| Abstract |
The shale oil of the Qingshankou formation in the Songliao Basin of China has become an important replacement for conventional resources, the lacustrine shale of Qingshankou Formation is formed in the outer delta front and semi-deep-lake sedimentary system, which mainly develops a pure matrix shale with laminar type with high clay content. The preliminary exploration results show that TOC content is the core parameter of shale oil enrichment and high production, and Poisson's ratio is the core sensitive elastic parameter of shale oil brittleness evaluation. However, conventional seismic inversion method for the spatial distribution prediction of shale oil enrichment parameters is challenging due to their heterogeneity and anisotropy. In this paper, a nonlinear global optimization pre-stack waveform inversion method of genetic algorithm (GA) which is based on the concepts of nature selection and the survival of the fittest is carried out. The advantage of the inversion method is that the input data is the full wave field information, so without transmission compensation and multi-wave conversion wave removal, good inversion results can still be obtained, and the interference of the thin interlayer complex response to the overlay interface can be effectively eliminated, and the continuity and accuracy of the inversion results are higher. By optimizing initial modeling and more refined processing of CRP gather, the resolution and precision of subsurface properties P-wave and S-wave velocites, density (ρ) are effectively improved. Based on the established relationship of petrophysical, Poisson's ratio and TOC content are further predicted, and the quantitative evaluation of shale oil geological desserts is realized. |
, Subhashis Mallick 
