HR: 1340h
AN: H13C-1387    [Abstracts]
TI: Comparison of Deterministic and Stochastic Fractures in Water Flooding Numerical Simulations
AU: * Belayneh, M
EM: m.belayneh@imperial.ac.uk
AF: Department of Earth Science and Engineering, Imperial College, Royal School of Mines, Exhibition Road, London, SW7 2AZ,
AU: Matthäi, S K
EM: s.matthai@imperial.ac.uk
AF: Department of Earth Science and Engineering, Imperial College, Royal School of Mines, Exhibition Road, London, SW7 2AZ,
AU: Blunt, M J
EM: m.blunt@imperial.ac.uk
AF: Department of Earth Science and Engineering, Imperial College, Royal School of Mines, Exhibition Road, London, SW7 2AZ,
AU: Rogers, S
EM: SRogers@golder.com
AF: Golder Associates Ltd, 500-4260 Still Creek Drive, Burnaby, Canada, V5C 6C6,
AB: ABSTRACT Determining fracture attributes including fracture number, number of fractures sets, their length distribution, orientation, spacing and aperture in reservoirs is a challenge. One way of doing this is by studying outcrop analogues that have the same geological history and show comparable petrophysical properties and incorporate into our reservoir model building and simulation. Vein networks that were once barren fractures (fossil fractures) which were later filled with minerals are used in this work. We accept the differences between veins and fractures proposed in the literature (e.g. Peacock 2004) who argued that veins and joints should be analysed separately. In this article we assume that the geometrical properties of both veins and joints can be analysed using the same approach. We have used calcite vein attributes determined from eight scan lines (to simulate boreholes) and window samples on well-exposed Liassic carbonate platforms on the southern margin of the Bristol Channel Basin. The vein attributes determined from each scan line were used to condition stochastic generation of fractures using the Discrete Fracture Network (DFN) code, FracMan. Water breakthrough time, comparison of storage capacity of fractures and matrix, total fracture surface area, fracture surface area per volume, fracture volume and fracture volume per volume of the model were then determined by applying a constant pressure gradient for each realisation to simulate water flooding numerical simulations using combined finite element – finite volume. This was then compared with water flooding numerical simulation for real fracture networks. The results indicate that, depending on the variability of the above attributes, fluid flow in the system can vary from pervasive type where the fractures play subordinate role to a highly localised flow where most of the flow occurs either through single or connected networks of fractures. The results of this work have profound impact for predicting oil recovery and water breakthrough time based on limited information from boreholes. Key words: fractures, fluid flow, water flooding, numerical simulations
DE: 5104 Fracture and flow
SC: Hydrology [H]
MN: 2007 Fall Meeting