Faulting and fault sealing in production simulation models: Brent Province, northern North Sea

Abstract

Faults can severely compartmentalize pressures and fluids in producing reservoirs, and it is therefore important to take these effects into account when modelling field production characteristics. The Brent Group fields, northern North Sea, contain a complex arrangement of fault juxtapositions of a well-layered sand-shale reservoir stratigraphy, and fault zones containing a variety of fluid flow-retarding fault rock products. It has been our experience that these fault juxtapositions impact the ‘plumbing’ of the faulted layering system in the reservoirs and the models that are built to mimic them – and are, in fact, a first-order sensitivity on compartmentalization of pressures and fluid flow during production simulation. It is important, therefore, to capture and validate the geological feasibility of fault- horizon geometries, from the seismic interpretation through to the static geocellular model, by model building in conjunction with the interpretation. It is then equally important to preserve this geometrical information during geocellular transfer to the simulation model, where it is critical input data used for calculation of fault zone properties and fault transmissibility multipliers, used to mimic the flow-retarding effects of faults. Application of these multipliers to geometrically weak models tends to produce ambiguous or otherwise potentially misleading simulation results. We have systematically modelled transmissibility multipliers from the upscaled cellular structure and property grids of geometrically robust models – with reference to data on clay content and permeability of fault rocks present within drill core from the particular reservoir under study, or from similar nearby reservoirs within the same stratigraphy. Where these transmissibility multipliers have been incorporated into the production simulation models, the resulting history matches are far better and quicker than had been achieved previously. The results are particularly enhanced where the fault rock data are drawn from rocks that have experienced a similar burial–strain history to the reservoir under study.

From mechanical modeling to seismic imaging of faults: A synthetic workflow to study the impact of faults on seismic

“…In reality though, faults are narrow zones or volumes of highly and heterogeneously strained rocks, with petrophysical properties differing from those of the host rock. Internal fault structure varies throughout reservoirs (Fisher and Jolley, 2007;Jolley et al, 2007;Faulkner et al, 2010 and references therein). Fault structure and distribution of fault properties depend on factors such as host lithology and stratigraphy (Davatzes and Aydin, 2005;Bastesen and Braathen, 2010), depth of burial at time of faulting (Fisher and Knipe, 2001), initial fault array geometry and structural evolution (Childs et al, 2009), and diagenesis (Solum et al, 2010).…”

Understanding regional-scale structural uncertainty: The onshore Gulf of Corinth rift as a hydrocarbon exploration analogue

“…Needham et al, 1996;Childs et al, 1997;Jolley et al, 2007). A number of studies have utilised 2D seismic forward modelling to generate synthetic seismic across known geometries and facies distributions (Johansen et al, 1994;Hodgetts and Howell, 2000;Alaei and Petersen, 2007) however, few if any use the technique to illustrate the potential uncertainties pertinent to hydrocarbon exploration as described here.…”

Safety-relevant hydrogeological properties of the claystone barrier of a Swiss radioactive waste repository: An evaluation using multiple lines of evidence

“…Specifically, it can be shown that, for clay mineral contents > 25 wt.-%, K reduces to values < 10 -9 m/s, and for clay mineral contents of > 40 wt.-% to values of < 10 -11 m/s. Jolley et al (2007) compiled data from a large number of permeability tests on fault rock in cores from a large K depth range from the Brent Province (North Sea) as a function of clay mineral content. All samples with clay contents > 40 wt.-% yielded K values Ä 10 -12 m/s (original permeability data transferred into hydraulic conductivity values, see Nagra 2014b, Dossier VI, Fig.…”