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Determination of Geostatistical Parameters Using Well Test Data

Abstract : In this paper we describe a new method to obtain estimations of the geostatistical parameters (GPs) such as the correlation length, lc and the permeability variance sigma2ln from well test data. In practical studies, the GPs are estimated using geological and petrophysical data, but often, these data are too scarce to give precise results. The proposed method uses the Bayesian inversion theory, in conjunction with a fast evaluation of well tests that implies upscaling techniques. The method was tested using synthetic well-test data performed on some training images, and estimations of the underlying correlation length, lc and permeability variance, sigma2ln were recovered. These estimations give a correct order of magnitude of the actual values, but as noticed in similar methods, the uncertainties are high. Once the GPs are estimated, other well established techniques can be used to get well-test matched reservoir images consistent with the geostatistical model. We will see that excellent well test data are needed, and that the method could be improved using multiple well test data.
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Y. Gautier, B. Noetinger. Determination of Geostatistical Parameters Using Well Test Data. Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles, Institut Français du Pétrole (IFP), 2004, 59 (2), pp.167-183. ⟨10.2516/ogst:2004013⟩. ⟨hal-02017295⟩



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