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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 11 | Page No.: 2016-2030
DOI: 10.3923/jas.2009.2016.2030
 
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Permeability Prediction in an Oil Reservoir and Construction of 3D Geological Model by Stochastic Approaches

S. Alfaaouri, M.A. Riahi, N. Alizadeh and M. Rezaei

Abstract:
The objective of this study is to construct a comprehensive, interdisciplinary and quantitative characterization of a carbonate oil reservoir in Marine oil field. Another purpose is to testify the performance of a mounted fuzzy logic inference technique in carbonates to predict permeability values. In addition, Tixtier modification of common Wyllie-Rose formula is also applied. In each case a blind testing was used to define model prediction accuracy. Furthermore, detailed error analysis in different permeability increments was also mounted to have a better comparison. In this study the geological reservoir model is developed in two steps, first the reservoir skeleton of the field was constructed and then the reservoir properties were distributed within that structure model applying the stochastic approach. One of the most common methods for permeability prediction is the technique proposed by Wyllie and Rose and then modified by Tixtier to be use in carbonate deposits. In addition, during this study a fuzzy-logic inference technique was also applied to predict permeability values. Finally, a sensitivity analysis was mounted on the methods for distributing permeability within the reservoir skeleton grid. First, the Sequential Gaussian Simulation approach was simply applied. Then, seismic cubic impedance and seismic phase information was used as a secondary variable in two separate studies. Furthermore, using the properly constructed reservoir model the hydrocarbon in place was quantified applying the deterministic approach.
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How to cite this article:

S. Alfaaouri, M.A. Riahi, N. Alizadeh and M. Rezaei, 2009. Permeability Prediction in an Oil Reservoir and Construction of 3D Geological Model by Stochastic Approaches. Journal of Applied Sciences, 9: 2016-2030.

DOI: 10.3923/jas.2009.2016.2030

URL: https://scialert.net/abstract/?doi=jas.2009.2016.2030

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