Dynamic Blowout Risk Analysis Using Loss Functions

Abstract

Most risk analysis approaches are static; failing to capture evolving conditions. Blowout, the most feared accident during a drilling operation, is a complex and dynamic event. The traditional risk analysis methods are useful in the early design stage of drilling operation while falling short during evolving operational decision making. A new dynamic risk analysis approach is presented to capture evolving situations through dynamic probability and consequence models. The dynamic consequence models, the focus of this study, are developed in terms of loss functions. These models are subsequently integrated with the probability to estimate operational risk, providing a real-time risk analysis. The real-time evolving situation is considered dependent on the changing bottom-hole pressure as drilling progresses. The application of the methodology and models are demonstrated with a case study of an offshore drilling operation evolving to a blowout.

A Bayesian‐loss function‐based method in assessing loss caused by ship‐source oil spills in the arctic area

“…It is noted that there are different forms of loss functions, but the fundamental idea is finding the difference between current output of a particular process and what is expected given the ideal conditions of the system (Abimbola & Khan, 2018; Khan et al., 2016). Other forms of loss function include regression loss function, mean squared logarithmic loss function, binary classification loss functions, and multi‐class classification loss functions among others (Khan et al., 2016).…”

“…In terms of the loss function, Zadakbar et al ( 2015) developed a loss function-based methodology which could be used for loss evaluation in a situation like the BP Texas City accident and the Knock-Out Drum. Similarly, Abimbola and Khan (2018) also proposed a loss functionbased consequence model for estimating the risk due to a blowout during oil and gas production. The relevant works related to Bayesian-based methodological works and loss function-based works are presented in Tables 1 and 2.…”

Real‐Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy‐Grey Relation Analysis

“…Moreover, there is very little research employing dynamic state-of-the-art correlation analysis methods for tailings dam collapses. Most traditional risk analysis methods are static and fail to capture the states of risk evolution [29]. However, the consequences of tailings dam breaks are dynamic events and circumstances beyond control.…”

Analysis of the Applicability of a Risk Quantitative Evaluation Method to High Temperature-Pressure Drilling Engineering

“…However, this region's drilling and completion construction is faced with problems such as high temperature and high pressure, narrow safety density windows, and strong uncertainty of formation pressure information. In construction, situations such as well kick, well circulation, borehole collapse, and pipe sticking frequently occur, seriously restricting the exploration and development process [1][2][3]. Risk assessment of drilling engineering is an essential means to ensure safe construction.…”