Dynamic risk evolution analysis for in-situ combustion incidents of offshore heavy oil recovery

被引:0
|
作者
Wu, Shengnan [1 ,2 ]
Liu, Tianqi [1 ,2 ]
Zhang, Laibin [1 ,2 ]
Liu, Yiliu [3 ]
机构
[1] China Univ Petr, Coll Safety & Ocean Engn, Changping Fuxue Rd 18, Beijing, Peoples R China
[2] Minist Emergency Management, Key Lab Oil & Gas Safety & Emergency Technol, Beijing, Peoples R China
[3] Norwegian Univ Sci & Technol, Dept Mech & Ind Engn, Trondheim, Norway
关键词
Dynamic Bayesian Network (DBN); In-situ combustion incidents; Dynamic risk analysis; Prediction of risk evolution; Root cause reasoning; MODEL; CORROSION; SAFETY;
D O I
10.1016/j.psep.2024.08.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In-situ combustion for offshore heavy oil involves significant risk factors related to ignition, gas injection, and corrosion prevention, especially under challenging operating conditions. If not properly managed, these risks can lead to explosions in injection or production wells. This paper proposes a hybrid HDBN-based risk analysis method to estimate the probability of explosions during the three critical phases of in-situ combustion and to diagnose key risk factors contributing to such incidents. The method introduces new bootstrap terms to in-situ combustion and constructs a hybrid DBN to capture the dynamic behavior of explosion incidents. It incorporates the Delphi method and triangular Pythagorean fuzzy theory to address data scarcity and uncertainty through affiliation and uncertainty functions. A key aspect of the proposed method is the graded quantification of damage to the casing due to corrosion and thermal stresses. A case study of a well in Liaodong Bay, Bohai Sea, demonstrates the feasibility of this method. The study captures dynamic risk evolution characteristics during three stages of in-situ combustion and conducts sensitivity analysis to obtain key risk factors such as "bottom high temperature" and "gas corrosion".
引用
收藏
页码:1355 / 1371
页数:17
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