Integrated Geological-Engineering Logging Evaluation and Application of "Six Properties" for Deep Coalbed Methane Reservoirs

To address the high temperature and pressure, strong heterogeneity, complex pore-fracture system, and significant in-situ stress constraints of deep coalbed methane reservoirs, this study establishes a geological-engineering collaborative evaluation framework based on six properties: lithology, hydrocarbon generation potential, petrophysical properties, gas-bearing property, fracability, and stress characteristics. The results show that lithology is characterized by low natural gamma, low density, high neutron response, high acoustic slowness, and relatively high resistivity. Hydrocarbon generation potential can be jointly characterized by elemental logging, density, acoustic, and resistivity logs. Petrophysical properties are controlled by pore-fracture structure and can be identified using density, acoustic, nuclear magnetic resonance, electrical imaging, and resistivity logs. Gas-bearing property is indicated by high resistivity, neutron-density anomaly, and nuclear magnetic resonance response differences. Fracability is constrained by array acoustic, density, and elemental logs, while stress characteristics are evaluated using array acoustic, electrical imaging, and density logs.Based on these understandings, a logging evaluation volume model composed of organic macerals, inorganic minerals, and pore fluids is constructed. Methods are developed for lithology identification, hydrocarbon generation evaluation, porosity and permeability calculation, adsorbed gas and free gas prediction, fracability characterization, and in-situ stress evaluation. Electrical responses are jointly controlled by lithologic composition, hydrocarbon generation evolution, pore-fracture structure, gas-bearing state, fracability, and stress conditions, showing strong comprehensiveness and non-uniqueness. Integrated application of electrical, density, acoustic, nuclear magnetic resonance, elemental, and imaging logs can reduce single-parameter interpretation uncertainty and improve the accuracy of key "six-properties" parameters. Application in the Daji Block shows that high-quality reservoirs are characterized by low ash content, high vitrinite content, relatively intact coal structure, large coal thickness, high gas content, effective pore-fracture systems, favorable fracability, and moderate stress difference, with high-resistivity and high-slowness logging responses. This method provides support for sweet spot prediction, horizontal well deployment, and fracturing interval optimization.