--> Abstract: Three-Dimensional Reservoir Models from Digitally Mapped Outcrop Data Using DGPS and LIDAR Mapping: Examples from the United Kingdom and Canada, by David Hodgetts, Nadine Mader, Rob Gawthorpe, Jonathan Redfern, and Ivan Perez; #90039 (2005)

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Three-Dimensional Reservoir Models from Digitally Mapped Outcrop Data Using DGPS and LIDAR Mapping: Examples from the United Kingdom and Canada

David Hodgetts, Nadine Mader, Rob Gawthorpe, Jonathan Redfern, and Ivan Perez
The University of Manchester, Manchester, United Kingdom

Digital outcrop surveying with Differential Global Positioning Systems (DGPS) and high resolution 3D laser scanners (LIDAR), integrated with more traditional methods of outcrop mapping and sedimentary logging, provides ideal datasets for building reservoir model analogues. The LIDAR point cloud data may be classified into geo-objects and reservoir facies with sedimentary logs and map data acting as conditioning for the point classification. This is achieved using both commercially available software and applications developed in house. The point data has then to be up-scaled into the reservoir model framework where it can then be used as conditioning for stochastic modelling. These outcrop data collection techniques have been applied to the excellent exposure of the Triassic Wolfville Formation around the Minas Basin, Nova Scotia. These outcrops are exposed in both cliff sections and wave-cut platforms, provides a unique three dimensional insight into the depositional processes, sedimentology and geometry of a classic red-bed fluvio-aeolian system. The area has also been affected by a post depositional phase of extensional faulting with minor displacement (<50cm). Fault traces are seen in both cliff sections and in the foreshore exposure making mapping fault lengths, geometries and displacements possible. In addition to this, several classic UK outcrops have been mapped a processed into 3D reservoir models. These outcrops have been mapped with DGPS and LIDAR and for the basis of one reservoir model analogue study. The high density of conditioning data, along with the associated improved understanding of geostatistics leads to improved, closer to deterministic, reservoir models.

AAPG Search and Discovery Article #90039©2005 AAPG Calgary, Alberta, June 16-19, 2005