Efficient Particle Swarm Optimization of Well Placement to Enhance Oil Recovery Using a Novel Streamline Based Objective FunctionSource: Journal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005::page 52903DOI: 10.1115/1.4032547Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: One of the main reservoir development plans is to find optimal locations for drilling new wells in order to optimize cumulative oil recovery. Reservoir simulation is a necessary tool to study different configurations of well locations to investigate the future of the reservoir and determine the optimal places for well drilling. Conventional wellknown numerical methods require modern hardware for the simulation and optimization of large reservoirs. Simulation of such heterogeneous reservoirs with complex geological structures with the streamlinebased simulation method is more efficient than the common simulation techniques. Also, this method by calculation of a new parameter called “timeofflight†(TOF) offers a very useful tool to engineers. In the present study, TOF and distribution of streamlines are used to define a novel function which can be used as the objective function in an optimization problem to determine the optimal locations of injectors and producers in waterflooding projects. This new function which is called “well location assessment based on TOF†(WATOF) has this advantage that can be computed without full time simulation, in contrast with the cumulative oil production (COP) function. WATOF is employed for optimal well placement using the particle swarm optimization (PSO) approach, and its results are compared with those of the same problem with COP function, which leads to satisfactory outcomes. Then, WATOF function is used in a hybrid approach to initialize PSO algorithm to maximize COP in order to find optimal locations of water injectors and oil producers. This method is tested and validated in different 2D problems, and finally, the 3D heterogeneous SPE10 reservoir model is considered to search locations of wells. By using the new objective function and employing the hybrid method with the streamline simulator, optimal well placement projects can be improved remarkably.
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| contributor author | Siavashi, Majid | |
| contributor author | Tehrani, Mohammad Rasoul | |
| contributor author | Nakhaee, Ali | |
| date accessioned | 2017-05-09T01:27:44Z | |
| date available | 2017-05-09T01:27:44Z | |
| date issued | 2016 | |
| identifier issn | 0195-0738 | |
| identifier other | jert_138_05_052903.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/160896 | |
| description abstract | One of the main reservoir development plans is to find optimal locations for drilling new wells in order to optimize cumulative oil recovery. Reservoir simulation is a necessary tool to study different configurations of well locations to investigate the future of the reservoir and determine the optimal places for well drilling. Conventional wellknown numerical methods require modern hardware for the simulation and optimization of large reservoirs. Simulation of such heterogeneous reservoirs with complex geological structures with the streamlinebased simulation method is more efficient than the common simulation techniques. Also, this method by calculation of a new parameter called “timeofflight†(TOF) offers a very useful tool to engineers. In the present study, TOF and distribution of streamlines are used to define a novel function which can be used as the objective function in an optimization problem to determine the optimal locations of injectors and producers in waterflooding projects. This new function which is called “well location assessment based on TOF†(WATOF) has this advantage that can be computed without full time simulation, in contrast with the cumulative oil production (COP) function. WATOF is employed for optimal well placement using the particle swarm optimization (PSO) approach, and its results are compared with those of the same problem with COP function, which leads to satisfactory outcomes. Then, WATOF function is used in a hybrid approach to initialize PSO algorithm to maximize COP in order to find optimal locations of water injectors and oil producers. This method is tested and validated in different 2D problems, and finally, the 3D heterogeneous SPE10 reservoir model is considered to search locations of wells. By using the new objective function and employing the hybrid method with the streamline simulator, optimal well placement projects can be improved remarkably. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Efficient Particle Swarm Optimization of Well Placement to Enhance Oil Recovery Using a Novel Streamline Based Objective Function | |
| type | Journal Paper | |
| journal volume | 138 | |
| journal issue | 5 | |
| journal title | Journal of Energy Resources Technology | |
| identifier doi | 10.1115/1.4032547 | |
| journal fristpage | 52903 | |
| journal lastpage | 52903 | |
| identifier eissn | 1528-8994 | |
| tree | Journal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005 | |
| contenttype | Fulltext |