Spatial Modeling and Resource Assessment of Wufeng–Longmaxi Black Shales in the Sichuan Basin and Its Periphery

The Wufeng and Longmaxi black shales, deposited during the Ordovician-Silurian transition, are widely distributed throughout the Sichuan Basin and its peripheral regions. These two stratigraphic units are characterized by their stratigraphic continuity, abundant fossil records, and high organic matter content. They not only provide a comprehensive archive of major geological events-including climatic shifts, biological evolution, and environmental changes associated with the Hirnantian glaciation, but also serve as the primary target layers for current marine shale gas exploration and development in China. Consequently, clarifying the spatiotemporal distribution patterns and evolutionary history of the Wufeng-Longmaxi black shales within the basin and its surrounding areas holds significant scientific and practical significance. Based on comprehensive stratigraphic information (including location, depth, lithology, biozones, thickness, and contact relationships) from hundreds of outcrop sections and boreholes, combined with seismic and well-logging data, this study employed GIS software and selected appropriate interpolation methods to reconstruct the present-day three-dimensional spatial distribution of the two black shale units, and quantitatively calculated their geographic distribution parameters such as area and volume. Building upon these models, and in conjunction with paleogeographic reconstructions of the depositional settings, we have performed continuous dynamic simulations to deconstruct the temporal architecture of high TOC intervals and analyze the developmental patterns of thickness distribution, thereby resolving the sedimentary processes and controlling factors. Furthermore, we have systematically compiled key petroleum geological parameters, including TOC content, thermal maturity, porosity, permeability, brittle mineral fractions to construct three-dimensional, multi-attribute spatial distribution models of these core shale gas reservoir properties. These models enable the analysis of spatial distribution patterns and inter-parameter relationships. Finally, by integrating high-resolution, quantitatively constrained spatial models of the black shales with the hydrocarbon-parameter attribute models related to shale gas productivity, we conduct a multi-parameter coupled analysis. Combined with quantitative sweet-spot evaluation criteria, potential zones favorable for shale gas production were identified.