测井技术2023，Vol.47Issue(6)：653-661,9.DOI:10.16489/j.issn.1004-1338.2023.06.002
基于物理信息神经网络的随钻电磁波电阻率测井响应模拟
Simulation of Electromagnetic Wave Resistivity Logging While Drilling Based on the Physical-Informed Neural Network
摘要
Abstract
In order to simulate the response of electromagnetic wave resistivity logging while drilling efficiently in complex media and accelerate the inversion of logging data,the physical-informed neural network(PINN)is used to simulate the response of electromagnetic wave resistivity logging while drilling.PINN incorporates the governing equation into the loss function and transforms the problem of solving partial differential equation into optimization problem.PINN realizes the solution of partial differential equation.In numerical examples,the scattered field is obtained by PINN method.The influence of sampling method,activation function and network architecture on the accuracy of PINN results are studied.The PINN method is used to calculate the response of electromagnetic wave resistivity logging while drilling in high resistivity and intrusive formation models.The numerical results show that the response of electromagnetic wave logging while drilling based on PINN simulation is consistent with the finite element results.This method can be used to accurately solve the response of electromagnetic wave resistivity logging while drilling.关键词
物理信息神经网络/随钻电磁波电阻率测井/测井响应/电磁场模拟Key words
physics-informed neural network/electromagnetic wave resistivity logging while drilling/logging response/electromagnetic field simulation引用本文复制引用
刘阳,王健,徐德龙..基于物理信息神经网络的随钻电磁波电阻率测井响应模拟[J].测井技术,2023,47(6):653-661,9.基金项目
国家自然科学基金面上项目"内嵌物理知识的深度神经网络电阻率三维反演研究"(42274177) （42274177）
国家自然科学基金项目"基于异常电磁扩散理论的感应测井裂缝密度评价研究"(41604123) （41604123）
