3D Time-domain electromagnetic full waveform inversion in Debye dispersive medium accelerated by multi-GPU paralleling

Electromagnetic full waveform inversion in Debye dispersive medium (EFWI-D) is a promising technique to reconstruct the inner structure and electrical properties of the medium such as soil, rock and biological tissues. Same as conventional full waveform inversion, EFWI-D requires high computational cost, especially in the 3D case. To reduce the long computation time, we design and implement the EFWI-D algorithm in time domain using multiple GPU cards. The inversion method is based on the L-BFGS optimization algorithm, which can increase the convergence of the misfit function, while the auxiliary differential equation (ADE) method is employed for modeling the Debye dispersive medium by using exponential time differencing (ETD) finite-difference time-domain (FDTD) approach. Moreover, a multi-stream strategy is performed in the workflow to improve the computation performance. Numerical results illustrate the improvement of the computational performance and the preliminarily feasibility of the proposed inversion algorithm. Program summary Program title: 3D Electromagnetic Full Waveform Inversion in Debye Dispersive Medium Based on Multi-GPU Paralleling CPC Library link to program files: https://doi.org/10.17632/mjd9pp5dcm.1 Licensing provisions: LGPL Programming language: C/C++, CUDA Nature of problem: Electromagnetic FWI derives high-resolution distribution of electrical parameters by using additional information provided by the amplitude and phase of the received signals. It goes beyond ray-tracing tomography techniques, which use only the travel time kinematics of the signals. Mathematically, electromagnetic FWI is a kind of conditional extremum problem which is to minimize the difference between observed and modeled waveform of received signals under the condition of Maxwell's equation. Solution method: The basis of inversion is the solution of the forward problem. In this program, the forward simulation is based on Auxiliary Differential Equation (ADE) method. Since the inverse problem is nonlinear, it is solved by using iterative solution which is an optimization method. As it is well known that 3D FWI requires tremendous computation, multi-GPU paralleling is used in this program to accelerate the computing process. Additional comments including Restrictions and Unusual features: The program is mainly designed to solve the inverse problem in Debye dispersive medium, but it also can be used for solving the forward and inverse problem in nondispersive medium by setting the input parameter: poles_of_debye_dispersive_medium(non_dispersive =0,disper sive =1-5 )=0. (C) 2021 Elsevier B.V. All rights reserved.