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Rastegarnia, Mahdi, Kadkhodaie-Ilkhchi, Ali. (1392). Permeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran. , 3(2), 87-97. doi: 10.22059/jgeope.2013.36017
Mahdi Rastegarnia; Ali Kadkhodaie-Ilkhchi. "Permeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran". , 3, 2, 1392, 87-97. doi: 10.22059/jgeope.2013.36017
Rastegarnia, Mahdi, Kadkhodaie-Ilkhchi, Ali. (1392). 'Permeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran', , 3(2), pp. 87-97. doi: 10.22059/jgeope.2013.36017
Rastegarnia, Mahdi, Kadkhodaie-Ilkhchi, Ali. Permeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran. , 1392; 3(2): 87-97. doi: 10.22059/jgeope.2013.36017

Permeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran

Geopersia
مقاله 8، دوره 3، شماره 2، اسفند 2013، صفحه 87-97    اصل مقاله (1.53 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jgeope.2013.36017
نویسندگان
Mahdi Rastegarnia1؛ Ali Kadkhodaie-Ilkhchi* 2
1Petroleum Engineering Department, Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
2Geology Department, Faculty of Natural Science, University of Tabriz, Tabriz, Iran
چکیده
Accurate permeability estimation has always been a concern in determining flow units, assigning appropriate capillary pressure and
relative permeability curves to reservoir rock types, geological modeling, and dynamic simulation.Acoustic method can be used as an
alternative and effective tool for permeability determination. In this study, a four-step approach is proposed for permeability estimation
from acoustic data. The steps include estimation of the Stoneley wave slowness from conventional logs using a support vector machine
neural network, determination of the Stoneley wave slowness in non-permeable zones, calculation of the Stoneley permeability index,
and calculation of the Stoneley-Flow Zone Index (ST-FZI) permeability using the index matching factor (IMF). Finally, a comparison
is made between the ST-FZI permeability with those derived from CMR log and core analysis. The results of this study show that
acoustic method in conjunction with robust SVM neural network can be considered as an accurate tool for permeability estimation in
the mixed clastic-carbonate reservoirs with complex pore type systems.
کلیدواژه‌ها
Cheshmeh Khush oilfield؛ Flow zone indicator؛ Permeability؛ Stoneley wave velocity؛ Well log data
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