Characterizing Shale Brittleness and Organic Enrichment Through Matrix Modulus Using Rock Physics-Based Elastic Impedance Inversion

Deep shale gas, as a crucial unconventional energy resource, is assuming an increasingly significant role in securing energy supply and advancing the global shift toward low-carbon development. Nevertheless, deep shale reservoirs are typically characterized by pronounced heterogeneity, complex mineralogical composition, and significant organic enrichment, which make the simultaneous seismic-scale characterization of brittleness and organic matter particularly challenging. To overcome these difficulties, we present a rock physics–driven inversion framework that incorporates two diagnostic parameters: the matrix bulk modulus (Km) and the disturbance bulk modulus (ΔK).Kmcharacterizes the inherent stiffness of the mineral matrix and demonstrates strong sensitivity to brittle mineral abundance, whereas ΔKcaptures the softening impact of organic matter on rock rigidity, thereby offering improved sensitivity to organic enrichment. By combining these two parameters, the respective influences of minerals and organic matter can be effectively disentangled at the seismic scale. Building upon this concept, we derive a new reflection coefficient expression formulated in terms of the matrix modulus and establish an elastic impedance inversion scheme. This framework enables the concurrent prediction of shale brittleness and organic enrichment from seismic observations. Rock physics analysis confirms thatKmis highly sensitive to brittle mineral content, while ΔKexhibits a relative increase of up to 300% with rising organic matter fraction, significantly exceeding the response of conventional density (~20%) and P-wave impedance (~40%). Synthetic tests show over 95% consistency between the proposed reflectivity and the exact Zoeppritz solution within 30° incidence. Well-log validation yields correlation coefficients of 0.77 betweenKmand mineral brittleness index, and 0.81 between ΔKand organic matter content, both outperforming conventional elastic indicators. Field applications demonstrate that the method achieves higher prediction accuracy, better vertical resolution, and improved lateral continuity compared to existing techniques. Beyond shale gas, this methodology offers a broadly applicable framework for characterizing unconventional reservoirs, including shale oil, oil shale, tight hydrocarbons, and gas hydrates, highlighting its relevance for future energy exploration and development.