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Article
Selection of Optimum Permeability Estimation Approach in a Heterogeneous Carbonate Reservoir

Authors: Mohsen Saemi --- Ali Mohammad Bagheri
Journal: Journal of Petroleum Research & Studies مجلة البحوث والدراسات النفطية ISSN: 22205381 Year: 2016 Volume: 272 Issue: 13 Pages: 143-153
Publisher: Ministry of Oil وزارة النفط

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Abstract

Determination of permeability is an essential component of reservoir characterization process which is among the key input parameters into a flow simulation models. Permeability modeling in carbonate reservoirs is still a challenge in the world. Permeability is directly determined in the laboratory from core analysis. Alternatively, it can be determined by analyzing well test or well logs. Due to high cost associated with coring and some technical problems, few wells in any given field are cored whereas most wells have wire-line logs. In this study detailed core analysis data including core porosity and core permeability supplemented by well logs and well test data to predict a continuous log derived permeability in un-cored wells in a heterogeneous carbonate reservoir in south west of Iran. The Mishrif reservoir in the studied field consists of limestone and interbedded shale. The field has 3 wells that have recovered cores. Permeability prediction was applied by several methods including: fuzzy logic, neural networks, clustering, empirical methods and regression analysis. These different methods were used to determine the optimal approach for utilizing in the field under study. To test the permeability prediction, the techniques were calibrated in 2 cored wells and blind tested in remaining cored well to see how well estimated permeability fitted the actual core permeability. Among all permeability modeling methods applied in the field, it turned out that electrofacies method and after that artificial neural network have the highest degree of association. Fuzzy logic and regression techniques are average in modeling permeability and empirical methods are not capable for predicting permeability in studied heterogeneous carbonate reservoir. The core analysis from 3 cored-wells was applied to determine permeability in 51 un-cored wells.


Article
Integration of NMR, Conventional Logs and Core Data to Improve Formation Evaluation of a Gas Reservoir in Kangan and Dalan Formation, Iran

Authors: Ghafor Karimi --- Mohammad Mohammadnia --- Ali Mohammad Bagheri
Journal: Journal of Petroleum Research & Studies مجلة البحوث والدراسات النفطية ISSN: 22205381 Year: 2014 Volume: 377 Issue: 10th Pages: 154-168
Publisher: Ministry of Oil وزارة النفط

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Abstract

Conventional log based reservoir characterization of a gas reservoir in the Kangan and Dalan formations have recently been improved by application of the nuclear magnetic resonance log (NMR). Important reservoir properties such as permeability pore size distribution and capillary pressure curves can be estimated from NMR. These parameters are simulated directly in the laboratory on core samples recovered from the reservoir. Due to high cost associated with coring and some technical problems, few wells in any given field are cored. The only problem of NMR measurements in gas reservoirs is that in gas-bearing zones, total NMR porosity read much less than actual porosity due to low hydrogen index of the gas. This problem was solved by integration of NMR porosity with conventional well logs such as density and sonic and compared with core porosity. Improved porosity calculation lead to better core independent permeability estimation on the wells logged with NMR. NMR T2 distribution was calibrated with laboratory derived pore size distribution in 7 samples and a constant scaling factor was derived for each rock type to predict a pseudo pore size distribution from NMR.Logarithmic mean of pore size distribution in 4 wells with NMR was integrated with conventional logs in an artificial neural network to predict a pseudo pore size distribution logarithmic mean (PPSDLM) in the wells without NMR. PPSDLM and conventional well logs were involved to an electrofacies modeling to predict electrofacies in the reservoir for characterization of heterogeneity of the reservoir in 3D geological model. NMR permeability was also imported to the model as an associated log to predict facies base permeability. To test the permeability prediction, estimated permeability was compared with core derived permeability on 2 cored wells to see how well, estimated permeability fitted the actual core permeability.

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