Abstract
Roof-coal recovery rate and the performance of gas extraction are essentially controlled by the fractures within coal-rock mass. Thus, it is important to generate the accurate fracture network ahead of mining face. In this study, ten boreholes located differently from the 8212 working face of Tashan Mine in Datong coal mining group, China, were drilled. With the help of borehole video instruments, the location, orientation of each fracture and the fracture number of different intersection type on each borehole wall were mapped with the advancing of mining face. These data were analyzed using the Matlab Toolbox RJNS3D and Dips to determine structural homogeneity zone, to find the number of fracture sets that exist in the coal-rock mass, volume density frequency for each set and the probability distributions of orientation, fracture size in 3-D. Sampling biases associated with orientation, spacing were corrected during the process. The constructed fracture networks were validated by comparing the observed mean spacing along normal vector of mean orientation for each set and the predict value on similar scanlines.
Wencheng Jin
Assistant Professor of Petroleum Engineering
My research interests include novel rock breakage and fracture for subsurface resource recovery, data-driven and physics-based multiphysics modeling in porous and fractured media, and granular material flow characterization and modeling. My research provides solutions for energy/minerals recovery & storage, material handling, and GeoHazards prediction.