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Nanomechanics and pore structure evolution in organic-rich shale reservoirs during high-temperature treatment: A multi-scale analysis of microscopic stability
Advances in Geo-Energy Research 2025, 17(3): 241-255
Published: 05 September 2025
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To address the challenges of conflicting macroscopic mechanical tests and the inability to reveal complex nanoscale mechanisms during deep shale thermal modification, this study comprehensively investigates the microstructural and nanomechanical evolution of Longmaxi shale under heat treatment. This involves the innovative combination of gas adsorption, atomic force microscope high-resolution mapping, and multi-level spatial statistical analysis to systematically elucidate the spatial evolution of the pore structure of shale, surface morphology, and nanomechanical properties. The findings reveal a unique hardening-softening-rehardening three-stage pattern: From 25-400 ℃, the average reduced modulus increases due to dehydration; from 400-600 ℃, organic matter pyrolysis significantly decreases the modulus, with intense atomic force microscope topographic uplift; from 600-900 ℃, the modulus slightly increases again due to structural collapse and pore network regeneration. Local indicators of spatial association analysis shows that this macro evolution stems from synergistic microscopic phase space reshaping. Crucially, the mesopore volume increases most significantly in the 400-500 ℃ range, and it exhibits its most notable increase. Considering energy efficiency and feasibility, this study demonstrates for the first time that 400-500 ℃ is an ideal temperature window for effective organic matter pyrolysis and nanopore optimization from a nanoscale spatial distribution and geometric stability perspective. This work provides crucial micro-mechanical mechanism support and precise temperature guidance for deep shale thermal modification, significantly outperforming the temperature ranges from traditional macroscopic experiments and filling the gap in macro-nanoscale mechanical discrepancies and spatial feature analysis.

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