Porosity estimation by ٣D seismic data using artificial neural networks

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,832

فایل این مقاله در 6 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

GCI12_044

تاریخ نمایه سازی: 11 دی 1384

چکیده مقاله:

Reservoir properties such as porosity could be predicted, precisely, by integration of seismic data and inversion result. In this study, first by using ٣D seismic data, horizon interpretations and well logs, ٣D acoustic impedance model of reservoir was generated. Then some single attributes extracted from seismic data. After that linear step wise regression method was used to generate seismic multi-attributes. Later, the three layered artificial neural network, with three nodes in input layer, eight nodes in hidden layer and one in output designed. Finally, ٣D porosity model estimated applying neural network, seismic multi-attributes and well logs.

نویسندگان

Javad Jamali

National Iranian Oil Company

Maryam Sadri

Amir Kabir University of Technology