1. Toward a Thorough Approach to Predicting Klinkenberg Permeability in a Tight Gas Reservoir: A Comparative Study

Sadegh Baziar; Mohammad Mobin Gafoori; Seyed Mehdi Mohaimenian Pour; Majid Nabi Bidhendi; Reza Hajiani

Volume 4, Issue 3 , Summer 2015, , Pages 18-36

http://dx.doi.org/10.22050/ijogst.2015.10365

Abstract
  Klinkenberg permeability is an important parameter in tight gas reservoirs. There are conventional methods for determining it, but these methods depend on core permeability. Cores are few in number, but well logs are usually accessible for all wells and provide continuous information. In this regard, ...  Read More

2. Development of an Intelligent System to Synthesize Petrophysical Well Logs

Morteza Nouri Taleghani; Sadegh Saffarzadeh; Mina Karimi Khaledi; Ghasem Zargar

Volume 2, Issue 3 , Summer 2013, , Pages 11-24

http://dx.doi.org/10.22050/ijogst.2013.3641

Abstract
  Porosity is one of the fundamental petrophysical properties that should be evaluated for hydrocarbon bearing reservoirs. It is a vital factor in precise understanding of reservoir quality in a hydrocarbon field. Log data are exceedingly crucial information in petroleum industries, for many of hydrocarbon ...  Read More

3. Support Vector Machine Based Facies Classification Using Seismic Attributes in an Oil Field of Iran

Majid Bagheri; Mohammad Ali Riahi

Volume 2, Issue 3 , Summer 2013, , Pages 1-10

http://dx.doi.org/10.22050/ijogst.2013.3640

Abstract
  Seismic facies analysis (SFA) aims to classify similar seismic traces based on amplitude, phase, frequency, and other seismic attributes. SFA has proven useful in interpreting seismic data, allowing significant information on subsurface geological structures to be extracted. While facies analysis has ...  Read More

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

Mohsen Karimian; Nader Fathianpour; Jamshid Moghaddasi

Volume 2, Issue 3 , Summer 2013, , Pages 25-36

http://dx.doi.org/10.22050/ijogst.2013.3642

Abstract
  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 with ...  Read More