In Situ Stress Distribution and Its Control on the Coalbed Methane Reservoir Permeability in Liulin Area, Eastern Ordos Basin, China

Permeability is one of the important factors that affect the production efficiency of coalbed methane, and it is mainly controlled by in situ stress. Therefore, it is very essential to study the in situ stress and permeability for the extraction of coalbed methane. Based on the injection/falloff well test and in situ stress measurement of 35 coalbed methane wells in the Liulin area in the east of the Ordos basin, the correlations between initial reservoir pressure, in situ stress, lateral stress coefficient, permeability, and burial depth were determined. Finally, the distribution characteristics of in situ stress and its influence on permeability were analyzed systematically. The results show that with the increase of burial depth, the initial reservoir pressure and in situ stress both increase, while the lateral stress coefficient decreases. The permeability variation is related to the type of stress field in different burial depths, and its essence is the deformation and destruction of coal pore structures caused by stress. The distribution characteristics of in situ stress at different depths and its effect on permeability are as follows: at depthsσh) and the permeability is a simple decreasing process with the increase of the depth; at depths>800 m, the vertical stress is dominant (σv≥σH>σh). The permeability of most coal is very small due to the large in situ stresses in this depth zone. However, because of the stress release at the syncline axis, coal with high permeability is still possible at this depth zone. Due to the existence of high permeability data points at burial depth (>800 m) and the fitting relationship between permeability and vertical stress, the maximum and minimum horizontal principal stress is poor. However, the coal permeability and lateral stress coefficient show a good negative exponential relationship. This indicates that the lateral stress coefficient can be used to predict permeability better.