2021
DOI: 10.1016/j.petrol.2021.108926
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Robust integrated optimization of well placement and control under field production constraints

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Cited by 15 publications
(4 citation statements)
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“…Assuming 𝑛 𝑐 clusters, the optimum number of clusters (𝑛 𝑐 π‘œπ‘π‘‘ ) is determined by comparing the average silhouette value (𝑆𝑖𝑙 Μ…Μ…Μ…Μ… (𝑛 𝑐 )) for different numbers of clusters (𝑛 𝑐 ), where the maximum silhouette value indicates the best quality of clustering. Detailed information about the standard procedure of calculating average silhouette value can be found in Salehian, Sefat [12] and Haghighat Sefat, Elsheikh [37].…”
Section: Reservoir Model Realization Selectionmentioning
confidence: 99%
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“…Assuming 𝑛 𝑐 clusters, the optimum number of clusters (𝑛 𝑐 π‘œπ‘π‘‘ ) is determined by comparing the average silhouette value (𝑆𝑖𝑙 Μ…Μ…Μ…Μ… (𝑛 𝑐 )) for different numbers of clusters (𝑛 𝑐 ), where the maximum silhouette value indicates the best quality of clustering. Detailed information about the standard procedure of calculating average silhouette value can be found in Salehian, Sefat [12] and Haghighat Sefat, Elsheikh [37].…”
Section: Reservoir Model Realization Selectionmentioning
confidence: 99%
“…Single-level optimization frameworks have been developed to optimize only one type of control variables, such as well locations [1][2][3][4][5][6][7] or well control settings like flow rate or pressure [8][9][10][11][12][13][14][15][16][17][18]. These methods may not be appropriate where the optimization problem involves multiple levels, as they do not capture the potential correlations or interference among control variables at different levels.…”
Section: Introductionmentioning
confidence: 99%
“…However, for China, which lacks oil and gas resources, planned drilling to meet the country's demand for oil and gas resources takes precedence over achieving economic benefits. One of the pivotal steps of the field plan is to finalize the drilling schedule [ 5 ], determining the timing and the relevant number of drillingsβ€”specifically, how many wells should be drilled in a given month [ 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…To date, researchers have developed injection-production optimization models using different algorithms. βˆ’ Isebor and Durlofsky developed the particle swarm optimization–mesh adaptive direct search (PSO–MADS) hybrid optimization algorithm to determine optimal development and production plans considering the objective of maximizing oil recovery while minimizing water injection . Ahmadloo et al develop a new diagnostic model with multivariate partial least squares (PLS), response surface methodology (RSM), and artificial neural network (ANN) to improve the quality of predictions .…”
Section: Introductionmentioning
confidence: 99%