で、国内のCCUSプロジェクトの効率向上に寄与する可能性がある。
In the global GX context
CCUS is critical for global net-zero targets. This paper offers a novel co-optimization framework for CO2 flooding and storage, balancing oil recovery and carbon sequestration, which can inform international CCUS project design.
👥 読者別の含意
🔬研究者:Provides a validated multi-objective optimization model for CO2 flooding-storage that can be applied to similar reservoir studies.
🏢実務担当者:Offers a practical optimization scheme to improve CO2 recovery and storage efficiency, enhancing project economics.
🏛政策担当者:Demonstrates the potential of CCUS technology to achieve both climate and economic benefits, supporting policy incentives.
📄 Abstract（原文）
Carbon capture, utilization, and storage (CCUS) technology plays a crucial role in mitigating global warming. CO 2 flooding‐storage technology provides substantial economic and environmental benefits by enhancing oil recovery while promoting carbon storage. This study focuses on low‐permeability reservoirs. By constructing the mathematical and physical model of CO 2 flooding‐storage process, the dynamic evolution characteristics of CO 2 flooding process are analyzed, with model accuracy verified through fitting. Secondly, a collaborative evaluation index for CO 2 flooding and storage is proposed, based on a dynamic weighting function and improved characterization parameters. And consider the dual objectives of oil displacement and carbon storage, an optimization process is formulated using a multi‐objective particle swarm optimization algorithm. Then, the engineering objectives of different development stages are analyzed, and the key parameters such as injection speed and pressure in each stage are optimized. Finally, the effectiveness of the proposed scheme is validated through the combination of the model and optimization algorithm. The research results show that the CO 2 recovery rate and storage rate have increased by 9.7% and 16.67% respectively, and the project NPV has increased by 66.5%. The optimization plan has significantly improved the CO 2 recovery and storage rates, and the economic benefits have also been significantly enhanced, providing theoretical basis and technical support for achieving the coordinated optimization of CO 2 flooding and storage.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/ep.70433first seen 2026-05-05 23:59:52
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