Well drilling riser fracture failure risk evaluation method based on fuzzy Bayesian network

A Bayesian network and risk assessment technology, applied in the field of deepwater drilling riser fracture failure risk assessment, to achieve the effect of accurate probabilistic reasoning and updating, and reducing possibility

Pending Publication Date: 2022-05-31
TIANJIN UNIV
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Problems solved by technology

[0004] Risk analysis is an important tool to prevent accidents and formulate measures. However, from the perspective of risk, there are few analyzes on the fractu

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  • Well drilling riser fracture failure risk evaluation method based on fuzzy Bayesian network
  • Well drilling riser fracture failure risk evaluation method based on fuzzy Bayesian network
  • Well drilling riser fracture failure risk evaluation method based on fuzzy Bayesian network

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Embodiment Construction

[0020] The specific structure and implementation process of this solution will be described in detail below through specific embodiments and accompanying drawings.

[0021] Such as figure 1 As shown, in one embodiment of the present invention, a fuzzy Bayesian network deepwater drilling riser fracture failure risk assessment method based on Cook's classical model is disclosed, including the following steps:

[0022] Step 1, construction of Bayesian network. First, analyze the root cause of the deepwater drilling riser fracture failure accident, identify the event, and complete the modeling of the fault tree; convert the fault tree model into a Bayesian network structure, and convert it into a conditional probability table through the "and / or" logic gate The way to construct the logical relationship of Bayesian network nodes.

[0023] Among them, through the analysis of the deep-water drilling riser fracture failure accident, the event of "deep-water drilling riser fracture f...

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Abstract

The invention relates to a well drilling riser fracture failure risk evaluation method based on a fuzzy Bayesian network, and the method comprises the following steps: constructing a Bayesian network: analyzing the root cause of a deepwater well drilling riser fracture failure accident, recognizing the event of the deepwater well drilling riser fracture failure accident, determining a top event, and determining the top event of the deepwater well drilling riser fracture failure accident; modeling of a fault tree is completed according to an intermediate event and a basic event; converting the fault tree model into a Bayesian network structure; evaluation data acquisition and conversion: determining expert weights based on a Kuke classical model, and realizing aggregation of evaluation suggestions of different experts on the occurrence possibility of the basic event; fuzzy data obtained through expert opinion aggregation is converted into a prior failure probability through defuzzification; and performing Bayesian network reasoning and sensitivity analysis.

Description

technical field [0001] The invention relates to the technical field of fracture failure risk assessment of deepwater drilling risers, in particular to a fuzzy Bayesian network deepwater drilling riser fracture failure risk assessment method based on Cook's classical model. Background technique [0002] The deepwater drilling riser is the key connection between the subsea wellhead and the floating drilling unit. However, the drilling riser system is affected by various complex loads such as strong winds and waves, which greatly affects the importance of the drilling riser. With the development of oil and gas exploration and development in the direction of deep water and ultra-deep water, the possibility of accidents in drilling riser system components is increasing. Drilling riser operations have the characteristics of high safety risks and high accident rates. Accidents in the drilling riser system will lead to pollutant discharge, drilling shutdown, and even catastrophic co...

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Application Information

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IPC IPC(8): G06F30/27G06N5/04G06Q50/02G06F111/08G06F119/02
CPCG06F30/27G06N5/046G06Q50/02G06F2111/08G06F2119/02
Inventor 余杨杨九余建星叶超涵吴世博高涵韬马文韬曾庆泽
Owner TIANJIN UNIV
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