Abstract
One important factor influencing the gas/water two-phase seepage during coalbed methane extraction is the absolute permeability of coal reservoirs. The sensible design of a surface coalbed methane drainage system and the enhancement of drainage efficiency depend heavily on the quick and precise prediction of this parameter. The Huanglong Jurassic No. 4 coal seam sample from the Dafosi Coal Mine in the Binchang Mining Area serves as the research object for this study, which employs low-field nuclear magnetic resonance (LF-NMR) technology and high-temperature and high-pressure displacement equipment. The LF-NMR technique was employed to test coal reserves under thermal-mechanical coupling conditions. In conjunction with fractal theory, the association between the absolute permeability and the fractal dimension of coal reservoirs was examined, as well as the dynamic evolution features of the fractal dimension of the pore structure of coal reservoirs under thermal coupling settings. The fractal dimension of the pore structure was used to create a permeability prediction model. According to the study, the fractal map of the coal reservoir's pore structure in its initial form contains clear inflection points that allow one to differentiate between the almost straight and curved segments. The fractal dimension D(1) of the bound pore segment is linearly negatively correlated with the absolute permeability. By contrast, the D(2) of the connected pore segment is exponentially negatively correlated with the absolute permeability. By identifying the inflection points in the diagram, T(2cut-off) can be rapidly ascertained to avoid the centrifugation test operation process. The absolute permeability prediction model based on the fractal dimension of the pore structure determined in this work may significantly streamline the experimental procedures while maintaining the accuracy of the prediction findings compared to the conventional NMR absolute permeability model. With just the NMR T(2) spectrum of the saturated sample, the model can determine its absolute permeability in real-time.