کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1756316 | 1522894 | 2007 | 12 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia](/preview/png/1756316.png)
Shear wave velocity (Vs) associated with compressional wave velocity (Vp) can provide accurate data for geophysical study of a reservoir. These so called petroacoustic studies have important role in reservoir characterization objectives such as lithology determination, identifying pore fluid type, and geophysical interpretation. In this study, fuzzy logic, neuro-fuzzy and artificial neural network approaches were used as intelligent tools to predict Vs from conventional log data.The log data of two wells were used to construct intelligent models in a sandstone reservoir of the Carnarvon Basin, NW Shelf of Australia. A third well was used to evaluate the reliability of the models.The results showed that intelligent models were successful for prediction of Vs from conventional well log data. In the meanwhile, similar responses from different other intelligent methods indicated their validity for solving complex problems.
Journal: Journal of Petroleum Science and Engineering - Volume 55, Issues 3–4, February 2007, Pages 201–212