Characterization and Modeling of the Fault Network of a Brazilian Pre-Salt Reservoir and Upscaling Results

De Lima, Alexandre (University of Campinastd) | Fourno, André (IFP Energies Nouvelles) | Noetinger, Benoit (IFP Energies Nouvelles) | Schiozer, Denis José (University of Campinas)

OnePetro 

Abstract

Carbonate Brazilian pre-salt fields have a large number of faults detected by seismic and well data. Nevertheless, because of limitations in seismic resolution, all existent faults cannot be identified. That is one of the main challenges for understanding related heterogeneities (vugs, karst) and the flow behavior. This paper deals with a fault analysis and modeling using an original approach and fault data of three pre-salt reservoirs.

One possible approach for characterizing and modeling the fault network (Verscheure et al, 2010) aims the integration of all available conceptual knowledge and quantitative data. This sub-seismic model keeps the geological consistency of seismic faults through capturing its specific spatial organization. First, geometry of seismic faults was characterized based on fractal methods. Secondly, sub-seismic faults were generated with stochastic algorithm. The work originality is also related to the studied reservoir which is close to two other fractured reservoirs. Each one aims a fault network with a specific fractal dimension. The fractal dimension choice was discussed.

The results presented on this article lead us to discuss the importance of how to choose the samples for modeling sub-seismic faults based on the ensemble of seismic faults available. This article answers the question about which available seismic faults we should use for estimating fractal dimension, should we use all available seismic faults near of the reservoir area or use only the faults inside the reservoir contour. After this short discussion on the fractal dimension choice from a spatial distribution point of view, the impact of this choice on flow was illustrated. The sub-seismic fault models were modeled using different fractal dimension. Subsequently, an upscaling step using analytical upscaling (Oda, 1985) was performed. Finally by comparing the upscaling results of the fault networks, the choice of fractal dimension was characterized from a production point of view. Finally our modeling choice and simulation results were presented.

Characterizing sub-seismic faults has a major impact on the overall flow behavior of the field. The chosen methodology has been applied only on synthetic cases but never published using real data. This work will interest a practicing engineer. The fault network of these neighbor reservoirs allows us to illustrate the importance on the choice of fractal dimension for characterizing the fault network and its impact on the subseismic models and fluid displacement, consequently on production.