Research on Lithology Identification Method Based on PSO-BP
In recent years,data analysis and deep learning technology have made great progress and brought considerable ben-efits to the society.Therefore,the use of deep learning method for lithology identification has become a research hotspot.Lithology identification is the core business of logging interpretation,accurate and effective prediction of reservoir properties is of great signifi-cance to petroleum exploration.However,the traditional lithology identification scheme has some disadvantages,such as high cost,long time and so on.Therefore,this paper uses the logging data of some wells in Songliao basin to study the model,after comparing the lithology identification results of different algorithms,a lithology identification method based on PSO-BP is proposed.Through data preprocessing of logging source data,construction of network identification model,optimization of lithology identification mod-el and evaluation of model output,the lithology identification method based on PSO-BP is realized.After repeated tests,the results show that the average accuracy of lithology identification using PSO-BP method can reach 92.2%,which provides a reliable support for reservoir prediction.
BP neural networkPSOlithology identificationdata preparationKNNSVM
国家科技期刊平台
NSTL
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