A stochastic optimization model for short-term production of offshore oil platforms with satellite wells using gas lift

Carlos Gamboa (), Thuener Silva, Davi Valladão, Bernardo K. Pagnoncelli, Tito Homem- de-Mello, Bruno Vieira and Alex Teixeira
Additional contact information
Carlos Gamboa: Industrial Engineering Department, PUC-Rio
Thuener Silva: Industrial Engineering Department, PUC-Rio
Davi Valladão: Industrial Engineering Department, PUC-Rio
Bernardo K. Pagnoncelli: Universidad Adolfo Ibáñez
Tito Homem- de-Mello: Universidad Adolfo Ibáñez
Bruno Vieira: CENPES, Petrobras
Alex Teixeira: CENPES, Petrobras

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 28, issue 3, No 2, 549-574

Abstract: Abstract Continuous gas lift is a popular method to enhance productivity in offshore oil platforms. We propose a steady-state two-stage stochastic programming model to maximize production, where the first-stage injection level determines the production potential, while recourse actions ensure capacity and platform constraints for each uncertainty realization. In particular, we develop a concave approximation of the performance curve that incorporates uncertainty in the water cut (WC) and gas–oil ratio (GOR). We generate WC and GOR realizations using a two-step data-driven approach: we extrapolate the trends using a $$\ell _1$$ ℓ 1 -filter, and bootstrap historical deviations to generate future realizations of WC and GOR. We present numerical results for the sample average approximation of the problem and assess the solution quality using standard techniques in the literature. Our numerical results suggest that taking uncertainty into account in the problem can lead to considerable gains.

Keywords: Oil production optimization; Continuous gas lift; Two-stage stochastic programming; Sample average approximation; 97M50; 90C15; 62M10 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11750-020-00547-0

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