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An Integrated Workflow for History Matching of Stochastic Models of Faulted and Fractured Reservoirs

L.Y. Hu, R. Basquet, S. Jenni, M.C. Cacas, B. Bourbiaux and J.M. Daniel
Institut Français du Pétrole 1-4, Avenue de Bois-Préau, 92852 Rueil-Malmaison Cedex, France

The key to effective management of faulted/fractured reservoirs lies in a thorough understanding of the geometry and conductive properties of the fault/fracture network. In recent years, tremendous advances have been made in the modeling of faulted/fractured reservoirs, both with respect to geological characterization [1] and fluid-flow simulation [2][3]. In the mean time, an innovative solution, based on the gradual deformation of geostatistical models [4][5][6], was proposed for history matching of reservoir models. But so far, this is limited to non-fractured reservoir models.

In this paper, we propose a workflow for history matching of stochastic models of faulted/fractured reservoirs. This workflow is based on a consistent integration of the geological modeling procedure for faulted/fractured reservoirs, the algorithm for fluid flow simulation on discrete fault/fracture networks [7] and our newly developed method for gradually deforming object-based reservoir models [8]. The approach will make it possible to optimize the match between the model and the field, while maintaining a geologically and geostatistically coherent fault/fracture representation. The result is a more robust simulation model, which will be more reliable in prediction than conventionally history matched models.

The emphasis of this paper will be on the methodology for history matching of stochastic models of faulted/fractured reservoirs at the scale of fracture swarms and sub-seismic faults (reservoir field scale). Validation of the methodology on synthetic cases (based on real faulted/fractured reservoirs) will be presented. Further extensions of the above methodology will include the calibration of fracture networks in the neighborhood of wells, the calibration of matrix block size distributions in the dual porosity and dual permeability framework.

References

1. Cacas M.C, Daniel, J.M. and Letouzey, 2001, Nested geological modelling of naturally fractured reservoirs, Petroleum Geoscience, Vol.7, pp.S43-S52.

2. Bourbiaux, B. Cacas, M.C., Sarda, S and Sabathier, J.C., 1998, A rapid and efficient methodology to convert fractured reservoir images into a dual-porosity model, Revue de l’IFP, Vol.53, No.6.

3. Cosentino, L., Coury, Y., Daniel, J.M., Manceau, E., Ravenne, C., Van Lingen, P., Cole, J. and Sengul, M., 2001, Integrated study of fractured middle east reservoir with stratiform super-K intervals – Part-2: Upscaling and dual media simulation, Paper SPE 68184.

4. Hu, L.Y., 2000, Gradual deformation and iterative calibration of Gaussian-related stochastic models, Math. Geology, Vol. 32, No.1.

5. Le Ravalec, M., Noetinger, B. and Hu, L.Y., 2000, The FFT moving average (FFT-MA) generator: An efficient numerical method for generating and conditioning Gaussian simulations, Math. Geology, Vol.32, No.6.

6. Roggero, F. and Hu, L.Y., 1998, Gradual deformation of continuous geostatistical models for history matching, Paper SPE 49004.

7. Sarda S., Jeannin L., Basquet R. and Bourbiaux B., 2002. Hydraulic Characterization of Fractured Reservoirs: Simulation on Discrete Fracture Models, SPE Evaluation & Engineering, April.

8. Hu, L.Y., 2003, History matching of object-based stochastic reservoir models, Paper SPE 81503.

Integrated workflow for history matching of stochastic reservoir models with heterogeneous matrix and fault/fracture network