Method for establishing logging prediction mathematic model about TOC (Total Organic Carbon)

Abstract

The invention relates to a method for establishing a logging prediction mathematic model about TOC (Total Organic Carbon). The method comprises the following steps: (1) obtaining organic carbon data and logging curve data; (2) making a single well comprehensive columnar diagram; (3) carrying out signal well depth location on organic carbon data, and regulating the depth position of an organic carbon sampling point; (4) computing correlated coefficients of each logging curve and the TOC; (5) going to the next step if the TOC and GR have highest correlated coefficients and best correlation, otherwise, failing to establish the logging prediction mathematic model about the TOC; (6) making scatter diagrams of the TOC and the GR, respectively establishing a linear relational expression, a quadratic function expression and an index relational expression of the TOC and the GR; (7) selecting the relational expression with the best correlation between the TOC and the GR, wherein the relational expression is a mathematic model for predicting the TOC of multiple wells in a destination zone in the next stage. According to the method for establishing the logging prediction mathematic model about the TOC, disclosed by the invention, the prediction problem of the TOC in a low-organic matter abundance carbonatite hydrocarbon source rock is simply and effectively solved.

Description

technical field [0001] The invention relates to a method for establishing a mathematical model for well logging prediction, in particular to a method for establishing a mathematical model for well logging prediction of organic carbon content in carbonate rocks with low organic matter. Background technique [0002] At present, for the prediction of organic carbon content (TOC), the prediction models explored by domestic and foreign scholars include qualitative identification model, single-parameter equivalent volume model, double-parameter intersection semi-quantitative model, multiple regression model, and log curve superposition model (ie ΔlogR method), fuzzy mathematical model and other methods. Among them, the most commonly used method is the ΔlogR method. Taking advantage of the characteristics that the higher the organic matter content of source rocks, the greater the acoustic time difference and resistivity, the organic carbon content is calculated by superimposing the...

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Problems solved by technology

[0003] In view of the above problems, the purpose of the present invention is to provide a method for establishing a mathematical model for logging prediction of organic carbon content, which simply and effectively solves the problem of predicting organic carbon content in carbonate source rocks with low organic matter abundance

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