Continental Shale Oil Reservoir Lithofacies Identification and Classification with Logging Data—A Case Study from the Bohai Bay Basin, China

Abstract

The development of laminations and mineral composition significantly determine the quality of shale oil reservoirs. The quantitative characterization of lamination development indicators and accurate calculation of mineral composition are key issues in logging evaluation. The Shahejie Formation continental shale oil reservoir in the Nanpu Sag, Bohai Bay Basin, was taken as a case study. Based on electrical imaging logging data, a high-pass filter was designed using the Chebyshev optimal approximation method to extract high-frequency information from the microelectrode curves of the electrical images. A high-resolution quantitative characterization method for millimeter-scale laminated structures of laminae was established, which improved the resolution by 2 to 3 times compared to the static and dynamic image resolutions of electrical imaging. By constructing lamination indices to characterize the sedimentary structural features of reservoirs, we effectively enhanced the fine recognition capability of electrical imaging logging data for sedimentary structures. Utilizing stratigraphic elemental well-log data, we employed an elemental–mineral component conversion model and optimized iterative techniques for accurate mineral composition calculation. We constructed a lithofacies classification scheme based on well-log data using the “rock types + sedimentary structures “approach, combined with research findings on lithofacies identification from well logs, and we identified 12 lithofacies types in the continental shale oil reservoirs of the Nanpu Sag, achieving fine-grained lithofacies logging identification across the entire area. The detailed lithofacies logging classification results were consistent with fine core descriptions.