Prediction of Sub-Seismic, Fault-Related Fracture and their Inclusion in Geocellular Models
Wolf, David; Bazalgette, Loic; Richard, Pascal
Whilst most motion along a fault is accommodated within a relatively narrow core, additional damage is incurred by the surrounding rock. Depending on the mechanics of the lithology and timing of deformation, this damage can have a major impact on reservoir performance. Damage can take the form of permeability-enhancing or -reducing features, such as: fractures, veins, deformation bands, or diffuse plastic deformation with only minor effects. Fracture-based damage zones are most common in well-cemented clastic and carbonate rocks. They can both enhance locally the storage properties of hydrocarbon reservoirs and channelize the flow. For those reasons, proper field development planning relies on the ability to predict the distribution and properties such damage zones.
In the subsurface, direct observations of fault zone architecture or damage zones are limited. The detailed structure of fault zone architecture is far below the resolution of even the best seismic data. Conversely, cores and wire-line logs provide high resolution 1D data limited by the sparse spacing of samples. In lieu of direct observation, a characterization method is to use outcrop observations as a proxy for damage zone geometries. These observations are then to be scaled by seismically resolvable aspects of fault geometry. Here, field exposures and core data have been utilized to assemble a database of likely geometries and determine predictive relationships with seismic-scale features (such as mechanical stratigraphy, displacement). The models need to be calibrated against dynamic data (e.g. pressure transient analysis, production index, production history, drilling fluid losses) to characterize the impact of damage zones on hydrocarbon storage and flow, or their influence on fracture stimulation.
Detailed modeling of sub-seismic fracture zones is a significant challenge. It often relies on stochastic fracture networks with little geological guidance. To overcome this limitation, our workflow is based on a thorough mechanical understanding. It uses geological constraints with field-tied correlations between seismic-scale features and fracture intensity or geometry aiming at capturing the dynamic behavior at the geocellular model-scale. This workflow helps focus data gathering to reduce the uncertainty at early stages as well as during the entire field development.
AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013