Unraveling factors controlling spectral characteristics and spectrofacies in carbonate rocks: a case study from the upper Jurassic carbonate sequence, Central Saudi Arabia

Discriminating carbonate lithofacies requires comprehensive field and lab work. Recent works have successfully demonstrated the potential application of spectral remote sensing to optimize the recognition of highly heterogenous carbonate lithofacies beyond traditional geological mapping. However, one major challenge in applying this technique is the chemical and physical variations that can influence the position and depth of spectral features, obscuring the actual mineralogy and texture of the rocks. Here, we present a novel approach by integrating spaceborne multispectral and ultra-high resolution spectroradiometer reflectance laboratory measurements to discriminate the carbonate lithofacies of the Upper Jurassic Hanifa Formation (Hawtah and Ullayah members) in Central Saudi Arabia that exhibit highly heterogenous facies and to unravel the controlling factors influencing their spectral characteristics. In addition, this carbonate formation is selected due to their regional significance as both conventional and unconventional reservoirs in the subsurface and global significance as one of the most extensive carbonate platforms in the Tethys region. Our findings show that the Minimum Noise Fraction (MNF) and Principal Component Analysis (PCA) of multispectral data were able to divide Hawtah member into three units and Ulayyah member into 12 units for the first time, which are further verified by detailed fieldwork and microfacies analysis. In addition, spectroradiometer results characterize the absorption features of each unit and lead to the definition of four spectrofacies of Hanifa Formation which correspond to certain mineralogical and textural variations. The proposed spectrofacies results exhibit high consistency with X-ray fluorescence, X-ray diffraction, and scanning electron microscopy results. This study shows the effectiveness and high accuracy of integrated multispectral and ultra-high resolution spectroradiometer reflectance data for discriminating and characterizing carbonate lithofacies which can be applied globally for reservoir characterization and in-situ limestone quality control in the cement industry.