Driven by global carbon neutrality goals, biochar has gained significant attention due to its stable carbon sequestration capabilities and environmental benefits. This research employs bibliometric tools such as VOSviewer 1.6.16, Citespace 6.2 R6, and Scimago Graphica to systematically analyze 2076 publications from the Web of Science Core Collection between 2007 and 2024, aiming to clarify the evolutionary trajectory, research hotspots, and international collaboration patterns of biochar carbon sequestration research while identifying future knowledge gaps for innovation. Research results reveal a three-stage developmental characteristic: 2007–2014 was a slow accumulation period for fundamental mechanism exploration, 2015–2020 was an accelerated expansion period driven by policies like the Paris Agreement, and 2021 to the present marks an exponential growth phase of interdisciplinary integration due to global carbon market consolidation. China and the United States are core producing countries, though inter-institutional deep collaboration remains insufficient. Research hotspots have progressively shifted from early biochar preparation and carbon stability to multiple waste materials (such as rice straw and urban carbon sequestration waste) and co-pyrolysis technologies (significantly emerging since 2022), with machine learning applications in process optimization becoming a nascent direction. The study recommends increasing cross-disciplinary research funding, establishing biochar raw material pollution standards, and promoting coordinated policies that combine biochar carbon sequestration with agricultural efficiency to support global carbon reduction objectives. Notably, the research’s reliance on the Web of Science Core Collection may limit coverage of non-English literature and regional studies. By quantitatively analyzing technological evolution and collaboration networks, this study provides a data-driven framework for optimizing biochar carbon sequestration strategies, helping bridge the gap between laboratory potential and actual climate emission reduction, and offering focused action pathways for policymakers and researchers.

As a critical supplement to unconventional natural gas resources, deep coalbed methane (CBM) requires a comprehensive understanding of reservoir pore structure and adsorption behavior. In this study, medium-rank coals from the Zijinshan area on the eastern margin of the Ordos Basin were analyzed using high-pressure mercury intrusion (HPMI), low-temperature nitrogen adsorption (LT-N2), low-pressure CO2 adsorption (LP-CO2), and scanning electron microscopy (SEM) to characterize full-scale pore size distributions. Results show that the pore system displays a stepwise distribution, with micropores (<2 nm) accounting for 68.77% of total pore volume and 97.76% of specific surface area, making them the primary sites for methane adsorption. Based on multi-scale pore data, Pearson correlation analysis and partial least squares regression (PLSR) were employed to determine the dominant controls on adsorption capacity. Total pore volume, micropores and mesopores structures, volatile matter, and fixed carbon were identified as major influencing factors. Fixed carbon enhances micropores development, while volatile matter contributes to the formation of pyrolysis-related pores and improved pore connectivity. Moreover, the high-temperature and high-pressure conditions typical of deep coal seams accelerate thermal evolution and compaction, further promoting the prevalence of micropores. These findings suggest that methane adsorption in deep coal reservoirs is controlled by the coupled effects of geological conditions, organic matter composition, and pore structure. This work provides insights into the nonlinear relationship between multi-scale pore systems and adsorption behavior, supporting efficient CBM exploitation under the dual-carbon strategy.

Hydraulic fracturing can significantly enhance coalbed methane production, with in-situ stress playing a crucial role in this process. Our study focuses on calculating in-situ stress in the deep 8+9# coal seam in the north-central Zijinshan block. Leveraging data from acoustic logging and hydraulic fracturing tests, we developed a stress prediction model tailored to the area’s geology. We analyzed stress’s impact on fracturing behavior and the origins of mechanical anisotropy in deep coal reservoirs using μ-CT imaging. Our results show that the Anderson-modified model, accounting for transverse isotropy, offers greater accuracy and applicability than traditional models. The study area exhibits a normal faulting stress regime with significant stress contrasts and maximum horizontal principal stress aligned with the east-west geological stress direction. After hydraulic fracturing, fractures form a complex fracture system resembling elongated ellipses in the coal reservoir, primarily extending in the vertical direction. To control fracture height and prevent penetration through the roof and floor, regulatory measures are essential. μ-CT analysis revealed the distribution of primary fractures, pores, and minerals in the coal, contributing to mechanical anisotropy. This research advances CBM development in the Zijinshan block and similar regions by refining stress prediction and fracturing propagation methods.

The Zhengzhuang Block in the Qinshui Basin is one of the important coalbed methane (CBM) development areas in China. As high-quality CBM resources become depleted, remaining reserves exhibit complex geological characteristics requiring advanced development strategies. In this study, a multidisciplinary workflow integrating 3D geological modeling (94.85 km² seismic data, 973 wells), geomechanical stress analysis, and production simulation was developed to optimize development of the Permian No. 3 coal seam. Structural architecture and reservoir heterogeneity were characterized through Petrel-based modeling, while finite-element analysis identified stress anisotropy with favorable stimulation zones concentrated in southwestern sectors. Computer Modeling Group (CMG) simulations of a 27-well group revealed a rapid initial pressure decline followed by a stabilization phase. A weighted multi-criteria evaluation framework classified resources into three tiers: type I (southwestern sector: 28–33.5 m³/t residual gas content, 0.8–1.0 mD permeability, 8–12% porosity), type II (northern/central: 20–26 m³/t residual gas content, 0.5–0.6 mD permeability, 5–8% porosity), and type III (<20 m³/t residual gas content, <0.4 mD permeability, <4% porosity). The integrated methodology provides a technical foundation for optimizing well patterns, enhancing hydraulic fracturing efficacy, and improving residual gas recovery in heterogeneous CBM reservoirs.