Combined Ground Penetrating Radar (GPR) and Outcrop Studies as a Tool for Predicting Subsurface Fluvial Architecture

Oluwatosin Akinpelu

University of Toronto, Department of Geology, Toronto, Canada

[email protected]

Predicting the detailed internal architecture of subsurface fluvial deposits has been an enigma in reservoir development over the last few decades. In today’s world of ever-increasing demand for petroleum, the need for accurate handling of reservoir heterogeneities for optimized production cannot be over-emphasized and requires extensive research.

The complex geometry of fluvial sandbodies and their significant spatial heterogeneity has recently triggered a burgeoning interest in the use of outcrop data as analogues for subsurface reservoirs. While earlier attempts have essentially been two-dimensional, three-dimensional outcrop studies of sub-surface reservoir analogues combining outcrop data and closely spaced GPR profiles hold the greatest promise for fluvial hydrocarbon reservoir evaluation and development. To this end, this project adopts hybrid techniques integrating outcrop-based architectural element mapping of cliff faces and GPR imaging to obtain three-dimensional data from near surface sandstone reservoir analogs in a wide variety of fluvial channel deposits from the Whirlpool Formation (Niagara Escarpment), Kayenta Formation, Castlegate Sandstone (Utah) and St. Mary River Formation (Alberta). Facies associations and their bounding surfaces are mapped on photomosaics and combined with the GPR profiles to generate detailed three-dimensional stratigraphic volumes which can be sliced in different directions to unravel the depositional history of each Formation.

This project offers significant promise in unravelling the controls on the distribution of heterogeneous facies in fluvial deposits through studies of complex outcrop analogues. It is also of immense application to field development and enhanced recovery projects geared at retrieving previously untapped mobile oil due to reservoir heterogeneities.

AAPG Search and Discovery Article #90060©2006 AAPG Foundation Grants-in-Aid