The Porosity Prediction of One of Iran South Oil Field Carbonate Reservoirs Using Support Vector Regression

The Porosity Prediction of One of Iran South Oil Field Carbonate Reservoirs Using Support Vector Regression

Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method...

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Bibliographic Details
Main Authors: Mohsen Karimian, Nader Fathianpour, Jamshid Moghaddasi
Format: Article
Language:English
Published: Petroleum University of Technology 2013-07-01
Series:Iranian Journal of Oil & Gas Science and Technology
Subjects:
Petrophysical Parameter
Reservoirs
Porosity
Well Log Data
Support Vector Machine
Online Access:http://ijogst.put.ac.ir/article_3642_4286517623335d98d338ff94a3483bdd.pdf

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