Integrated multispectral remote sensing approach for high-resolution spectral characterization and automated mapping of carbonate lithofacies

Abstract

Field-based high-resolution carbonate facies mapping is often challenging due to the limited accessible exposure, high-degree of heterogeneity, and lack of distinct natural characteristics between different lithofacies. To mitigate this issue, we proposed a novel approach by integrating multispectral remote sensing, advanced image processing techniques, and supervised classification to perform high-resolution carbonate lithofacies mapping and utilized the extensive Mesozoic carbonate in Saudi Arabia as an example. For this study, the Tuwaiq Mountain Formation (TMF) was selected not only because of its wide aerial distribution but also its importance as conventional and unconventional hydrocarbon reservoirs in the subsurface. Our proposed method was able to map and delineate different members (T1, T2, T3) and key lithofacies in the TMF. In addition, based on the spectral characteristics, the middle member of TMF (T2) can be further subdivided into two subunits (T2-a of higher reflectance & T2-b of lower reflectance). These findings are further corroborated by detailed microfacies analysis, which validates the presence of two sub-members of T2 (T2-a: Spiculitic foraminiferal wackestone and T2-b: Coralline floatstone facies). This resulted in a revised and accurate lithofacies map that made significant modifications over older maps. The overall accuracy of TMF lithofacies is 93.4 % with a kappa coefficient of 0.88. This study demonstrates that multispectral remote sensing approach are effective at distinguishing different carbonate units and providing high-resolution carbonate facies maps. The proposed approach should be applicable to other carbonate outcrops globally and could help in improving carbonate lithofacies mapping where the outcrops are not accessible.