Characterizing reservoir heterogeneity remains a critical challenge in subsurface exploration due to the limited resolution and mineralogical detail of conventional seismic and well-log data. Outcrop analogs provide a valuable solution, exposing continuous geological sections that can be leveraged to interpret subsurface plays. This study demonstrates a novel multi-scale workflow integrating hyperspectral remote sensing to quantitatively characterize outcrop heterogeneity in the Neuquén Basin, Argentina—a key analog for prolific unconventional reservoirs.

We acquired data across three scales: (i) proximal (XRD, µXRF, laboratory spectroscopy, petrography), (ii) local (UAV- and tripod-mounted hyperspectral imaging), and (iii) regional (orbital data). Hyperspectral imagery was processed using advanced classification algorithms to generate high-resolution mineralogical maps, quantifying mineral phases and hydrocarbons. Integration of these datasets enabled the precise identification of stratigraphic units and revealed significant variations in depositional environments. The methodology successfully delineated lithological heterogeneities within the mixed clastic-carbonate-evaporite sequence, providing insights into architectural elements.

Results confirm that the fusion of modern remote sensing with traditional field techniques enables a comprehensive, multi-scale assessment of mineralogy and facies architecture. This workflow effectively bridges the gap between detailed outcrop observation and subsurface reservoir models, providing a robust template for quantifying heterogeneity in reservoir analogs. The findings have direct applications for improving geological models in the Los Molles and Vaca Muerta formations and similar petroleum systems worldwide.