Well Placement Optimization Using Simulated Annealing and Genetic Algorithm

2019 ◽  
Author(s):  
Aisha Diggi Tukur ◽  
Petrus Nzerem ◽  
Nhoyidi Nsan ◽  
Ikechukwu Stanley Okafor ◽  
Abdullahi Gimba ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization

Infill well placement optimization in coal bed methane reservoirs using genetic algorithm

Fuel ◽  
2013 ◽  
Vol 111 ◽  
pp. 248-258 ◽  
Author(s):  
Alireza Salmachi ◽  
Mohammad Sayyafzadeh ◽  
Manouchehr Haghighi
Keyword(s):  
Genetic Algorithm ◽  
Coal Bed ◽  
Coal Bed Methane ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization

Well Placement Optimization Using a Genetic Algorithm With Nonlinear Constraints

2009 ◽  
Author(s):  
Alexandre Anoze Emerick ◽  
Eugenio Silva ◽  
Bruno Messer ◽  
Luciana Faletti Almeida ◽  
Dilza Szwarcman ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Constraints ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization

scholarly journals A Modified Niching Crow Search Approach to Well Placement Optimization

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 857
Author(s):  
Jahedul Islam ◽  
Md Shokor A. Rahaman ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Ahshanul Hoqe ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Multimodal Optimization ◽  
Test Functions ◽  
Well Placement ◽  
Suggested Approach ◽  
Placement Optimization ◽  
Well Placement Optimization ◽  
Search Approach

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.

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