シェール貯留層における第一次ハフ・アンド・パフ炭化水素回収とCO2貯留の無次元スケーリング
Dimensionless Scaling of First-Cycle Huff-n-Puff Hydrocarbon Recovery and CO2 Storage in Shale Reservoirs (原題)
Qian Zhang, Ming Ma, H. Emami-Meybodi
🤖 gxceed AI 要約
日本語
本研究は、シェール貯留層での循環CO2圧入（ハフ・アンド・パフ）における炭化水素回収率とCO2貯留効率を支配する無次元数を、次元解析により初めて同定した。Vaschy–BuckinghamのΠ定理に基づき、フーリエ数や拡散率比、流体–固体摩擦係数などを含むスケーリング関係を導出し、回収率と貯留率それぞれに臨界点（ψRC=0.0015、ψSC=0.0025）が存在することを示した。これにより、貯留層間で転用可能な最適化指針を低計算コストで提供する。
English
This study applies dimensional analysis for the first time to cyclic CO2 huff-n-puff in shale reservoirs, identifying key dimensionless groups governing hydrocarbon recovery (RF) and CO2 storage (EF). Using the Vaschy–Buckingham Pi theorem, it derives scaling relations with response-specific Fourier numbers, diffusivity ratios, and fluid-solid friction moduli, revealing critical transition points (ψRC=0.0015, ψSC=0.0025) between mixing- and retention-limited regimes. The result offers transferable, low-cost optimization guidance for CCUS in ultratight reservoirs.
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
CCUSは日本のGX実現に向けた重要技術であり、特にCO2貯留ポテンシャル評価やEORとの統合はエネルギー安全保障と脱炭素の両立に資する。本論文のスケーリング則は、国内での貯留層評価やCCUSプロジェクト設計の効率化に示唆を与える。
In the global GX context
As CCUS is central to global net-zero pathways and increasingly embedded in climate disclosure and transition finance frameworks, this work advances the engineering optimization of CO2 storage combined with enhanced recovery. The dimensionless scaling approach improves transferability of injection designs across reservoirs, supporting more credible CCUS project economics.
👥 読者別の含意
🔬研究者:次元解析をCCUSプロセス最適化に適用する手法と臨界点の物理的解釈が参考になる。
🏢実務担当者:シェール・超緻密貯留層でのCO2圧入設計において、計算コストを抑えた最適化指針として活用できる。
🏛政策担当者:CCUSプロジェクトの貯留効率評価や技術実証の設計基準を検討する際の参考になる。
📄 Abstract（原文）
Cyclic CO2 injection is the key component of carbon capture, utilization, and storage (CCUS) that enhances hydrocarbon recovery while sequestering CO2, contributing to global greenhouse gas mitigation. However, its optimization remains challenging because the process is governed by numerous interacting variables with nonlinear and competing effects, limiting the transferability of optimized parameters across reservoir systems. To address this, for the first time, this study applies dimensional analysis to identify the key dimensionless groups and establish physically interpretable scaling relations governing CO2 injection performance, enabling optimization with substantially reduced computational cost. A species-based mass transport model incorporating inhomogeneous fluid distribution induced by fluid–solid interactions is used to simulate cyclic CO2 injection and generate a comprehensive data set for dimensional analysis. Based on the Vaschy–Buckingham Pi theorem, dimensional analysis reveals key dimensionless groups governing hydrocarbon recovery (RF) and CO2 storage (EF), including response-specific Fourier numbers (FoR, FoS), diffusivity ratios (RDR, RDS), fluid–solid friction modulus (φR, φS), together with time ratio (RT), normalized drawdown pressure (PD), and relative fluid–solid interaction coefficient (χ). The RF scaling relation identifies a critical point, i.e., ψRC = 0.0015, separating mixing-dominated and mixing-limited regimes, providing a calibrated transition criterion for identifying diminishing recovery gains. The critical point ψSC = 0.0025 in the EF scaling relation marks the transition between retention-growth and retention-limited regimes, beyond which additional gains in postcycle CO2 retention diminish. This study provides practical guidance for cyclic CO2 injection in ultratight reservoirs, supporting more effective CO2 utilization for hydrocarbon recovery and improved CO2 storage performance.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://pubs.acs.org/enfuem/article-pdf/doi/10.1021/acs.energyfuels.6c04290/68988713/acs.energyfuels.6c04290.pdffirst seen 2026-10-31 05:41:44 · last seen 2026-11-05 06:00:28
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