Pathways and challenges of the application of geophysical techniques to multifaceted coalbed methane reservoir characterization

Revealing the distribution patterns of coal reservoir parameters is essential for evaluating the resource potential and guiding the production activities of coalbed methane (CBM). Although direct methods such as sample testing, coal core observation, and well testing measurement are effective, they are time consuming, costly, and limited by the sampling locations and data volume. Consequently, the precision of regional-scale reservoir characterization based solely on these methods is often insufficient. Therefore, predictive methods based on geophysical technologies have been developed by establishing correlations between reservoir parameters and geophysical data, using direct measurements as labels. These methods offer significant advantages in terms of efficiency and cost-effectiveness, making them highly promising and practically valuable in the CBM field. This study presents a critical review of these advancements. First, the fundamental principles of seismic and geophysical logging are systematically introduced, along with methods for data preprocessing and analysis. Second, based on the differences in response mechanisms of various geophysical datasets to different reservoir parameters, the application advances of these techniques in assessing coal properties, coal structures, permeability, and fluid characteristics are emphasized. These advancements have contributed significantly to reducing exploration costs and improving development efficiency. However, the highly complex and heterogeneous nature of coal reservoirs weakens the correlation between geophysical data and individual reservoir parameters, and the generalizability existing predictive models remains limited. To overcome these challenges, this paper proposes several key directions for the future development of geophysical technologies in CBM research, including: (1) the development of reservoir evaluation models that integrate geological constraints with algorithmic prediction; (2) the advancement of geophysical theory and the improvement of model generalizability; (3) the establishment of models focused on the spatial distribution characteristics of coal measure reservoir parameters; and (4) the construction of a comprehensive evaluation system that integrates geology, reservoir, and development for CBM.