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

Author:

Hodgetts D.12,Drinkwater N. J.3,Hodgson J.1,Kavanagh J.1,Flint S. S.1,Keogh K. J.14,Howell J. A.15

Affiliation:

1. Stratigraphy Group, Department of Earth and Ocean Science, University of Liverpool Brownlow Street, Liverpool L69 3BX, UK david.hodgetts@man.ac.uk

2. Now at Department of Earth Science, University of Manchester Oxford Road, Manchester M13 9PL, UK

3. Schlumberger Cambridge Research High Cross, Madingley Road, Cambridge CB3 0EL, UK

4. Statoil ASA, TEK F&T UTV TOS Forushagen, 4035 Stavanger, Norway

5. Department of Geology, University of Bergen Allegaten 41, N-5007 Bergen, Norway

Abstract

AbstractRecent 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.

Publisher

Geological Society of London

Subject

Geology,Ocean Engineering,Water Science and Technology

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