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Coal Geology & Exploration

Authors

LI Quangui, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, ChinaFollow
PENG Shuyue, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China
LIANG Yunpei, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, ChinaFollow
LI Wenxi, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China; College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China
QIAN Yanan, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China; School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
CHENG Chunhui, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China
YU Changjun, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China
ZHAN Jinfei, State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China; School of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China

Abstract

Background Microseismic monitoring, a non-destructive monitoring technique, has been extensively applied in the hydraulic fracturing performance assessment of coal seams. However, little attention is paid to the vertical wave velocity gradients in media in the same layer during the construction of layered wave velocity models. This leads to limited precision of travel time calculation and microseismic source localization, thus affecting the assessment accuracy of the hydraulic fracturing of coal seams. Objective and Methods Based on the coal seam segmented hydraulic fracturing project in a mine in Anhui, this study proposes an improved velocity model based on the Universal Kriging interpolation method. By incorporating anisotropy factors, the velocity values in the grid cells of the same layer are interpolated on the basis of the sonic logging velocity model, to characterize the anisotropic features, which are then used to correct the elastic wave propagation path. The effectiveness of the improved velocity model is validated by comparing the source location accuracy of known perforation events. Based on this model, further calculations of reservoir permeability and Stimulated Reservoir Volume (SRV) were performed, achieving a comprehensive evaluation of the coal seam hydraulic fracturing effect.Results and Conclusions The results indicate that compared to the linear interpolation method, the universal Kriging interpolation method effectively enhanced the microseismic source localization accuracy. For the same perfo-ration point, the localization errors yielded by the improved wave velocity model decreased by up to 7.22 m compared to those of the initial layered wave velocity model. The hydraulic fracturing performance assessment reveals that the microseismic source localization accuracy after wave velocity interpolation was improved and that the vertical discreteness of microseismic events was effectively restricted, with the effective influence radius of various fracturing segments determined at about 90 m. The distribution density of microseismic events and the permeability varied across the coal seam area, with high post-fracturing permeability observed near the wellbore of various fracturing segments. The SRVs in horizontal well No.1 totaled 1.977 × 107 m3, and the SRV and hydraulic fracture length were positively correlated with the total volume of injected fluids. Overall, the hydraulic fracturing performance based on microseismic assessment aligns with the expectation.

Keywords

hydraulic fracturing, microseismic monitoring, anisotropy, universal Kriging interpolation method, wave velocity model, grid search

DOI

10.12363/issn.1001-1986.25.01.0053

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