Pore Structure Characterisation and Permeability Prediction of Coal Samples Based on CT Digital Core and Fractal Theory

Abstract

The pore structure and connectivity of coal directly control fluid storage and migration and provide an important basis for evaluating coal-seam permeability and gas-drainage performance. To quantitatively characterise the pore structure of anthracite and improve the accuracy of permeability prediction, anthracite from the Sihe Mine in Jincheng was investigated using porosity–permeability testing, CT scanning and digital-core reconstruction. Image filtering, threshold segmentation and black-hat compensation were used to extract the pore phase. The minimum REV was determined from porosity stability, and the connected pore network was extracted using the maximal ball algorithm. The box-counting dimension and a fractal permeability model were then applied to predict permeability. The average porosity and permeability of the coal samples were 1.8769% and 0.17708 μm2, respectively. The total CT porosity was 2.7128%, and the connected porosity of the REV was 1.358%. The fractal-model prediction was 0.1894 μm2 and the Stokes simulation result was 0.186436 μm2; both were close to the experimental values. The results provide a reference for quantitative pore-structure characterisation and permeability prediction of coal samples.