Optimization and Application of Organic Carbon Logging Prediction Models for Source Rocks:A Case Study of Chang 9 Member of Yanchang Formation in Ansai Area,Ordos Basin
Total organic carbon(TOC)mass fraction is an important index of source rocks evaluation.In order to evaluate the organic carbon of source rocks in Chang 9 Member of Yanchang Formation in Ansai area,southeast Ordos basin,firstly,this article establishes w(TOC)models for quantitative prediction of well logging by applying the multiple regression model,the traditional △log R model,the improved △log R model and the generalized △log R model,based on core analysis of measured w(TOC)data and the response characteristics of source rocks to different logging curves.Secondly,by analyzing and combining these models,the fitting superposition coefficient extracted from the improved △log R model is applied to the calculation of two generalized △log R models,and the application effect is good.Finally,the four models are compared and optimized,and the most suitable quantitative prediction model for source rocks in the study area is proposed.The results show that the generalized △log R model considering the density factor has the highest accuracy,with an average relative error of 7.78％;The multiple regression model has the second highest accuracy,with an average relative error of 9.65％.Both of them can meet the accuracy requirements of quantitative prediction of w(TOC).
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