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Estimation of Permeability of a Sandstone Reservoir by a Fractal and Monte Carlo Simulation Approach: a Case Study : Volume 21, Issue 1 (03/01/2014)

By Vadapalli, U.

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Book Id: WPLBN0004017193
Format Type: PDF Article :
File Size: Pages 10
Reproduction Date: 2015

Title: Estimation of Permeability of a Sandstone Reservoir by a Fractal and Monte Carlo Simulation Approach: a Case Study : Volume 21, Issue 1 (03/01/2014)  
Author: Vadapalli, U.
Volume: Vol. 21, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Vedanti, N., Dimri, V. P., Srivastava, R. P., & Vadapalli, U. (2014). Estimation of Permeability of a Sandstone Reservoir by a Fractal and Monte Carlo Simulation Approach: a Case Study : Volume 21, Issue 1 (03/01/2014). Retrieved from

Description: CSIR-National Geophysical Research Institute, Hyderabad, India. Permeability of a hydrocarbon reservoir is usually estimated from core samples in the laboratory or from well test data provided by the industry. However, such data is very sparse and as such it takes longer to generate that. Thus, estimation of permeability directly from available porosity logs could be an alternative and far easier approach. In this paper, a method of permeability estimation is proposed for a sandstone reservoir, which considers fractal behavior of pore size distribution and tortuosity of capillary pathways to perform Monte Carlo simulations. In this method, we consider a reservoir to be a mono-dispersed medium to avoid effects of micro-porosity. The method is applied to porosity logs obtained from Ankleshwar oil field, situated in the Cambay basin, India, to calculate permeability distribution in a well. Computed permeability values are in good agreement with the observed permeability obtained from well test data. We also studied variation of permeability with different parameters such as tortuosity fractal dimension (Dt), grain size (r) and minimum particle size (d0), and found that permeability is highly dependent upon the grain size. This method will be extremely useful for permeability estimation, if the average grain size of the reservoir rock is known.

Estimation of permeability of a sandstone reservoir by a fractal and Monte Carlo simulation approach: a case study

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