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Reservoir performance prediction becomes an important consideration for making the proper field development <br /> <br /> and optimization plan. In petroleum industries there is a need to estimate performance prediction for large-scale <br /> <br /> reservoir. The capacitance...

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Main Author: AULIA JUSTISIANANTO (NIM : 12214098), AHMAD
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/25161
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:25161
spelling id-itb.:251612018-09-03T13:37:29Z#TITLE_ALTERNATIVE# AULIA JUSTISIANANTO (NIM : 12214098), AHMAD Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/25161 Reservoir performance prediction becomes an important consideration for making the proper field development <br /> <br /> and optimization plan. In petroleum industries there is a need to estimate performance prediction for large-scale <br /> <br /> reservoir. The capacitance-resistive model (CRM) which regarded as a powerful method to quick-look the <br /> <br /> reservoir performance, has recently been used in many reservoirs to simulate the waterflooding program but only <br /> <br /> in single-layer reservoir case. <br /> <br /> The modification of CRM equation and fractional oil model that is suitable for multilayer reservoir case are <br /> <br /> developed in this study. A simple analytical method to estimate layered interwell connectivity, time response <br /> <br /> delay, and fractional model coefficient is introduced in order to obtain specific solution for multilayer CRM and <br /> <br /> fractional flow model equations. <br /> <br /> Both multilayer CRMIP and multilayer empirical fractional oil model has successfully validated with two layers, <br /> <br /> three layers, and four layers of synthetical reservoir case. Validation results show good agreement between the <br /> <br /> calculated rate with the actual rate from historical production data. The proposed method in this study is very <br /> <br /> attractive in understanding the behavior and property of layer-scale reservoir. Simple approach that is used in this <br /> <br /> model, make the new powerful and easy to use of multilayer reservoir simulation tool. <br /> 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
description Reservoir performance prediction becomes an important consideration for making the proper field development <br /> <br /> and optimization plan. In petroleum industries there is a need to estimate performance prediction for large-scale <br /> <br /> reservoir. The capacitance-resistive model (CRM) which regarded as a powerful method to quick-look the <br /> <br /> reservoir performance, has recently been used in many reservoirs to simulate the waterflooding program but only <br /> <br /> in single-layer reservoir case. <br /> <br /> The modification of CRM equation and fractional oil model that is suitable for multilayer reservoir case are <br /> <br /> developed in this study. A simple analytical method to estimate layered interwell connectivity, time response <br /> <br /> delay, and fractional model coefficient is introduced in order to obtain specific solution for multilayer CRM and <br /> <br /> fractional flow model equations. <br /> <br /> Both multilayer CRMIP and multilayer empirical fractional oil model has successfully validated with two layers, <br /> <br /> three layers, and four layers of synthetical reservoir case. Validation results show good agreement between the <br /> <br /> calculated rate with the actual rate from historical production data. The proposed method in this study is very <br /> <br /> attractive in understanding the behavior and property of layer-scale reservoir. Simple approach that is used in this <br /> <br /> model, make the new powerful and easy to use of multilayer reservoir simulation tool. <br />
format Final Project
author AULIA JUSTISIANANTO (NIM : 12214098), AHMAD
spellingShingle AULIA JUSTISIANANTO (NIM : 12214098), AHMAD
#TITLE_ALTERNATIVE#
author_facet AULIA JUSTISIANANTO (NIM : 12214098), AHMAD
author_sort AULIA JUSTISIANANTO (NIM : 12214098), AHMAD
title #TITLE_ALTERNATIVE#
title_short #TITLE_ALTERNATIVE#
title_full #TITLE_ALTERNATIVE#
title_fullStr #TITLE_ALTERNATIVE#
title_full_unstemmed #TITLE_ALTERNATIVE#
title_sort #title_alternative#
url https://digilib.itb.ac.id/gdl/view/25161
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