lithofacies division method for the shale based on Fisher discriminant analysis

Abstract

The embodiment of the invention discloses a lithofacies division method for the shale based on Fisher discriminant analysis. According to mineral compositions, a sedimentary structure and organic matter contents, mud rock lithofacies division is carried out to obtain a mud rock lithofacies division class result; a logging identification mode pattern of the mud rock lithofacies is established and awell logging curve class reflecting the lithology of the rock is selected based on the logging identification mode pattern; Fisher discriminant analysis is performed by SPSS software; on the basis ofcore logging data, a mud rock lithofacies class is determined and, the well logging curve reflecting the lithofacies characteristics is selected, and a lithofacies determination classification equation is established; according to a well logging curve of an unknown lithofacies, a function value of the lithofacies discriminant classification equation is obtained; and on the basis of the function value, a mud rock lithofacies division class to which the unknown lithofacies is determined. According to the invention, for the well section being lack of data like the core, logging, and diffractionanalysis, the mud rock lithofacies can be divided in details by using the lithofacies determination equation based on the well logging data, thereby improving the division precision and promoting theoil exploration.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of oil and gas exploration, and in particular to a method for shale lithofacies division based on Fisher discriminant analysis. Background technique [0002] With the development of the petroleum industry, the focus of oil and gas exploration has gradually shifted to unconventional oil and gas reservoirs, and the exploration and development of fine-grained deposits is one of the current hot issues. At present, scholars at home and abroad have carried out many studies on fine-grained sediments, mainly focusing on petrological characteristics, reservoir characteristics, genetic types, lithofacies division, and sequence division, to clarify the mineral composition and structural characteristics of fine-grained sedimentary rocks, and to identify effective reservoirs. According to the type of set space, establishing the relationship between the trace element chemical characteristics of d...

AI Technical Summary

Problems solved by technology

At present, the lithofacies classification based on well logging data is mainly for sandstone. Due to the high degree of differentiation of different grain sizes of sandstone, it is relatively easy. However, due to the fine grain size of mudstone, it is difficult to further subdivide lithofacies.

Images