Optimization with the gradual deformation method

Mathematical Geology

Volumn 34, Issue 2, 2002, Pages 125-142

  Le Ravalec Dupin, Mickaële ^a   Nœtinger, Benoît ^a  

^a IFP ENERGIES NOUVELLES   (France)

Author keywords

Convergence; Gradual deformation; Optimization

Indexed keywords

MODELING; RESERVOIR CHARACTERIZATION;

EID: 1842619590     PISSN: 08828121     EISSN: 15738868     Source Type: Journal    
DOI: 10.1023/A:1014408117518     Document Type: Article

References (16)

1. de Marsily, G., Lavedan, C., Boucher, M., and Fasanino, G., 1984, Interpretation of interference tests in a well field using geostatistical techniques to fit the permeability distribution in a reservoir model, in Verly, G., David, M., Journel, A. G., and Maréchal, A., eds., Geostatistics for natural resources characterization: Reidel, Dordrecht, The Netherlands, v. 2, p. 831-849.
2. Farmer, C. L., 1992, Numerical rocks, in King, P. R., ed., Mathematics of oil recovery: Oxford University Press, Oxford, UK, p. 437-447.
3. Holland, J. H., 1992, Adaptation in natural and artificial systems: Ann Harbor, The University of Michigan Press, Cambridge, MA, 211 p.
4. Hu, L. Y., 2000a, Gradual deformation and iterative calibration of Gaussian-related stochastic models: Math. Geol., v. 32, no. 1, p. 87-108.
5. Hu, L. Y., 2000b, Gradual deformation of non-Gaussian stochastic simulations: 6th Geostatistics Congress, Cape Town, South Africa, 10-14 April.
6. Hu, L. Y., Blanc, G., and Nœtinger, B., 1999, Gradual deformation and iterative calibration of sequential stochastic simulations: S. J. Lippard, A. Naess, and R. Sinding-Larsen, Proceedings of IAMG 1995, Trondheim, Norway, 6-11 Aug., 1999, vol. 2, p. 493-498.
7. Le Ravalec, M., Nœtinger, B., and Hu, L.-Y., 2000, The FFT moving average (FFT-MA) generator: An efficient numerical method for generating and conditioning Gaussian simulations: Math. Geol., v. 32, no. 6, p. 701-723.
8. Le Ravalec-Dupin, M., Hu, L.-Y., and Nœtinger, B., 2000, Sampling the conditional realization space using the gradual deformation method: 6th Geostatistics Congress, Cape Town, South Africa, 10-14 April.
9. Le Ravalec-Dupin, M., Nœtinger, B., Hu, L.-Y., and Blanc, G., 2000, Conditioning to dynamic data: An improved zonation approach: Pet. Geosci., vol. 7, p. S9-S16, 2001.
10. Neuman, S. P., 1973, Calibration of distributed parameter groundwater flow models viewed as a multiobjective decision process under uncertainty: Water Resour. Res., v. 9, no. 4, p. 1006-1021.
11. Oliver, D. S., 1995, Moving averages for Gaussian simulation in two and three dimensions: Math. Geol., v. 27, no. 8, p. 939-960.
12. Oliver, D. S., He, N., and Reynolds, A. C., 1996, Conditioning permeability fields to pressure data: 5th ECMOR, Leoben, Austria, 3-6 Sept., p. 259-268.
13. Reynolds, A. C., He, N., Chu, L., and Oliver, D. S., 1995, Reparameterization techniques for generating reservoir descriptions conditioned to variograms and well-test pressure data: SPE annual technical conference and exhibition, Dallas, TX, 22-25 Oct., SPE 30588, p. 609-624.
14. Roggero, F., and Hu, L.-Y., 1998, Gradual deformation of continuous geostatistical models for history matching: SPE annual technical conference and exhibition, New Orleans, LA, SPE 49004.
15. Sun, N.-Z., 1994, Inverse problems in groundwater modeling: Kluwer, Dordrecht, The Netherlands, 337 p.
16. Tarantola, A., 1987, Inverse problem theory - Methods for data fitting and model parameter estimation: Elsevier, Amsterdam, The Netherlands, 613 p.