High-resolution Spectral Characterization of Heterogenous Carbonate Lithofacies and their Controlling Factors

Discriminating carbonate lithofacies demands extensive fieldwork and costly geochemical analysis which is often constrained by outcrop accessibility and the number of studied sections. To overcome these challenges, the present work employs integration between spaceborne multispectral and lab hyperspectral datasets for the late Jurassic carbonate lithofacies discrimination and spectral characteristics. Carbonate minerals spectra show diagnostic absorption features in the shortwave infrared (SWIR) while impurities features exist in the visible near-infrared (VNIR)- SWIR wavelength region. Several chemical and physical factors affect the position and depth of carbonate minerals absorption features. In this study, Hanifa Formation in Central Saudi Arabia has gained economic significance as a key conventional and unconventional reservoir which is divided into Hawtah and Ulayyah members. The Minimum Noise Fraction (MNF) and Principal Component Analysis (PCA) image processing techniques were utilized on ASTER and Sentinel 2A multispectral data successfully differentiated the Hawtah member into three units and the Ulayyah member into twelve units for the first time which was verified by detailed microfacies analysis. Hyperspectral laboratory measurements of the newly identified units have characterized their absorption features, leading to the classification of four distinct spectrofacies within the Hanifa Formation. Each absorption feature corresponds to a specific mineralogy which shows high consistency with X-ray fluorescence, X-ray diffraction, and Scanning electron microscopy analyses. Also, Hyperspectral measurements showed that chemical factors, such as mineralogy, Mg, Fe, and clays, influence the depth and position of absorption features, while physical factors like grain size, porosity, and weathering primarily affect the reflectance values in the VNIR-SWIR wavelength ranges. This study demonstrates the effectiveness and high accuracy of using integrated multi and hyperspectral data to distinguish and characterize carbonate lithofacies. These methods can be applied worldwide for reservoir/ aquifer characterization, as well as for in-situ limestone quality control in the cement industry.

Keywords

Carbonates lithofacies, Absorption features, Hyperspectral, Multispectral, Spectrofacies.