Cloud Model for Security State Recognition Based on Factor Space

Yang, Li; Qin, Hongmei; Zhang, Jian; Su, Huawen; Li, Guoshu; Bai, Sichang

doi:10.1109/jsen.2021.3098679

Cited by 7 publications

(1 citation statement)

References 14 publications

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“…With the gradual perfection of cloud model theory, its application has gradually expanded to many areas such as data mining [15,16], decision analysis [17], and intelligent control [18]. In the field of oil and gas development, the application of the cloud model in reservoir evaluation [19], oil and gas industry control system safety status identification [20], and accident risk assessment [21,22] has proven that it can overcome the limitations of the aforementioned methods.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Asset Evaluation Method for Oil and Gas Projects

et al. 2023

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The rapid and accurate evaluation of oil and gas assets, specifically for new development projects, poses a significant challenge due to the various project types, limited data availability, brief periods for assessment and decision making, and constraints arising from varying contractual and taxation conditions, political stability, and societal factors. This study leverages the grading standards of the evaluation index system for new oil and gas field development projects, along with relevant mathematical theories and methods for project evaluation and optimization. We developed an asset evaluation approach for new oil and gas projects by analyzing the assets of six new oil and gas field development projects in Brazil. This analysis resulted in the grading and ranking of new projects, and we tested and demonstrated four asset optimization techniques. After a comparative analysis with conventional evaluation results, we established an oil and gas project asset optimization approach centered on the cloud model comprehensive evaluation and linear weighted ranking, exhibiting Kendall’s tau coefficient of 0.8667 with conventional methods. The findings suggest that the combination of the cloud model comprehensive evaluation method with the linear weighted ranking method can facilitate asset optimization for oil and gas field development projects, meeting the practical needs for fast selection among various new projects. Furthermore, this research offers a technical and theoretical foundation for rapid evaluation and decision making regarding new assets.

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