Simulation of Electromagnetic Wave Resistivity Logging While Drilling Based on the Physical-Informed Neural Network - LIU Yang; WANG Jian; XU Delong (Cejing jishu)
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.