System hazard identification prediction prevention (SHIPP) methodology predictive accident modeling approach

A process accident occurs as a result of a sequence of events initiated by deviation in the process parameters and/or failure or malfunctioning of one or more components. Many process accidents are controlled and mitigated before they escalate to major events. Unfortunately some do go on to produce catastrophic consequence s. As the size and complexity of processing facilities increase, the potential risk posed by accidents is increasing. Operational safety could be improved by giving emphasis to the prevention of incidents, rather than relying on control and mitigative measures. This method is referred to as an "inherently safer approach ". To prevent major, though infrequent, event occurrence, it is important to consider accident precursors (symptoms of hazards) such as operational deviations, mishaps, and near misses, in order to prevent abnormal events at source rather than controlling or mitigating them. -- The objective of this research is to present a novel methodology known as System Hazards Identification, Prediction and Prevention (SHIPP) for process accident modeling and prevention. In this methodology, a new process accident model with predictive capabilities is developed. The SHIPP is a systematic methodology to identify, evaluate, and model the accident process, thereby predicting and preventing future accidents in a process facility. In this methodology, process hazard accidents are modeled using safety barriers. The model relies on process history, accident precursor information, and accident causation modeling. The fault tree and event tree analysis techniques are used to enhance the accident model and to represent a holistic picture of the cause-consequence mechanism of the accident process. Quantitative analysis has two aspects: updating and prediction. The model is able to capture the process operational behaviour, and update the accident likelihood using the Bayesian updating mechanism. The predictive model forecasts the probability of a number of abnormal events occurring in the next time interval. Application of this methodology is demonstrated by a case study. The quantitative results demonstrate that the probabilities of abnormal events dramatically change over time as new information is observed, and the adequacy and accuracy of model prediction is better in short term prediction rather than long term prediction. -- Through the SHIPP methodology, qualitative and quantitative analyses provide insight to identify critical safe ty barriers and functions, and determine the likelihood of failure of these measures. Combining management oversight, human factor and engineering analyses, the SHIPP methodology provides a comprehensive, systematic approach to manage a process system risk

Accident modeling and risk assessment framework for safety critical decision-making: application to deepwater drilling operation

Rising global energy demand is encouraging oil companies to invest in deepwater drilling. However, there are numerous engineering and safety challenges involved in this activity. The BP Deepwater Horizon accident (Macondo well blowout) has raised serious concerns about the safety of deepwater drilling. The major reasons for such a catastrophic blowout event are the lack of continuous assessment of risk and the lack of risk-based decision making to take timely and adequate preventive actions. The present work proposes an accident modeling and risk assessment framework based on accident precursors (early warnings). This framework uses the system hazard identification, prediction and prevention methodology to model the unwanted situation. The proposed risk assessment framework generates results that can be used to: (1) analyze the dynamic performance of safety barriers, (2) analyze the probability of occurrence of different severity levels, (3) analyze the dynamic risk profile of different severity levels and the aggregated risk profile, and (4) help to make safety-critical decisions based on aggregated risk profile. The present work provides an assessment of offshore deepwater drilling risk assessment and a basis to make timely and precise safety critical decisions. The risk assessment methodology is demonstrated on the Macondo well blowout accident. This case study highlighted the applicability and advantages of using the proposed method in drilling operations. </jats:p

Multiphase Hydrate Induction Experiment in a Subsea Pipeline

Formation of hydrates is one of the many challenges faced in the offshore oil and gas industry. It may result in blockage of subsea pipelines and equipment, which may result in flow line rupture and process accident. Although extensive experiment study is conducted to better understand the nucleation of hydrates and their slug flow behavior in gas-water/oil systems. However, there is limited understanding regarding the effects of multiphase fluid dynamics and geometric scales on the formation/growth of hydrates in subsea pipelines. In this paper a multiphase lab scale flow loop set-up is proposed to study the effects of pipe diameter, wall roughness, solid particles and hydrodynamic properties. The multiphase development length of a pipe for varying geometric and flow parameters is also analyzed considering three phase mixture properties. This study will help in identifying the accurate development length for gas/liquid/solid multiphase flow.</jats:p