Use of structure-guided 3D controlled-source electromagnetic inversion to map karst features in carbonates in offshore northwest Borneo

Abstract

Fractured and/or karstic carbonates (FKC) in the subsurface are commonly associated with significant drilling risk, or reservoir effectiveness issues. Understanding the distribution of karsts will help avoid drilling into possible voids and also re-assess risks associated with reservoir effectiveness. A 2020 3D seismic acquisition in offshore northwest Borneo provided data for identifying new carbonate prospects and an opportunity to revisit a 2010 marine controlled source electromagnetic (CSEM) survey that was not designed specifically for FKC mapping but can serve to test new inversion capability for imaging karsted carbonate bodies. 3D CSEM data was used to detect and characterize the nature (i.e., fractured and/or karsted) of carbonate prospects mapped using 3D seismic data. In one approach, structure-tensors computed from these seismic data were used to constrain the 3D CSEM inversion on the Azure cloud platform. In another approach, cross-gradients between vertical and horizontal resistivities were used as a structural guide obviating the need for seismic data. The resulting anisotropic resistivity models were validated using resistivity logs from a nearby well; the resistivity results matched the well logs satisfactorily, providing geological justification to interpret the presence of karst features in the resistivity volumes. Lateral boundary of the carbonate prospects was mapped based on resistivity characteristic, both in seismic- and non-seismic guided structure-coupled inversion. Resistivity-depth cross-section of the area revealed the presence of resistivity discontinuity at the seismic-inferred boundary of the main carbonate prospect. Also, resistivity depth slices of the models clearly demonstrated that the areal distribution of low and high resistive zones can be mapped and useful deductions such as the presence of FKC and basement characteristics can be made using the 3D inversion of the CSEM data.

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

“…For geological verification, we extracted resistivity‐versus‐depth profiles from each of the 3D models (derived from different starting half‐space) at the borehole locations and compared them with resistivity logs from 11 wells that are located nearby or at shortest offsets from the MT lines using a threshold distance of 5 km (see Figure 7 and Texts S7 and S8 in Supporting Information S1). We consider this as a geologically valid way of ground‐truthing any inversion model (e.g., Karpiah et al., 2022; Mackie et al., 2020; Meju et al., 2019; Saleh et al., 2022). Ideally, this will enable us to select which of the MT models best describes the subsurface geology.…”

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

“…This provided the motivation for the development of a crossgradient-based anisotropic-resistivity-imaging algorithm that directly enforces structural similarity between the horizontal and vertical resistivity models without control from seismic or well data [4,14,15]. The seismic, image-guided anisotropic 3D inversion of CSEM and MT data is an adaption of this crossgradient philosophy, in which the structural controls from seismic or other images are infused in the anisotropic resistivity inversion process [7,[16][17][18]. [1].…”

“…It is emerging that integrating 3D anisotropic CSEM-MT data imaging into seismic or structural constraints leads to geologically robust models [4,7,15]. Two methods of geologically consistent 3D anisotropic CSEM and MT resistivity inversion (using crossgradient constraints) have recently been developed [7,15,18] and are briefly described below.…”