Shale reservoirs provide critical storage space for unconventional oil and gas, yet their frequent vertical facies alternations and complex spatial architectures make it difficult for conventional two-point geostatistical methods to reproduce thin interbedding and reservoir-scale continuity. Multiple-point geostatistics can incorporate structural information through training images (TIs), but practical 3D shale modeling is often hindered by the limited availability of representative 3D TIs. Using the F2 Member in the Qintong Sag, Subei Basin, eastern China, as a case study, we propose a hierarchical 2D-to-3D geological modeling workflow that combines mixed-point geostatistical simulation (MIXSIM) for generating vertical 2D facies sections and a sequential 2D simulation strategy with conditioning data (s2Dcd) for propagating section-based patterns into 3D space under hard well constraints. In the workflow, vertical sections serve as TI carriers to explicitly capture bedding-scale alternations, while well data are imposed as hard conditioning information during 3D simulation. Quantitative evaluation is performed in terms of (i) conditioning-data consistency, (ii) vertical facies-transition statistics quantified by transition counts and Markov transition probability matrices, (iii) global facies proportions summarized as the mean of 10 realizations, and (iv) connectivity characterized by connected geobody analysis. The realizations honor the conditioning data exactly, reproduce vertical transition behavior with a transition-matrix discrepancy of DMAE = 0.0396, and maintain global facies proportions close to well-based estimates with a maximum deviation of 2.36%. These results demonstrate that the proposed MIXSIM–s2Dcd workflow provides a practical solution for well-data-driven, high-resolution 3D shale facies modeling when 3D training images are unavailable.
Han et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: