W-17: Surface to Subsurface: Drone-Enabled Analog Studies for Reservoir Characterization

This workshop demonstrates how UAV technology revolutionizes surface-to-subsurface analog studies for reservoir characterization. Participants learn structure-from-motion photogrammetry, LiDAR, and semi-airborne electromagnetic methods to capture depositional architecture at centimeter-scale resolution. Through case studies from modern fluvial systems (Mississippi/Missouri, Red River, De Grey Delta) and outcrop analogs (Montllobar fan, Mesa Rica Sandstone), attendees extract quantitative parameters for stochastic reservoir modeling and integrate analog data with subsurface workflows.
Materials Covered and Skills Gained
• UAV Acquisition Techniques - Learn structure-from-motion photogrammetry, LiDAR vegetation penetration, and semi-airborne electromagnetic methods for capturing geomorphic features at reservoir-relevant scales.
• Quantitative Parameter Extraction - Extract measurable architectural parameters (channel dimensions, point bar geometries, crevasse splays) from modern systems to develop probability distributions for stochastic reservoir modeling.
• Fluvial and Deltaic Case Studies - Analyze drone surveys from active rivers and outcrop analogs to understand bounding surface hierarchies, permeability barriers, and facies asymmetry in wave-influenced deltas.
• Subsurface Workflow Integration - Translate UAV-derived data into reservoir modeling formats using digital outcrop modeling, training images, and multi-point statistics for improved well placement.

Lead Organizer

John Holbrook, Texas Christian University

Co-Organizer(s)

Jessica Puglsey, University of Aberdeen
John Howell, University of Aberdeen