DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD

Gas well flowing pressure is very important in production for examples to predict flow rate, optimize completion string, and design artificial lift equipment. There are several method to determine well flowing pressure. These methods often result in flowing pressure with large error percentage comp...

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Bibliographic Details
Main Author:	ALIF
Format:	Final Project
Language:	Indonesia
Subjects:	Pertambangan dan operasi berkaitan
Online Access:	https://digilib.itb.ac.id/gdl/view/64670
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:64670
spelling	id-itb.:646702022-06-02T09:56:54ZDETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD ALIF Pertambangan dan operasi berkaitan Indonesia Final Project equation, flowing pressure, multi variable regression, pressure loss, vertical well, wet gas INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/64670 Gas well flowing pressure is very important in production for examples to predict flow rate, optimize completion string, and design artificial lift equipment. There are several method to determine well flowing pressure. These methods often result in flowing pressure with large error percentage compare to measured flowing pressure in field. In addition, these methods are too difficult to be implemented with manual calculation. In this final project, a new equation is developed. This equation can be used to determine well flowing pressure for wet gas. This equation is developed by using multi variables regression method. The proposed equation can be used easily to calculate pressure loss in vertical well and result in smaller error percentage. In order to avoid large error percentage when using the proposed equation, in this final project, some limit has been set up where the proposed equation still have a great accuracy result text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
topic	Pertambangan dan operasi berkaitan
spellingShingle	Pertambangan dan operasi berkaitan ALIF DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
description	Gas well flowing pressure is very important in production for examples to predict flow rate, optimize completion string, and design artificial lift equipment. There are several method to determine well flowing pressure. These methods often result in flowing pressure with large error percentage compare to measured flowing pressure in field. In addition, these methods are too difficult to be implemented with manual calculation. In this final project, a new equation is developed. This equation can be used to determine well flowing pressure for wet gas. This equation is developed by using multi variables regression method. The proposed equation can be used easily to calculate pressure loss in vertical well and result in smaller error percentage. In order to avoid large error percentage when using the proposed equation, in this final project, some limit has been set up where the proposed equation still have a great accuracy result
format	Final Project
author	ALIF
author_facet	ALIF
author_sort	ALIF
title	DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
title_short	DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
title_full	DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
title_fullStr	DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
title_full_unstemmed	DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD
title_sort	determination of wet gas well flowing pressure using multivariables regression method
url	https://digilib.itb.ac.id/gdl/view/64670
_version_	1822932512109756416

DETERMINATION OF WET GAS WELL FLOWING PRESSURE USING MULTIVARIABLES REGRESSION METHOD

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