Three-dimensional geological models from outcrop data using digital data collection techniques: an example from the Tanqua Karoo depocentre, South Africa

TLDR

Recent technological advances enable efficient digital data collection from outcrops, exemplified by studies of the faulted Permian turbidite fans at the Tanqua depocentre in South Africa, which expose continuous 40 km dip and 20 km strike sections. The study aims to use the integrated dataset to elucidate the stratigraphic evolution of a deep‑water fan complex through true 3‑D analysis of field data. Digital data were collected using DGPS, laser surveying, ground and helicopter photography, photogrammetry, digital outcrop logging, and borehole geophysics, then integrated into 3‑D geological models constructed with a subsurface reservoir‑modelling system. The approach improves understanding of deep‑water fan geometries and flow‑problematic zones, enhancing offshore analogue models, and has already been used to condition stochastic geological models of a North Sea deep‑water reservoir.

Abstract

Abstract Recent technological advances have made the collection of digital geological data from outcrops a realistic and efficient proposition. The world-class exposures of Permian basin-floor turbidite fans of the Tanqua depocentre, Karoo Basin, South Africa have been the focus of one such study. These outcrops are faulted at a subseismic scale (displacements of up to 40 m), with continuous exposures of up to 40 km in depositional dip and 20 km strike directions. Digital data collection has been undertaken using a variety of methods: differential global-positioning systems (DGPS) mapping, surveying using laser total station and laser rangefinders, ground- and helicopter-based digital photography and photogrammetry, and digital sedimentary outcrop logging as well as geophysical data from boreholes. These data have then been integrated into several 3-D geological models of the study area, built using a subsurface reservoir-modelling system. The integrated dataset provides insights into the stratigraphic evolution of a deep-water fan complex by allowing true 3-D analysis and interpretation of data collected in the field. The improved understanding of these deep-water fan systems will improve existing models of offshore analogues by enhancing understanding of geometries and trends not resolvable from existing offshore data and by identifying potential problematic areas for fluid flow. Initial results from the application of this approach have been successfully applied to the conditioning of stochastic geological models of a subsurface deep-water reservoir from the North Sea.