Advanced Methods of Joint Inversion of Multiphysics Data for Mineral Exploration

Abstract

Different geophysical methods provide information about various physical properties of rock formations and mineralization. In many cases, this information is mutually complementary. At the same time, inversion of the data for a particular survey is subject to considerable uncertainty and ambiguity as to causative body geometry and intrinsic physical property contrast. One productive approach to reducing uncertainty is to jointly invert several types of data. Non-uniqueness can also be reduced by incorporating additional information derived from available geological and/or geophysical data in the survey area to reduce the searching space for the solution. This additional information can be incorporated in the form of a joint inversion of multiphysics data. This paper presents an overview of the main ideas and principles of novel methods of joint inversion, developed over the last decade, which do not require a priori knowledge about specific empirical or statistical relationships between the different model parameters and/or their attributes. These approaches are designated as follows: (1) Gramian constraints; (2) Gramian-based structural constraints; (3) localized Gramian constraints; and (4) joint focusing constraints. We provide a short description of the mathematical foundations of each of these approaches and discuss the practical aspects of their applications in mineral exploration.

Joint Three-Dimensional Inversion of Gravity and Magnetic Data Collected in the Area of Victoria Mine, Nevada, Using the Gramian Constraints

“…When performing a joint inversion of gravity and magnetic field data, the parametric functional (2) needs adjustment to encompass both gravity and magnetic misfit functionals. Additionally, a Gramian stabilizer is integrated to promote interaction between the density and magnetic inverse models [24]:…”

“…The Gramian stabilizer ensures a correlation between the density and magnetization inverse models, thereby guaranteeing geological consistency across both models [23,24].…”

Probabilistic approach to Gramian inversion of multiphysics data

“…This will result in the shared Earth model characterized by similar behavior of the gradients of different physical properties. In this case, Gramian constraint, similarly to the cross-gradient method (Gallardo and Meju, 2003, 2004, 2007Gallardo, 2007), enforces the structural similarity between different physical inverse models (Zhdanov et al, 2021). We can also use various functions of the model parameters, e.g., logarithms or trigonometric functions, to enforce the correlation between the transformed parameters.…”

Special Issue: Advancement of Functionalized Mineral Materials and Rock

“…Functionalizing mineral materials is crucial for meeting application needs and exploring new markets or applications in response to evolving industrial and societal demands. Therefore, it is crucial to take proactive measures in utilising effective mineral substances for energy conservation, fire prevention, filling and coating, environmental protection, energy storage, heat preservation, and other related applications [1][2][3][4][5].…”