Method comparison for gas lift allocation aimed at multiple gas lift wells
Continuous gas lift source is essential which allows each of gas lift wells to produce. However, the problem is the amount of total gas lift availability for a field is typically limited. Therefore engineers have to use the total available gas to allocate to all or selected gas lift wells in the fie...
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my-utm-ep.860202020-08-30T08:49:32Z Method comparison for gas lift allocation aimed at multiple gas lift wells 2018 Razak, Mohd. Firdaus TP Chemical technology Continuous gas lift source is essential which allows each of gas lift wells to produce. However, the problem is the amount of total gas lift availability for a field is typically limited. Therefore engineers have to use the total available gas to allocate to all or selected gas lift wells in the field. One of the approaches is to apply the same amount of gas lift injected for each well in a field, but this method is not optimum especially for wells that have different gas lift performance. This study has been executed to compare different methods in the curve based model for gas lift allocation aimed multiple wells to maximize the total production rate in a field. In the curve based model, three methods of optimization have studied which are Binary Integer Linear Optimization, General Reduced Gradient (GRG) Optimization, and Evolutionary Optimization. General Allocation Program (GAP) software has been used to model and compute the optimum allocation and has used as a benchmark in this thesis. Result confirmed that optimize allocation can deliver more production compare to the average amount of gas lift method. Additionally, best curve fit equation in the curve based method for non-linear equation has been computed to represent the gas lift performance curve. Alarcon equation is the best curve fit equation compared to Hamedi, Haiquan, and Viera. GRG Optimization has the fastest computing time and as accurate as an Evolutionary Optimization method. Binary Integer Linear intuitively has provided better gas lift allocation comparing to the GRG and Evolutionary Method. 2018 Thesis http://eprints.utm.my/id/eprint/86020/ http://eprints.utm.my/id/eprint/86020/1/MohdFirdausRazakMSChe2018.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:131606 masters Universiti Teknologi Malaysia, Faculty of Engineering - School of Chemical & Energy Engineering Faculty of Engineering - School of Chemical & Energy Engineering |
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Universiti Teknologi Malaysia |
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UTM Institutional Repository |
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English |
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TP Chemical technology |
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TP Chemical technology Razak, Mohd. Firdaus Method comparison for gas lift allocation aimed at multiple gas lift wells |
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Continuous gas lift source is essential which allows each of gas lift wells to produce. However, the problem is the amount of total gas lift availability for a field is typically limited. Therefore engineers have to use the total available gas to allocate to all or selected gas lift wells in the field. One of the approaches is to apply the same amount of gas lift injected for each well in a field, but this method is not optimum especially for wells that have different gas lift performance. This study has been executed to compare different methods in the curve based model for gas lift allocation aimed multiple wells to maximize the total production rate in a field. In the curve based model, three methods of optimization have studied which are Binary Integer Linear Optimization, General Reduced Gradient (GRG) Optimization, and Evolutionary Optimization. General Allocation Program (GAP) software has been used to model and compute the optimum allocation and has used as a benchmark in this thesis. Result confirmed that optimize allocation can deliver more production compare to the average amount of gas lift method. Additionally, best curve fit equation in the curve based method for non-linear equation has been computed to represent the gas lift performance curve. Alarcon equation is the best curve fit equation compared to Hamedi, Haiquan, and Viera. GRG Optimization has the fastest computing time and as accurate as an Evolutionary Optimization method. Binary Integer Linear intuitively has provided better gas lift allocation comparing to the GRG and Evolutionary Method. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Razak, Mohd. Firdaus |
| author_facet |
Razak, Mohd. Firdaus |
| author_sort |
Razak, Mohd. Firdaus |
| title |
Method comparison for gas lift allocation aimed at multiple gas lift wells |
| title_short |
Method comparison for gas lift allocation aimed at multiple gas lift wells |
| title_full |
Method comparison for gas lift allocation aimed at multiple gas lift wells |
| title_fullStr |
Method comparison for gas lift allocation aimed at multiple gas lift wells |
| title_full_unstemmed |
Method comparison for gas lift allocation aimed at multiple gas lift wells |
| title_sort |
method comparison for gas lift allocation aimed at multiple gas lift wells |
| granting_institution |
Universiti Teknologi Malaysia, Faculty of Engineering - School of Chemical & Energy Engineering |
| granting_department |
Faculty of Engineering - School of Chemical & Energy Engineering |
| publishDate |
2018 |
| url |
http://eprints.utm.my/id/eprint/86020/1/MohdFirdausRazakMSChe2018.pdf |
| _version_ |
1747818481486659584 |