The recent years have seen the emergence of detailed field data acquisition and efficient modelling tools to characterize reservoirs and model their complex internal structure in a realistic way. This progress led to the detection of multi-scale fractures in most reservoirs, and enabled to interpret unexpected field production features such as early breakthroughs. Therefore, the availability of a workflow and an integrated modelling methodology becomes more and more crucial to take into account the geological information about fractures/faults into the reservoir dynamic simulation process for optimizing field productivity and reserves. This paper reviews and illustrates the overall methodology and the specifically-involved procedures and tools we have gradually built from the experience acquired in various fractured field case studies.
The main steps of this multidisciplinary approach include (a) the detection, geological analysis and modeling of multiscale natural fracture network from seismic and well data, (b) its validation and calibration from dynamic field information such as well tests, (c) the choice of an equivalent simulation model applicable at reservoir scale, and its construction thanks to innovative flow up-scaling procedures applied to the realistic model provided by the geologist, (d) the implementation of predictive and numerically-efficient algorithms to represent the physics of flow transfers occurring both at local and large scale during multiphase field production.
Thanks to this consistent workflow, field simulation models remain interpretable in geological terms, which is helpful for subsequent model updating. Thus, specialists in geosciences and reservoir engineers can cooperate in a very effective way to improve the management of fractured reservoirs.
The presence of fractures and faults in petroleum reservoirs has always been an issue for the assessment of field productivity and reserves. The internal structure and flow behaviour of fractured reservoirs1,2,3 has been fairly well understood for a long time however, until recently, no consistent methodology and software enabled to integrate field information about natural fracturing for field production purposes. The recent development of new field data acquisition techniques, such as borehole imaging and 3D seismic, was an incentive for such integration. The unexpected production behaviour of many fields4 arising from an insufficient consideration of fracture effects on flow emphasized the need for better characterizing the distribution of fractures at various scales and transferring the meaningful part of this information to field simulation models.
Taking into account the availability of fracture-related information and flow simulation issues, we developed an integrated methodology involving the following steps (Fig. 1):
- constrained modelling of the geological fracture network based on the analysis, interpolation and extrapolation of fracture information acquired in wells and seismic surveys, sometime completed by outcrop analogue data;
- characterizating the hydrodynamic properties of this natural network from flow-related data; - choosing a flow simulation model suited to the role played by fractures and faults at various scales and involving upscaled parameters derived from the flow-calibrated geological fracture model;
- simulating reservoir flow behaviour on the basis of a physical assessment of multiphase flow mechanisms prevailing in transfers within and between media.
Using terminology found in the literature,5 the first two steps of this methodology combine a forward approach mainly based on geosciences and an inverse approach based on reservoir engineering. The flow upscaling procedures involved in the last two steps ensure consistency between the flow-calibrated geological model and the single-medium, multi-medium and/or explicit modelling approach(es) chosen for field simulation. The four steps of this integrated approach are presented, discussed and illustrated hereafter.
Building a geological model of faults and fractures.
The methodology is extensively described by Cacas et al.6 and is briefly summarized hereafter (Fig. 2).