Research on identification model of element logging shale formation based on IPSO-SVM

作     者：He Zhang Yu'nan Li 

作者机构：School of Mechatronic EngineeringSouthwest Petroleum UniversityChengdu610500China 

出 版 物：《Petroleum》 (油气（英文）)

年 卷 期：2022年第8卷第2期

页      面：185-191页

核心收录：

学科分类：081803[工学-地质工程] 08[工学] 0818[工学-地质资源与地质工程] 

主　　题：Element logging Particle swarm optimization Geo-steering SVM Shale 

摘      要：In the process of shale gas drilling,geo-steering plays an important role in shale gas *** paper analyzes the constituent elements of shale formation,and selects the most suitable constituent elements of shale formation.A particle swarm optimization algorithm based on improved inertia weight and acceleration factor is proposed to optimize the parameters of support vector *** lithology identification model of shale formation is established based on *** to the experimental analysis based on the field historical data,the recognition rate of IPSO-SVM is increased by 17.79%,10.17%and 8.05%,respectively,compared with SVM,GA-PSO and *** terms of running time,the running time of IPSO-SVM is 13.76s and 9.5s shorter than that of GA-PSO,PSO-SVM,*** comparing the experimental results of different models,IPSO-SVM has the advantages of strong robustness,strong reliability,high accuracy and fast convergence *** provides a theoretical basis for precise geo-steering and finding the optimal shale layer.