Joint reconstruction and multi-modality/multi-spectral imaging (or joint geophysical inversion) is of growing importance in a wide range of contemporary issues including cost-effective environmental and groundwater investigations, natural hazard monitoring, carbon dioxide sequestration and efficient prediction and extraction of fossil and renewable fuels. It is also emerging rapidly in biomedical and materials science imaging. It combines data acquired using different methods (or modalities) to provide more realistic images of the subject under investigation than achievable using an individual modality as now well-known in environmental and energy investigations. Combining observations of multiple physical phenomena on an object of investigation has potential for accurate predictions and hence risk reduction in decision making with data. In the environmental and energy industries, the challenge in this integrated imaging of the subsurface is how to combine large-volumes of correlated data from interrelated physical phenomena or disparate data from unrelated physical phenomena and taking into account the different support volumes of the data (due to the different spatial scales or foot-prints of measurement modalities). In this paper, I describe some important considerations for adequate sampling of subsurface targets and data homogenization (or pre-conditioning), which data sets and physical constraints are most important for the joint image reconstruction process to be successful, uncertainty analysis, and the recent advances in structure-coupled inverse modeling of spatio-temporal multiphysics observations in petroleum and environmental investigations.
Max Meju has over 30 years experience in joint geophysical inversion and electromagnetic (EM) imaging methods. He trained at Imperial College London (MSc,DIC) and University of Edinburgh (PhD). He lectured geophysics at UK Universities (Leicester & Lancaster) for 21 years; worked for Petronas Research (2008-2011) to develop their marine controlled-source EM (CSEM) modelling and interpretation capability; now develops and applies multiphysics imaging for Petronas Upstream operations. He published over 100 innovative scientific papers in international journals (including Nature and AGU journals) and chapters of 7 high-profile reseach textbooks. His classic book (Geophysical Data Analysis: Understanding Inverse Problem Theory and Practice) published in 1994 by Society of Exploration Geophysicists in Tulsa (Oklahoma, USA) is still popular in most undegraduate geophysics programs worldwide. He won the Bullerwell Prize (UK geophysicisit of the year) in UK in 1996,and the international Gerald W. Hohmann Prize in 2002 for research excellence in EM. Max Meju and his research student Luis Gallardo invented in 2003 the cross-gradient structural joint inversion method that is now popular in geophysical and hydrological imaging and is now receiving attention in biomedical and materials science imaging. He starred in a major NATIONAL GEOGRAPHIC TV documentary ‘Volcano Alert’ broadcast worldwide in 2007. He is a member of SEG, EAGE and AGU, a fellow of the Royal Astronomical Society London, member of SEG Council (District 12 representative,2010-2013), and was an associate editor of AGU’s Journal of Geophysical Research (solid Earth, 2005-2016).