测井技术2024，Vol.48Issue(4)：438-452,15.DOI:10.16489/j.issn.1004-1338.2024.04.004
基于PCA-BP神经网络的TOC测井评价方法研究
Research on TOC Log Evaluation Method Based on PCA-BP Neural Network
摘要
Abstract
The organic carbon content is the main parameter to evaluate the potential of hydrocarbon source rocks.The commonly used TOC logging inversion model is difficult to deeply analyze the complex collinearity relationship between logging curves,which restricts the comprehensive evaluation effect of multi-dimensional logging information.An intelligent prediction method of organic carbon content based on principal component analysis and back propagation(PCA-BP)neural network is established,based on the pyrolysis experimental results and conventional logging curves of Triassic Baijiantan formation mudstone in Mahu sag.The method is based on the weighted average of sensitive logging curves and TOC test results as the original data set.Firstly,the variance inflation factor is used to detect the collinearity between the logging curves.Then,the principal component analysis(PCA)technology is used to decollinearity and reduce the dimension of the original data set,and two principal components are determined.Finally,combined with neutron,gamma ray,density and acoustic logging curve values,a three-layer back propagation(BP)neural network prediction model with six input nodes is established to evaluate the source rock potential of the Triassic Baijiantan formation in the study area.The prediction results of the cumulative 410 m section of three coring wells show that the determination coefficient of the model is as high as 0.879,the average absolute error and mean square error of the prediction results are 0.220 and 0.107,respectively,and the mean relative deviation is 16.1%.The research results provide a reliable reference for the optimization of exploration domain in Junggar basin.关键词
PCA-BP神经网络/有机碳含量/测井评价/降维/去共线性Key words
PCA-BP neural network/organic carbon content/log evaluation/reduction dimension/decollinearity分类
天文与地球科学引用本文复制引用
尚亚洲,许多年,张兆辉,刘建宇,赵雯雯..基于PCA-BP神经网络的TOC测井评价方法研究[J].测井技术,2024,48(4):438-452,15.基金项目
新疆维吾尔自治区"天池英才"计划"基于沉积-成岩补偿评价的致密砂岩储层甜点预测"(51052300560) （51052300560）
甘肃省油气资源研究重点实验室开放基金"致密砂岩全尺度岩石相数字建模及其地震响应分析"(SZDKFJJ2023007) （SZDKFJJ2023007）
新疆大学博士"启动基金"项目"基于沉积构造相表征识别的页岩有效储层评价预测方法"(620322016) （620322016）
