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The second member of the Kongdian formation (Ek   2   ) in the Cangdong Sag of the Bohai Bay Basin is a closed con   tinental lacustrine basin deposit with extensive horizontal distribution and stable vertical distribution, good source rock quality,    and rich shale oil resources. The Ek   2   shale oil reservoir has diverse lithology, which has obvious features of thin inter layering with    fine grained sediments. It has developed very well, and has complex mineral compositions so it is difficult to use conventional    logging data to carry out qualitative lithologic identification and mineral content calculation. In this paper, the main rock types    of shale oil reservoirs in the target block are felsic shale, calcareous shale, mixed shale, and clay stone. These were determined    by comprehensive analysis of geological and core data. By combining core analysis and logging data analysis, the response    characteristics of different rock types on micro resistivity imaging logging and conventional logging data are defined. Optimizing    the deep resistivity, compensation density and compensated sonic logging curves, and proposing a qualitative identification method    for rock types of “   φDT   -   φDEN   &   R   t   /   R   sh   ” cross plot, effectively improved the accuracy of shale oil reservoir lithology identification,    and realized continuous automatic discrimination of rock type classifications. In view of the complicated shale lithology and diverse    mineral composition in the target block, as well as the large difference between the conventional mineral content calculation method    

and the actual situation, according to the X-ray diffraction analysis data of rock samples from the target block, it is determined that    the main minerals of the shale oil reservoir are felsic minerals (quartz and feldspar), carbonate minerals (calcite and dolomite), and    clay. From this, the corresponding mineral volume model is established, using compensated acoustic wave logging, compensation    density, normalized difference between compensation density and compensated neutron logging, deep resistivity, natural gamma and    other sensitive curves. The calculation of the content of carbonate rock and clay minerals is carried out using the method of multiple    stepwise regression, and the calculation accuracy of the content of carbonate rock and clay minerals is significantly improved    through three multiple regressions. On this basis, a logging interpretation model which is suitable for quantitative calculation of    shale oil reservoir mineral content in research blocks is derived. The mineral content calculated by this interpretation model is highly    consistent with the core analysis results. The developed method effectively solves the difficult problem of lithology evaluation of    shale oil reservoirs and improves the accuracy of lithology evaluation using conventional logging data.