Fine Prediction and Characterization of Lithology-Reservoir-Fluid in Southeastern Margin Slope Belt of the Pre-Caspian Basin

As the exploration target is shifted to the eastern slope belt of the southeast depression zone in the Pre-Caspian Basin, the sub-salt structural-lithologic reservoirs of carbonate beach facies under the slope structure background are characterized by complex and diverse lithology, thin reservoir thickness and rapid lateral variation, which brings great challenges to prediction and description of lithology, reservoir and fluid distribution, restricting subsequent reserve replacement and exploration benefits. In this paper, on the basis of lithology identification with core and well logging data, the pre-stack and post-stack seismic joint inversion by logging constraint is carried out. The post-stack p-wave impedance inversion results are used as the initial model of pre-stack p-wave impedance inversion, and neural network inversion is applied to improve the resolution of pre-stack inversion results. Based on the rock physics theory, the seismic petrophysical elastic parameters for differentiating mudstone (mud-bearing limestone) and limestone are studied and obtained, and the identification factor of mudstone with multiple sensitive elastic parameters combination is constructed. After eliminating the lithology effect of mudstone, sensitive elastic parameters are furtherly compared to differentiate tight limestone and porous limestone (porosity > 4%), and fine prediction of thin and porous limestone reservoir is carried out. Finally, the correlation between elastic parameters and logging porosity and the fluid factor of coordinate rotation change are used to achieve fine logging porosity and the fluid factor of coordinate rotation change are used to achieve fine description of reservoir porosity volume and prediction of oil and gas content. Therefore, a set of carbonate rock fine prediction technique by lithology-reservoir-fluid three-stage approaching target is developed. The results show that the identification factor of mudstone based on combined computation of multiple sensitive elastic parameters lays a foundation for thin reservoir and fluid prediction, and the lithology prediction results obviously avoid the unreliability of lithology prediction by single sensitive elastic parameter. The high-resolution pre-stack seismic inversion technique by logging data constraint is established, which improves the prediction accuracy of thin carbonate reservoirs. Application of techniques from this paper provides direct guidance for well deployment in this area, and the high-yield oil flow are obtained proved with well testing results. The prediction and characterization technique of lithology-reservoir-fluid three-stage approaching target provides references for studies in similar areas.