[vc_empty_space][vc_empty_space]
Oil production optimization in a cluster of gas lift wells system
Saepudin D.a, Sukarno P.b, Soewono E.b, Sidarto K.A.b, Gunawan A.Y.b
a Program Studi Ilmu Komputasi, Insitut Teknologi Telkom, Indonesia
b Drilling and Production Engineering and Oil and Gas Management Research Group, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]In this study, optimization problems for a cluster of gas lift wells system, which are coupled with a production and gas injection manifold, are discussed. The main goal is to determine the optimum gas injection rate for each well that maximizing the total oil production rate. The total gas for injection is constrained by the maximum availability and the total liquid production rate is constrained by separator capacity. The mathematical model for gas lift problem could be written as a boundary value problem, where the two parameter family non linear differential equation of the boundary value problem represents steady flow equation along the tubing, satisfying wellhead pressure and bottom hole pressure as boundary conditions. Oil production rate is a non-linear function of gas injection rate, which is given implicitly from the gas lift model. A computation scheme based on genetic algorithms is developed to solve the constrained optimization problem with and without considering separator capacity. Our results show quite good estimation for optimum solution. This approach is also flexible to accommodate separator capacity constraints. © 2010 Asian Network for Scientific Information.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Capacity constraints,Constrained optimi-zation problems,Injection manifolds,Nonlinear differential equation,Nonlinear functions,Oil-production rates,Optimization problems,Penalty approach[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Constrained optimization,Gas lift,Genetic algorithms,Penalty approach[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.3923/jas.2010.1705.1713[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]