Surface geometry inversion of transient electromagnetic data

Abstract

We investigate an emerging method called surface geometry inversion (SGI) for the inversion of transient electromagnetic (TEM) data. Conventional minimum-structure inversion methods parameterize the earth model with many mesh cells within which the physical properties are constant, and construct a physical property model that is usually smoothly varying as well as fits the observations. With these smooth models, it is difficult to extract the interface between different geologic units, and it can be especially difficult to target drillholes for thin, plate-like targets, which are frequently encountered in mineral exploration. Our SGI parameterizes the model in terms of the coordinates of the nodes (vertices) used to connect together the surfaces that define the geologic interfaces. The algorithm then inverts for the locations of these nodes, which directly provides geometric information about the target. This can be more useful than a fuzzy image of conductivity, especially for an exploration project. A genetic algorithm (GA) is used to solve the nonlinear, overdetermined optimization problem. We use a finite-element solver to solve the TEM forward-modeling problem of each candidate model in the GA population. Because forward modeling is independent for each model, we implement a hybrid message passing interface (MPI) + OpenMP parallel method to improve computational efficiency. We investigate a new parameterization method specifically designed for thin, plate-like structures, which is more efficient and can effectively avoid self-intersection. We first illustrate the effectiveness of our SGI algorithm on a synthetic block model before testing the new parameterization method on a synthetic thin plate model. Finally, we apply our SGI to a real data set collected for the exploration of thin graphitic faults in a uranium exploration project in Canada. The constructed model from our SGI corresponds well with the drilling data.