Flexible Simulation of Faults
- Per Roe (Norwegian Computing Center) | Petter Abrahamsen (Norwegian Computing Center) | Frode Georgsen (Norwegian Computing Center) | Anne Randi Syversveen (Norwegian Computing Center) | Oddvar Lia (StatoiHydro)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 19-22 September, Florence, Italy
- Publication Date
- Document Type
- Conference Paper
- 2010. Society of Petroleum Engineers
- 5.1.5 Geologic Modeling, 5.5.8 History Matching, 5.1.7 Seismic Processing and Interpretation, 5.1.8 Seismic Modelling, 5.1.1 Exploration, Development, Structural Geology, 5.5 Reservoir Simulation, 1.1 Well Planning, 7.2.2 Risk Management Systems, 5.1.2 Faults and Fracture Characterisation
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Fault geometry is modelled on basis of seismic data, but restricted by fault observations in wells. Due to uncertainties in depth migration, seismic interpretation and well data, there is a significant uncertainty in the geometry and position of the faults. Fault uncertainty impact reservoir volume, flow properties and well planning, and can be studied by stochastic simulation of faults.
We have developed a method for stochastic simulation of fault surfaces and fault networks using standard geostatistical methods. This is made possible by the fault parameterization used, where the faults are modelled as tilted surfaces. This new method is more flexible and efficient compared to already existing algorithms due to a simpler parameterization. Conditioning to fault observations in wells is also made simpler.
The fault is defined as a two-dimensional surface on a tilted reference plane. The uncertainty for a fault surface is bounded by a volume enclosing the fault surface. The smoothness of the simulated fault surfaces is controlled by variograms. The simulation is done by adding a simulated Gaussian residual. Well conditioning is done by kriging.
Using the described method we can simulate a set of fault realizations where the simulated faults look realistic, are within the defined uncertainty volumes, and honour well observations.
Technical contributions compared to previous work include efficient simulation of fault geometry, a flexible uncertainty model and well conditioning with no performance impact.
Fault modelling is an important part of the structural modelling workflow. During the recent years, software has made significant improvements in terms of better quality, faster model building and improved updatability by simplified workflow for fault surfaces and fault truncations. But still, it is not easy to create multiple realizations as a part of a uncertainty study. Interpretation and depth conversion uncertainties of fault surfaces and fault throw influence volume calculations of segmented reservoirs and flow across fault surfaces. It has been difficult to capture this uncertainty without a lot of manual work to create alternative fault realizations. Very often this is not done, with the consequence that fault interpretation uncertainty is ignored.
The existence, location and geometry of faults have a large impact on reservoir volumes and reservoir connectivity and compartmentalization. Understanding these uncertainties is important in well planning or if one wants to perform history matching. An uncertainty model for the fault geometry makes it possible to run Monte Carlo simulation of the fault surfaces. This lets us analyze the uncertainty of the reservoir volumes, probability for different compartmentalization scenarios or analyze uncertainty in reservoir communication and reservoir flow. (Rivenæs et al. 2005)
Information about faults comes mainly from three sources, seismic data; well data and knowledge of the local geology. Thore et al. (2002) lists several sources of uncertainty with regard to seismic interpretation of faults, but conclude that the main sources are uncertainty in the seismic interpretation together with vertical and lateral uncertainty from the time-depth migration of the seismic data.
The interpretation uncertainty is a consequence of the poor quality of the seismic data near faults, together with the fact that faults are modelled as two-dimensional planes even though they actually are three-dimensional structures. The interpretation uncertainty encompasses both the existence of faults and fault patterns, and the location and local shape of the faults. The depth migration uncertainty is due to uncertainty in the velocity model, and uncertainty in the actual seismic signal path due to non-horizontal velocity contrasts. The interpretation error is assumed to be independent for each fault, while the error introduced by the time-depth migration is correlated between faults. The migration error affects a larger area of the reservoir, and the error introduced by the time-depth migration for a single fault will be similar to the error for other nearby faults.
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