Crustal structure and basement-cover relationship in the Dangerous Grounds, offshore North-West Borneo, from 3D joint CSEM and MT imaging

Abstract

Accurate mapping of crustal thickness variations and the boundary relationships between sedimentary cover rocks and the crystalline basement is very important for heat-flow prediction and petroleum system modeling of a basin. Using legacy industry 3D data sets, we investigated the potential of 3D joint inversion of marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data incorporating resistivity anisotropy to map these parameters across subbasins in the Dangerous Grounds in the southwestern rifted margin of the South China Sea, where limited previous seismic and potential field basement interpretations are available for comparison. We have reconstructed 3D horizontal and vertical resistivity models from the seabed down to >40 km depth for a 35×42 km2 area. The resistivity-versus-depth profile extracted from our 3D joint inversion models satisfactorily matched the resistivity and lithologic well logs at a wildcat exploration well location chosen for model validation. We found that the maximum resistivity gradients in the computed first derivative of the 3D resistivity volumes predict a depth to basement that matches the acoustic basement. The models predict the presence of 2 to approximately 5 km thick electrically conductive (<20 Ωm) sedimentary cover atop an electrically resistive (>100 Ωm) crystalline crust that is underlain by an electrically conductive (<100 Ωm) upper mantle at depths that vary laterally from approximately 25 to 30 km below sea level in our study area. Our resistivity variation with depth is found to be remarkably consistent with the density distribution at Moho depth from recent independent 3D gravity/gradiometry inversion studies in this region. We suggest that 3D joint inversion of CSEM-MT, seismic, and potential field data is the way forward for understanding the deep structure of such rifted margins.

Using Large-Size Three-Dimensional Marine Electromagnetic Data for the Efficient Combined Investigation of Natural Hydrogen and Hydrocarbon Gas Reservoirs: A Geologically Consistent and Process-Oriented Approach with Implications for Carbon Footprint Reduction

“…where d represents the observed MT and/or CSEM amplitude and phase data, f(m v,h ) are the model responses predicted by 3D anisotropic forward theory, W is a weighting matrix whose entries are the inverse variance or covariance of d, and m v and m h are the sought vertical and horizontal resistivity models, respectively. R is the Tikhonov regularization operator, and the pre-multipliers α and β are weights selected by initial trial-and-error testing [17,36]. The third term on the right-hand side is the non-linear crossgradients operator, or structure-promoting regularization [37], where ∇m v and ∇m h are the gradients of the vertical and horizontal resistivity models, respectively.…”

Deep Structure of the Santos Basin, Offshore Brazil From 3D Inversion of magnetotelluric Data

“…Marine magnetotelluric (MT) method is an established tool for offshore resistivity mapping (e.g., Constable & Weiss, 2006;Gallardo et al, 2012;Hoversten et al, 1998Hoversten et al, , 2015Karpiah et al, 2020;Key et al, 2004;Mackie et al, 2020;Saleh et al, 2022;Zhdanov et al, 2011). It is envisaged that resistivity models from threedimensional inversion of MT data may provide important constraints to address the challenges about the mapping of the basement topography, crustal nature, and Moho variation.…”