Two-dimensional inversion of spectral induced polarization data using MPI parallel algorithm in data space

摘要

Traditional two-dimensional (2D) complex resistivity forward modeling is based on Poisson’s equation but spectral induced polarization (SIP) data are the coprod-ucts of the induced polarization (IP) and the electromagnetic induction (EMI) effects. This is especially true under high frequencies, where the EMI effect can exceed the IP effect. 2D inversion that only considers the IP effect reduces the reliability of the inver-sion data. In this paper, we derive differential equations using Maxwell’s equations. With the introduction of the Cole–Cole model, we use thefi nite-element method to conduct 2D SIP forward modeling that considers the EMI and IP effects simultaneously. The data-space Occam method, in which different constraints to the model smoothness and parametric boundaries are introduced, is then used to simultaneously obtain the four parameters of the Cole–Cole model using multi-array electricfi eld data. This approach not only improves the stability of the inversion but also signifi cantly reduces the solution ambiguity. To improve the computational effi ciency, message passing interface program-ming was used to accelerate the 2D SIP forward modeling and inversion. Synthetic da-tasets were tested using both serial and parallel algorithms, and the tests suggest that the proposed parallel algorithm is robust and effi cient.