Abstract
A new approach for conditional simulation is proposed. The key idea of this method is to dissociate the task of estimating the local probability distribution functions from the task of producing equi-probable images. Probability Field Simulation starts with the premise that the local conditional distributions are known. The conditional simulations are then obtained by drawing realizations from these cdfs. The probability values used to draw from the local cdfs constitute a probability field, and are viewed as outcomes of a random function characterized by a uniform distribution and a given covariance function. Probability Field Simulation, thus, consists of the following steps: inferring the univariate and bivariate characteristics of the probability field, generating a non-conditional simulation of the probability field and , finally, using the simulated probability values to draw from the local cdfs. Guidelines on how to infer the distribution characteristics of the probability field are discussed and an example of application is presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Damsleth E., Tzolesen C.B, Omre K.H. and Haldorsen, H.H., 1990, “A two-stage stochastic model applied to a North Sea reservoir”, SPE Paper No. 20605.
Gómez-Hernández J.J and Srivastava R.M., 1990, “ISIM3D: An ANSI-C 3 dimensional multiple indicator simulation program”, Computers and Geosciences, v.16, n.6, pp 395–440.
Haldorsen H.H. and Damsleth E., 1990, “Stochastic Modeling”, Journal of PetroleumTechnology, April 1990, pp. 404–412.
Hewett T. and Behrens R.A. (1988) “Conditional simulation of reservoir heterogeneity with fractals”, SPE Paper No. 18326.
Isaaks E.H., 1990, “The Application of Monte Carlo Methods to the Analysis of Spatially Correlated Data”, PhD thesis, Stanford University, 213p.
Journel A.G. and Alabert F.G., 1988, “Focusine on Spatial Connectivity of Extreme-Valued Attributes: Stochastic Indicator Models of Reservoir Heterogeneities”, SPE Paper No 18324.
Matheron G., Beucher H, Fouquet Ch. de, Galli A and Ravenne Ch., 1988, “Simulations Conditionnelle à Trois Faciès dans une Falaise de la Formation du Brent”, Sciences de la Terre, No. 28, pp. 213–249.
Ruffo P. and Scola V., 1992, “An Application of Geostatistical Simulation to Probability Estimation of Prospects Geometry”, Mediterranean Petroleum Conference, Tripoli, 10p.
Srivastava R.M., 1990, “An Application of Geostatistical Methods for Risk Analysis in Reservoir Management”, SPE Paper No 20608.
Verly G., 1983, “The Multigaussian Approach and its Applications to the Estimation of Local Reserves”, Mathematical Geology, vol. 15, No 2, pp. 259–286.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1993 Kluwer Academic Publishers
About this chapter
Cite this chapter
Froidevaux, R. (1993). Probability Field Simulation. In: Soares, A. (eds) Geostatistics Tróia ’92. Quantitative Geology and Geostatistics, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1739-5_7
Download citation
DOI: https://doi.org/10.1007/978-94-011-1739-5_7
Publisher Name: Springer, Dordrecht
Print ISBN: 978-0-7923-2157-6
Online ISBN: 978-94-011-1739-5
eBook Packages: Springer Book Archive