Space based Earth observation approach for exploring hydrocarbon prospects in an intracratonic rift basin – A study in north Cambay basin, Gujarat

Abstract

In the present study, we carried out a conjugate analysis of Landsat-8 Operational Land Imager (OLI), Sentinel-2B Multi-Spectral Instrument (MSI), Advanced Land Observation Satellite Phased Array L-band SAR (ALOS PALSAR), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over a study area of northern Cambay Basin to delineate prospective areas for hydrocarbon exploration. In this regard, we utilized feature-oriented principal component (PC) images of Landsat OLI data, PC images of Sentinel-2B visible and near-infrared (VNIR)-short-wave infrared (SWIR) bands, thresholded Cartosat-1 Digital Elevation Model (DEM), and polarization image composite of ALOS PALSAR data to delineate geomorphic and lineament features in the study area. Most of the geomorphic features, such as scroll plain, gullies, elevated pediment, circular drainage anomalies, etc., indicate localized structural uplift. Geomorphic anomalies and lineaments, essential for identifying structural controls of near-surface hydrocarbon accumulation, were identified using enhanced satellite data. Geophysical anomalies derived from gravity datasets supplemented the presence and down-depth continuity of geological structures. Spectral profiles of calcrete-bearing soil samples were used to identify calcrete-rich zones in the optical remote sensing image data as a proxy owing to field evidence of close association of calcrete-rich soils with known subsurface hydrocarbon accumulations. Sub-pixel mapping algorithm Constrained Energy Minimization (CEM) applied to SWIR bands of ASTER data was used to delineate surface proxies of near-surface hydrocarbon seepage. Isopach maps of shallowest reservoir formations (Mid-/ Late Eocene) were used as indicators of favorable near-surface hydrocarbon accumulation.Earth observation-based geomorphic, lineament, and spectral anomalies were integrated with supplementary datasets, such as reservoir isopach and absorbed gas anomalies, as controls using the weighted summation method for quantitative deduction of the hydrocarbon potential map of the study area. The weights for input variables or parameters (geomorphic, spectral, geochemical, etc.) were inferred based on spatial associations of these anomalous units/variables with the existing oil & gas well locations. The identified potential map is in broad synergy with the field observations on localized uplift, geo-botanical anomalies, and calcrete-rich zones within the extent of high & moderate hydrocarbon potential areas.