Logistic regression-based automatic lithological naming method

Abstract

The invention discloses a logistic regression-based automatic lithological naming method. The method comprises the following steps that: 1) the mineral component percentage data of the rock sample of a to-be-named stratum are obtained, the structural characteristics of granularity, rounding and cement components are observed by naked eyes; 2) rock sample data with thin section authentication and naming conclusions are collected as a training set; 3) with the to-be-named stratum adopted as a test set, a thin section authentication conclusion as a dependent variable, granularity, rounding and cement components as factors, and the mineral component percentage content as a concomitant variable, unordered multi-classification logic regression is carried out, logic regression models of various lithological properties are established; 4) the mineral component percentage, granularity, rounding and cement component data of the to-be-named stratum are substituted into logic regression models; and 5) lithological naming is performed for the to-be-named stratum according to a maximum membership principle. With the method disclosed by the invention adopted, naming results are more scientific and objective; the problem that qualitative data such as structures cannot participate in quantitative calculation is solved; and requirements for on-site rapid naming while drilling can be met.

Description

technical field [0001] The invention relates to the field of petroleum exploration and development, in particular to a method for naming lithology in the field of mud logging technology in the process of petroleum exploration and development, in particular to an automatic lithology naming method based on logistic regression. Background technique [0002] Lithology naming is the basic work of mud logging, which plays an important role in later reservoir evaluation. At present, the methods of mud logging lithology naming mainly include ① naked eye observation; ② thin section identification; ③ X-diffraction whole-rock analysis. The current lithology naming method has the following deficiencies: [0003] 1. Inner eye observation is the first-hand information on site, but it has high requirements for naming personnel, and the method is simple, which cannot meet the needs of fine naming; [0004] 2. Observation and naming under the microscope are accurate, the process is complex,...

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Problems solved by technology

[0003] 1. Inner eye observation is the first-hand information on site, but it has high requirements for naming personnel, and the method is simple, which cannot meet the needs of fine naming;

[0004] 2. Observation and naming under the microscope are accurate, the process is complicated, the requirements for personnel and equipment are high, and the identification period is long, which is not suitable for the field and cannot meet the needs of the field naming while drilling

[0005] 3. Through X-diffraction whole-rock analysis, the mineral composition of the rock can be obtained for naming. Currently, methods for naming mineral composition include curve intersection method, plate analysis method, etc. These methods use fewer mineral types and low dimensional utilization. Not suitable for high-dimensional mineral analysis, and no reference to factors such as mineral structure when naming

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