CHEN Shuangqing. Progress and prospect of optimization methods for oil and gas field surface engineering in the context of carbon peaking and carbon neutrality[J]. Oil & Gas Storage and Transportation, 2022, 41(7): 765-772. DOI: 10.6047/j.issn.1000-8241.2022.07.002
Citation: CHEN Shuangqing. Progress and prospect of optimization methods for oil and gas field surface engineering in the context of carbon peaking and carbon neutrality[J]. Oil & Gas Storage and Transportation, 2022, 41(7): 765-772. DOI: 10.6047/j.issn.1000-8241.2022.07.002

Progress and prospect of optimization methods for oil and gas field surface engineering in the context of carbon peaking and carbon neutrality

  • Most of the energy-saving and efficiency-improving problems of oil and gas field surface engineering can be attributed to the optimization of conditional extreme values. Applying the optimization methods for the optimal design of the production and construction schemes for oil and gas field surface engineering has become an important supporting way to achieve the goal of "dual carbon". Herein, the important progress of optimization research for the gathering, water injection and supporting engineering systems of oil and gas field surface engineering was summarized. Meanwhile, the theoretical results of the overall optimization for oil and gas field surface engineering in the new stage of energy-saving and efficiency-improving, as well as the optimization of surface and underground integration, were reviewed, and the problems to be solved urgently in the research of optimization models and solution methods were discussed. In the context of stricter carbon reduction policy and increasing difficulty in energy-saving and efficiency-improving, the development direction of optimization methods for oil and gas field surface engineering was prospected. Moreover, it was pointed out that the "artificial intelligence plus (AI+)" research by integrating artificial intelligence and big data would be an important innovation direction in the future, and efforts could be made in the establishment of generalized optimization models, the research on data mining-driven optimization methods, and the construction of dynamic optimization methods. In general, the research results could provide reference for the intelligent development of optimization methods and technologies for oil and gas field surface engineering, thus promoting the energy conservation and emission reduction in oil and gas fields.
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