REVストレインと石炭のメソスケール変形法と主要パラメータの感度分析に基づいた透過性モデルセット
Wei Wang1, Wenzhi Li1, Jinhao Yu1
1School of Civil Engineering and Architecture, Henan University, Kaifeng 475004, China.
ACS omega
|September 2, 2025
まとめ
炭床メタンの利用のための新しい浸透性モデルは,立方法と代表的な元素容量を用いて開発されました. 立方法則等価 (CLE) モデルは,恒定行列幅 (CMW) モデルよりも実験データとよりよく一致していますが,どちらも大きなフィッティングエラーを示しています.
科学分野:
- 地理科学
- 地球科学
- 石油工学
背景:
- 炭鉱床の浸透性を正確に予測することは,効率的な炭鉱床メタン (CBM) 資源の利用に不可欠です.
- 既存のモデルは,ストレス下での石炭の複雑な変形行動を完全に捉えることができないかもしれません.
研究 の 目的:
- 代表的要素容量 (REV) と立方法に基づく新しい透かし性モデルを導き出し,評価する.
- ストレス環境下における石炭のメソスケール変形を現実的に表現する.
主な方法:
- 3つのモデルセットの開発:立方法の等価 (CLE),常時行列幅 (CMW),常時REV容量 (CRV).
- 実験データに対するモデルの性能の分析,フィッティングエラーとパラメータの感度に焦点を当てた.
主要な成果:
- 実際のストレスの関係を取り入れたCLEモデルセットは,CMWモデルセットと比較して実験データとのより良い一致を示した.
- CMWとCLEのモデルセットは,特に異なるガス (N2,CH4,CO2) の散布モジュールと吸い込みストレスの係数について,実質的な2パラメータフィッティング (PF-2) のエラーを示しました.
- パラメータの感度分析では,ボリューム・モジュール,断裂・ボリューム・モジュール,吸い込みストレスの係数がモデル予測に有意な影響を及ぼしていることが明らかになった.
結論:
- 導出された透過性モデルは,石炭のメソスケール変形をより現実的に表現します.
- 重要なフィッティングエラーは,CBMリソースの正確な評価のためにこれらのモデルのさらなる精錬の必要性を強調します.
- パラメータの感度を理解することは,モデルの精度を改善し,予測バイアスを減らすための鍵です.
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