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[ ] Prieditis, J.,Texaco E&P Technology Dept. , Yang, A.P., Texaco E&P Technology Dept. and Wilkins, M.D. , Texaco Inc., "Simulation of a CO2 Flood in the Slaughter Field with Geostatistical Reservoir Characterization", SPE 49168, 1998. [ ] M.N. Bushara and A.El Tawel, Zakum Development Company (ZADCO), Effective Permeability Modeling :Geostatistical Integration of Permeability Indicators, offshore Abu Dhabi SPE 78583, 2002. [6] Jef Caers, Geostatistical reservoir modelling using statistical pattern recognition, Journal of Petroleum Science and Engineering ( ) , . [7] N.I.O.C Volume 1: Oct 1974 by B.P. Reserch Center Report EPR/R8114/EPR/ R226 Oil Reserves and Production Potential of the Mansouri Field, IRAN

[9] C.V.Deutch and P.W.Cockerman, Exxon Production Research Co. Geostatistical Modeling of Permeability with Annealing Cosimulation (ACS) ,SPE 28413, 1994. [ ] N.I.O.C, Well Testing Data of the Bangestan Reservoir Mansouri Field, .

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Stochastic distribution of permeability for one of the south reservoir of

IRAN with the help of Geostatisical methods

Mohammad Mehdi Khajeh1, Mohammad Aghabeigi2* 1: Sahand University of Technology (SUT) 2: National Iranian South Oil fields Company (NISOC)

E-mail: aghabeigi60@yahoo.com

Abstract

Petrophisical data of reservoir are always one of the important parameter to evaluate the reservoir performance, because of limited available number of data, gathering new information may not be possible but by simulation methods. One of the method is Geostatistics which is now under consideration in developed countries as a reliable method. The specific characteristic of Geostatistics with respect to classical statistics is evaluation of spatial error distribution function beside the absolute results of estimation and the accuracy of estimation can be calculated. Therefore the data gathering is limited only to low accuracy area. In this paper, the permeability data obtained from well test analysis in Mansori field was used to estimate the permeability distribution and evaluate the error distribution function by Geostatistics, also possible conditions in simulation of permeability distribution would be described. Keywords: Permeability, geostatistics, variogram, kriging, Simulation

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