Abstract:

To achieve dynamic risk management and control during the CO₂ injection process in CCUS oilfields and prevent CO₂ leakage acidents, a dynamic assessment method for the probability of high-risk scenarios was proposed. Firstly, a novel improved FPN model was developed by integrating a three-parameter Weibull distribution model for equipment failure probability based on Grey Model (GM) and Support Vector Machine (SVM) with FPN model. Subsequently, the risk analysis was conducted on the above ground CO₂ injection system of CCUS process. The CO₂ leakage accident chain was established to quantitatively predict the accident occurrence probability. The dynamic characteristic of equipment failure probability changing with time (t) and the impact of protection layers on risk were taken into account by the improved FPN. The results indicate that when t=500 h, the risk exhibits an exponential increase. The safety valve is identified as the protection layer with the highest importance. When t=303 days, the system's residual risk reaches the PetroChina risk acceptance criterion of 1×10^-5, indicating that the system risk becomes unacceptable beyond this point. It is recommended to add a high-high level interlock protection layer, which extends the time until system risk becomes unacceptable to 5 832 days, thereby significantly reducing maintenance frequency and costs.

Key words: carbon capture utilization and storage(CCUS), above ground injection system, high-risk scenarios, probability of occurrence, dynamic quantitative evaluation, fuzzy petri net(FPN)