Coal structure identification method based on three-terminal tuple chart in complex structure area - Jianghai ZOU; Gang XIANG; Yinlan FU; Yongyu YANG; Hengyi ZHAO; Jian ZHENG (Meikuang Anquan)
The coalbed methane resources in Guizhou Province are extremely abundant and are mainly present in the coal seams of Longtan Formation of the Upper Permian. Different coal body structures are significant influencing factors for parameters such as the permeability, porosity, compressibility, and gas content of coal reservoirs. Meanwhile, they are closely related to the layer selection for fracturing operations and the magnitude of gas production in the later stage. Therefore, as the continuously deepening exploration and development of coalbed methane in Guizhou Province, the quantitative identification of coal body structures has received increasing attention. To address the difficulty in identifying coal body structures in conventional drainage and production wells, based on the logging response characteristics of different coal body structures, this study proposes a quantitative identification method of coal body structure based on three-terminal tuple chart and establishes a three-terminal tuple identification chart for the coal body structure in the study area. The research results indicate that with the intensification of the fragmentation degree, the primary structural coal, fractured coal, and tectonic coal generally exhibit a sequential decrease in compensated density and resistivity, and a gradual increase in compensated acoustic wave, compensated neutron, and natural gamma, etc. When the logging curve data of compensated density, resistivity, and natural gamma are selected as the three-terminal points of the three-terminal tuple chart, different coal body structure types are well distinguished on the three-terminal tuple chart. Moreover, comparing with the identification results of core and imaging logging, it is demonstrated that the three-terminal tuple chart can effectively enhance the accuracy of coal body structure identification.