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گواهی نمایه سازی مقاله Permeability Estimation by Artificial Intelligence Methods from Wireline Logs; A Case Study From One of the Iranian Oil Reservoirs

عنوان مقاله: Permeability Estimation by Artificial Intelligence Methods from Wireline Logs; A Case Study From One of the Iranian Oil Reservoirs
شناسه (COI) مقاله: IPEC03_154
منتشر شده در سومین کنگره ملی مهندسی نفت در سال ۱۳۹۰
مشخصات نویسندگان مقاله:

Haniyeh Jalayeri - Department of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology
Amin Malekpoor - Department of Mining, Metallurgy and Petroleum Engineering, Amirkabir University of Technology
Aboulghasem Kamkar Rouhani - Department of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology
Mansour Ziaii - Department of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology

خلاصه مقاله:
Reservoir characterization plays a crucial role in modern reservoir management.The reservoir characteristics include porosity, permeability, facies distribution, anddepositional environment. Permeability is an important parameter associated with the characterization of hydrocarbon reservoirs. Estimation of permeability fromwireline logs is important yet difficult task to encounter in geophysical formation evaluation. This study was carried out permeability estimation in a carbonate gasreservoir with the artificial intelligence methods. Fuzzy logic and neuro-fuzzy method that based on fuzzy logic presented good results. It’s shown in present work, when the number of data is low and the formation is complex (such as carbonate reservoirs), the methods based on fuzzy logic will have appropriate performance

کلمات کلیدی:
Permeability; Fuzzy logic; Neuro-fuzzy method; Carbonate gas reservoir

صفحه اختصاصی مقاله و دریافت فایل کامل: https://www.civilica.com/Paper-IPEC03-IPEC03_154.html