Investigating the Recoverability of Density-Susceptibility Relationships from Geophysical Inversions
Abstract
Imaging subsurface based on multiple potential-field datasets has been popular in resource explorations. Interpreting multi-physical datasets generally involves two steps. Different physical property models are first inverted, either separately or jointly, followed a process called geology differentiation where inverted physical property values are classified into distinct classes. The implicit assumption here is that the inverted physical property relationships are reliable. But whether this assumption is generally valid remains unknown. If this is not generally true, when would the recovered physical property relationships become unrecoverable? Moreover, it is well known that the inverted physical property values from standard L2-norm inversions are underestimated. How the underestimation affects the recoverability is unexplored. On the other hand, the sparse norm regularization method has proved to recover models with compact boundaries and elevated values. How the sparse norm inversions influence the recoverability of physical property relationships also needs to be studied. To better understand the recoverability of physical property relationships and to answer these questions, we have designed six geological scenarios, each of which contains three causative geological units at various depths and differs in physical property values. For each scenario, we simulated gravity and magnetic data, performed both smooth L2-norm and mixed L12-norm inversions, both separately and jointly. For each inversion, we analyzed the recovered physical property values and performed geology differentiation. Our work shows that (1) the recoverability of physical property relationships is significantly affected by the depths of the source bodies, and (2) joint sparsity inversion results in the best recoverability consistently in all scenarios. Our work provides a strong motivation for implementing joint sparsity inversion when the goal is to identify different geological units based on potential-field data. We are currently applying the same workflow to the airborne gravity and magnetic data collected over the QUEST project in British Columbia of Canada. Our objective is to identify prospective areas for future mineral exploration under the thick glacial cover.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMNS24A..02L