RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING
The problems of cost and time inefficiency during reservoir simulation persists in designing a steam huff and puff injection scheme. Therefore, developing predictive proxy models using machine learning algorithms is a suitable solution to address this concern. This study employed polynomial regressi...
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2023
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oai:utpedia.utp.edu.my:246432024-07-30T03:19:58Z http://utpedia.utp.edu.my/id/eprint/24643/ RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING MERDEKA, MOHAMMAD GALANG TA Engineering (General). Civil engineering (General) The problems of cost and time inefficiency during reservoir simulation persists in designing a steam huff and puff injection scheme. Therefore, developing predictive proxy models using machine learning algorithms is a suitable solution to address this concern. This study employed polynomial regression (PR) and artificial neural network (ANN) models to develop predictive models of the steam huff and puff injection scheme. Using a one-well cylindrical synthetic reservoir model, a total of 6084 experimental observations were simulated, each with 28 different features as input parameters. For each experiment, cumulative oil production and maximum oil production rate were extracted as the output parameters for developing the models. Reservoir properties which could change after an injection cycle, were also modelled. The developed models were evaluated based on the fitting performance from adjusted R-square (????????????????2), the mean absolute error (MAE) and the root mean square error (RMSE). 2023-12 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24643/1/Mohammad%20Galang%20Merdeka_20000264%20%281%29.pdf MERDEKA, MOHAMMAD GALANG (2023) RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING. Masters thesis, UNSPECIFIED. |
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TA Engineering (General). Civil engineering (General) MERDEKA, MOHAMMAD GALANG RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
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The problems of cost and time inefficiency during reservoir simulation persists in designing a steam huff and puff injection scheme. Therefore, developing predictive proxy models using machine learning algorithms is a suitable solution to address this concern. This study employed polynomial regression (PR) and artificial neural network (ANN) models to develop predictive models of the steam huff and puff injection scheme. Using a one-well cylindrical synthetic reservoir model, a total of 6084 experimental observations were simulated, each with 28 different features as input parameters. For each experiment, cumulative oil production and maximum oil production rate were extracted as the output parameters for developing the models. Reservoir properties which could change after an injection cycle, were also modelled. The developed models were evaluated based on the fitting performance from adjusted R-square (????????????????2), the mean absolute error (MAE) and the root mean square error (RMSE). |
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Thesis |
author |
MERDEKA, MOHAMMAD GALANG |
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MERDEKA, MOHAMMAD GALANG |
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MERDEKA, MOHAMMAD GALANG |
title |
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
title_short |
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
title_full |
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
title_fullStr |
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
title_full_unstemmed |
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING |
title_sort |
reservoir performance prediction in steam huff and puff injection using proxy modelling |
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2023 |
url |
http://utpedia.utp.edu.my/id/eprint/24643/1/Mohammad%20Galang%20Merdeka_20000264%20%281%29.pdf http://utpedia.utp.edu.my/id/eprint/24643/ |
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1806417978210648064 |
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13.222552 |