سال انتشار: ۱۳۸۴

محل انتشار: دوازدهمین کنفرانس ژئوفیزیک

تعداد صفحات: ۶

نویسنده(ها):

Javad Jamali – National Iranian Oil Company
Maryam Sadri – Amir Kabir University of Technology

چکیده:

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.