摘要
The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.
The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.
