A Study on Prediction of Output in Oilfield Using Multiple Linear Regression

An oilfield is an area with reserves of recoverable petroleum, especially one with several oil-producing wells [1]. The challenge in this project is to find the variable for the output of oilfield because here are numerous factors affecting output in an oilfield. The relationship between field outpu...

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Main Authors: Razali, Radzuan, Mustafar, Izni
Format: Citation Index Journal
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.8283 /
Published: 2011
Subjects:
QA76 Computer software
Online Access: http://eprints.utp.edu.my/8283/1/IJAST-Prediction_of_output_in_oilfield.pdf
http://eprints.utp.edu.my/8283/
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spelling utp-eprints.82832017-03-20T01:59:40Z A Study on Prediction of Output in Oilfield Using Multiple Linear Regression Razali, Radzuan Mustafar, Izni QA76 Computer software An oilfield is an area with reserves of recoverable petroleum, especially one with several oil-producing wells [1]. The challenge in this project is to find the variable for the output of oilfield because here are numerous factors affecting output in an oilfield. The relationship between field output and one of the affecting factors is unscientific and are not precise, which it is needed to come out with a simple and more accurate. 8 parameters have been identified to predict the oilfield of output. After several screening test using Multiple Linear Regression, 4 parameters have been identified as a most significant parameter. The ordinary least squares method also used to minimize the sum of variables by eliminating the least important variables. And to validate the data, new set of different data used with only the most significant parameters. It validates the method as all the parameters obey the rules of P-value. 2011-07-01 Citation Index Journal PeerReviewed application/pdf http://eprints.utp.edu.my/8283/1/IJAST-Prediction_of_output_in_oilfield.pdf Razali, Radzuan and Mustafar, Izni (2011) A Study on Prediction of Output in Oilfield Using Multiple Linear Regression. [Citation Index Journal] http://eprints.utp.edu.my/8283/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
topic QA76 Computer software
spellingShingle QA76 Computer software
Razali, Radzuan
Mustafar, Izni
A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
description An oilfield is an area with reserves of recoverable petroleum, especially one with several oil-producing wells [1]. The challenge in this project is to find the variable for the output of oilfield because here are numerous factors affecting output in an oilfield. The relationship between field output and one of the affecting factors is unscientific and are not precise, which it is needed to come out with a simple and more accurate. 8 parameters have been identified to predict the oilfield of output. After several screening test using Multiple Linear Regression, 4 parameters have been identified as a most significant parameter. The ordinary least squares method also used to minimize the sum of variables by eliminating the least important variables. And to validate the data, new set of different data used with only the most significant parameters. It validates the method as all the parameters obey the rules of P-value.
format Citation Index Journal
author Razali, Radzuan
Mustafar, Izni
author_sort Razali, Radzuan
title A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
title_short A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
title_full A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
title_fullStr A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
title_full_unstemmed A Study on Prediction of Output in Oilfield Using Multiple Linear Regression
title_sort study on prediction of output in oilfield using multiple linear regression
publishDate 2011
url http://eprints.utp.edu.my/8283/1/IJAST-Prediction_of_output_in_oilfield.pdf
http://eprints.utp.edu.my/8283/
_version_ 1741196115839025152
score 11.62408

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