Anais Estendidos Do XXXV Conference on Graphics, Patterns and Images (SIBGRAPI Estendido 2022) 2022
DOI: 10.5753/sibgrapi.est.2022.23277
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Predicting oil field production using the Random Forest algorithm

Abstract: Precisely forecasting oil field performance is essential in oil reservoir planning and management. Nevertheless, forecasting oil production is a complex nonlinear problem due to all geophysical and petrophysical properties that may result in different effects with a bit of change. All decisions to be made during an exploitation project needs to be made considering different efficient algorithms to simulate data, providing robust scenarios to lead to the best deductions. To reduce the uncertainty in the simulat… Show more

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Cited by 2 publications
(2 citation statements)
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“…Equation (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) shows the solution for the system (2-12) considering the equation (2-1) and (2-2). We can see that the solution behaves, as seen in Figure Pressure derivative curve indicates when a transition between two regions with different permeability occurs.…”
Section: Solutionsmentioning
confidence: 99%
See 1 more Smart Citation
“…Equation (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) shows the solution for the system (2-12) considering the equation (2-1) and (2-2). We can see that the solution behaves, as seen in Figure Pressure derivative curve indicates when a transition between two regions with different permeability occurs.…”
Section: Solutionsmentioning
confidence: 99%
“…Gonçalves et al (2022) [6] discussed the use of Random Forest algorithm to forecast daily oil production in reservoir. The authors proposed to predict a one-time step production using the Volve oil field dataset to conduct experiments.…”
Section: Introductionmentioning
confidence: 99%