Deep coalbed methane (CBM) is an important unconventional gas resource following shallow coal seam development, vital for energy supply and security. The deep coal seams in the study area are characterized by low porosity, low permeability, high stress, and strong plasticity, leading to significant differences in fracturing effectiveness and gas production among wells. This highlights the need for sweet spot identification in deep coal seams. This study focuses on developing and evaluating the integrated geological and engineering sweet spots (ESSs) in deep coal-bearing formations. The approach includes constructing brittleness, fracture development, and differential stress indices to characterize the ESSs, while gas content and permeability index (GCPI) represents the geological sweet spots (GSSs). The analytic hierarchy process-technique for order preference by similarity to ideal solution (AHP-TOPSIS) algorithm is then used to combine these indicators, resulting in a comprehensive evaluation of sweet spots and their distribution within the reservoir. The validation of the ESSs and ESS integrated with GSS (ESSIGSS) was conducted using post-fracturing analysis, microseismic monitoring, and gas production. The result of post-fracturing analysis showed a negative correlation trend between the assessment score of ESS (ESS-AS) and pay zone stress (PZS). This suggests that higher ESS-AS are associated with lower fracture propagation difficulty. Microseismic monitoring results from a horizontal well indicate that high ESS-AS values correspond to larger fracture-stimulated volumes. Additionally, an evaluation index—gas production index of ESSIGSS (ESSIGSS-GPI) that incorporates fracturing fluid and proppant usage is developed, and for the 15 wells analyzed, this index shows a correlation coefficient of 0.66 with the assessment score of ESSIGSS-AS, indicating that wells with higher ESSIGSS-AS scores experience lower operational difficulty in hydraulic fracturing and higher peak production. The study provides a distribution map of sweet spots for development based on the evaluation results, offering valuable insights for optimizing well locations, fracturing designs, and the coproduction of CBM and tight gas in deep coal seams.

Keywords:
sedimentary rock, clastic rock, reservoir simulation, organic-rich rock, wellbore design, coal seam gas, hydraulic fracturing, coal seam, coalbed methane, completion installation and operations
Subjects:
Artificial intelligence, Coal seam gas, Completion Installation and Operations, Exploration, development, structural geology, Formation Evaluation & Management, Fracturing materials (fluids, proppant), Hydraulic Fracturing, Information Management and Systems, Naturally-fractured reservoirs, Open hole/cased hole log analysis
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