Paper Information

Title: 

ESTIMATION OF POROSITY UTILIZING ARTIFICIAL NEURAL NETWORK SYSTEMS

Type: PAPER
Author(s): KADKHODAEI ILKHCHI A.,REZAEI MOHAMMAD REZA,RASHIDI MASOUD,FATHI ALI*
 
 *MINING ENGINEERING DEPARTMENT, FACULTY OF ENGINEERING, THE UNIVERSITY OF TARBIAT MODARRES, TEHRAN, IRAN
 
Name of Seminar: PROCEEDING OF IRANIAN MINING ENGINEERING CONFERENCE
Type of Seminar:  CONFERENCE
Sponsor:  IRANIAN SOCIETY OF MINING ENGINEERING
Date:  2005Volume 1
 
 
Abstract: 

Porosity is one of the most important parameters for evaluation of petrochemical properties in a hydrocarbon reservoir. In the petroleum industry this parameter obtained from Helium injection test on the plugs. But preparation of cores is a difficult and expensive procedure. As well as it is not possible to prepare core from some wells such as horizontal wells.
In this study we use from the artificial neural network as a new approach for calculating core porosity. For this purpose petrochemical data from one of the wells, Southern Iran, was used to construct a model based on ANNs. Second well which did not contribute for construction the models was used to evaluate the reliability of the model. Results show that ANN has been successful for estimating of core porosity.    

 
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