Reservoir Characterization from Digital Outcrop Data: New techniques for Structural and Stratigraphic Modelling

Hodgetts, David¹, Rob Gawthorpe¹, Paul Wilson¹, Franklin Rarity¹, Emma Finch¹ (1) University of Manchester, Manchester, England

Digital outcrop data provides an ideal opportunity to improve understanding of reservoirs at resolutions much higher than possible in the subsurface. Technologies such as LIDAR and DGPS allow rapid and highly accurate data collection, and provide data ideally suited to building high resolution and geologically realistic models. These outcrop based datasets differ, however, from subsurface data in several ways. Outcrop data tends to be very data dense in some areas and sparse in others (causing problems in surface gridding), data formats may be quite different and outcrop data resolution is generally much higher than in its subsurface counterpart. This increase in resolution and data density leads to problems in the majority of modeling packages as they have not been designed to work with such data. In-house software is being developed in order address these problems. A variety of new methodologies are incorporated into this software, including new surface modeling techniques, methods for geostatistical data extraction, improved structural modeling approaches and ways of utilizing and applying this extra information to the subsurface. These new techniques have been applied to the modeling of the Nukhul syncline, Gulf of Suez. The new modeling approaches have allowed complex and geologically realistic structural models to be built between high data density areas, and effective geostatistical data extraction from the outcrop data. The new modelling approaches have been integrated into the in-house software application capable of handling the detail and complexity of real geological scenarios, as well as being able to provide virtual outcrop examples forming part of a reservoir modeling example database.