Neural network use ability in Well Log Data Analysis
محل انتشار: هفتمین کنگره ملی مهندسی شیمی
سال انتشار: 1390
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 795
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شناسه ملی سند علمی:
ICHEC07_649
تاریخ نمایه سازی: 25 فروردین 1394
چکیده مقاله:
Well log data analysis plays an important task in petroleum exploration. It is used to identify the potential for oil production at a given source and so forms the basis for the estimation of financial returns and economic benefits. In recent years, many computational intelligence techniques such as backpropagation neural networks (BPNN) and fuzzy systems have been applied to perform the task. Support vector machines (SVMs) are new techniques and very few reports have been published in this application area. This paper presents the study and comparison of BPNN model with a SVM model on a set of practical well log data. Future directions of exploring of the use of SVM for improved results will also be discussed.
کلیدواژه ها:
well log data analysis ، reservoir characterization ، backpropagation neural networks (BPNN) ، support vector machine (SVM)
نویسندگان
Mohammad Ali Mohammadi
Department of petroleum engineering ,Omidiyeh Branch ,Islamic Azad University , Omidiyeh ,Iran
Ali Mohammadi
Department of petroleum engineering ,Omidiyeh Branch ,Islamic Azad University , Omidiyeh ,Iran
Jamshid Moghadasi
Department of petroleum engineering ,Omidiyeh Branch ,Islamic Azad University , Omidiyeh ,Iran
Mohammad Javad Mohammadi
Department of petroleum engineering ,Omidiyeh Branch ,Islamic Azad University , Omidiyeh ,Iran