A quantum computing-based numerical method of mixed-integer optimal control problems under uncertainty for alkali–surfactant–polymer flooding. Issue 3 (4th March 2021)

• Record Type: Journal Article
• Authors: Liu, Zhe; Li, Shurong; Ge, Yulei
• Is Part Of: Engineering optimization. Volume 53:Issue 3(2021)
• Page Start: 531
• Page End: 550
• Publication Date: 2021-03-04
• Subjects: Mixed-integer optimal control problem -- ASP flooding -- improved possibilistic programming algorithm -- quantum annealing -- quantum ant colony algorithm; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2020.1741568
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This article presents a numerical method based on quantum computing to solve two unresolved key issues for alkali–surfactant–polymer (ASP) flooding in oil exploitation: uncertainties affecting development planning and a switch control regarding injection oil wells. First, a fuzzy multi-objective mixed-integer optimal control model describing the mechanism of ASP flooding is established. Then, an improved possibilistic programming algorithm is presented to remove fuzziness and transform the model into a deterministic single-objective mixed-integer nonlinear programming (MINLP) model. On this basis, a bi-level quantum computing algorithm including quantum annealing and quantum ant colony algorithm is proposed to solve the MINLP and acquire the optimal mixed-integer control variables. The superiority of the proposed algorithm is verified by testing a number of benchmark examples. Finally, the numerical method based on quantum computing is adopted to solve successfully a mixed-integer optimal control problem for ASP flooding under uncertainty.