Organic-rich shale lithofacies geophysical prediction: A case study in the fifth organic-matter-rich interval of Paleogene Hetaoyuan Formation, Biyang Depression

The fifth organic-matter-rich interval (ORI 5) in the He-third Member of the Paleogene Hetaoyuan Formation is believed to be the main exploration target for shale oil in Biyang Depression, eastern China. An important part of successful explorating and producing shale oil is to identify and predict organic-rich shale lithofacies with different reservoir capacities and rock geomechanical properties, which are related to organic matter content and mineral components. In this study, shale lithofacies are defined by core analysis data, well-logging and seismic data, and the spatial-temporal distribution of various lithologies are predicted qualitatively by seismic attribute technology and quantitatively by geostatistical inversion analysis, and the prediction results are confirmed by the logging data and geological background. ORI 5 is present in lacustrine expanding system tract and can be further divided into four parasequence sets based on the analysis of conventional logs, TOC content and wavelet transform. Calcareous shale, dolomitic shale, argillaceous shale, silty shale and muddy siltstone are defined within ORI 5, and can be separated and predicted in regional-scale by root mean square amplitude (RMS) analysis and wave impedance. The results indicate that in the early expansion system tract, dolomitic shale and calcareous shale widely developed in the study area, and argillaceous shale, silty shale, and muddy siltstone only developed in periphery of deep depression. With the lake level rising, argillaceous shale and calcareous shale are well developed, and argillaceous shale interbeded with silty shale or muddy siltstone developed in deep or semi-deep lake. In the late expansion system tract, argillaceous shale is widely deposited in the deepest depression, calcareous shale presented band distribution in the east of the depression. Actual test results indicate that these methods are feasible to predict the spatial distribution of shale lithofacies.