Consequence risk analysis using operating procedure event trees and dynamic simulation

Faults due to human errors cost the petrochemical industry billions of dollars every year and can have adverse environmental consequences. Unquantified human error probabilities exist during process state transitions performed each day by process operators using standard operating procedures. Managing the risks associated with operating procedures is an essential part of managing the overall safety risk. Additional operator training and safety education cannot eliminate all such faults due to human errors; therefore, we propose an operating procedure event tree (OPET) like analysis with branches and events specifically designed to perform risk analysis on operating procedures. The OPET method adapts event trees to analyze the risk due to human error while performing operating procedures. We consider human error scenarios during the procedure and determine the likely consequences by applying dynamic simulation. The modified event tree provides an estimate of the error frequencies.Operating procedure steps were developed, and potential operator faults were determined for two typical equipment switching procedures found in chemical plant operations. Then, dynamic simulation using Aspen HYSYS software was applied to determine the overpressure related consequences of each fault. Finally, the error frequencies resulting from those scenarios were analyzed using operating procedure event trees. We found that a typical ethylene plant gas header would overpressure with 0.6% frequency per manual dryer switch. Since dryer switches occur from every few days up to once per shift, these results suggest that dryer switching should be automated to ensure safe and environmentally friendly operation. Process dryer switching performed manually by operators opening and closing gate valves can be automated with control valves and a distributed control system. A sample distillation column was found to overpressure with 0.85% frequency per manual reflux pump switch.     

Fuzzy risk assessment of oil and gas offshore wells

Risk evaluation of offshore wells is a challenging task, given that much of the available data is highly uncertain and vague, and many of the mechanisms are complex and difficult to understand. Consequently, a systematic approach is required to handle both quantitative and qualitative data as well as means to update existing information when new knowledge and data become available. Each Basic Risk Item (BRI) in a hierarchical framework is expressed as a fuzzy number, which is a combination of the likelihood of a failure event and the associated failure consequence. Analytical Hierarchy Process (AHP) is used to estimate weights required for grouping non-commensurate risk sources. Evidential Reasoning (ER) is employed to incorporate new data for updating existing risk estimates. It is envisaged that the proposed approach could serve as a basis for benchmarking acceptable risks in offshore wells.     

Evacuation, escape, and rescue experiences from offshore accidents including the Deepwater Horizon

When a major hazard occurs on an installation, evacuation, escape, and rescue (EER) operations play a vital role in safeguarding the lives of personnel. There have been several major offshore accidents where most of the crew has been killed during EER operations. The major hazards and EER operations can be divided into three categories; depending on the hazard, time pressure and the risk influencing factors (RIFs). The RIFs are categorized into human elements, the installation and hazards. A step by step evacuation sequence is illustrated. The escape and evacuation sequence from the Deepwater Horizon offshore drilling platform is reviewed based on testimonies from the survivors. Although no casualties were reported as a result of the EER operations from the Deepwater Horizon, the number of survivors offers a limited insight into the level of success of the EER operations. Several technical and non-technical improvements are suggested to improve EER operations. There is need for a comprehensive analysis of the systems used for the rescue of personnel at sea, life rafts and lifeboats in the Gulf of Mexico.     

Cost-based fire risk assessment in natural gas industry by means of fuzzy FTA and ETA

Fire is the most prevalent accident in natural gas facilities. In order to assess the risk of fire in a gas processing plant, a fault tree analysis (FTA) and event tree analysis (ETA) has been developed in this paper. By utilizing FTA and ETA, the paths leading to an outcome event would be visually demonstrated. The framework was applied to a case study of processing plant in South Pars gas complex. All major underlying causes of fire accident in a gas processing facility determined through a process hazard analysis (PHA). Fuzzy logic has been employed to derive likelihood of basic events in FTA from uncertain opinion of experts. The outcome events in event tree has been simulated by computer model to evaluate their severity. In the proposed methodology the calculated risk has the unit of cost per year which allows the decision makers to discern the benefit of their investment in safety measures and risk mitigation.     

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors

INTRODUCTION: Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. METHOD: The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. RESULTS: This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. IMPACT ON INDUSTRY: "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.     

工程系统一体化安全风险模型研究

借鉴功能模拟原理,利用目标树-成功树-主逻辑图(GTST-MLD)框架,提出了一个一体化安全风险模型。该模型对关联于工程系统安全特性的目标、功能、结构、行为等因素予以综合,提供了从多层次研究解决安全问题的模型基础,克服了基于事件树/故障树模型的概率风险评估等传统方法而分别对系统结构、行为、事件进行研究的问题,支持实现在更高的系统功能层面上对系统安全性的分析研究。通过研究该模型在安全风险评估、事故因果关联分析、潜在交互作用鉴别中的应用,表明研究成果为解决复杂工程系统安全问题提供了新的分析手段。     

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

A method is presented for analysis of reliability of complex engineering systems using information from fault tree analysis and uncertainty/imprecision of data. Fuzzy logic is a mathematical tool to model inaccuracy and uncertainty of the real world and human thinking. The method can address subjective, qualitative, and quantitative uncertainties involving risk analysis. Risk analysis with all the inherent uncertainties is a prime candidate for Fuzzy Logic application. Fuzzy logic combined with expert elicitation is employed in order to deal with vagueness of the data, to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing.The proposed model is able to quantify the fault tree of LPG refuelling facility in the absence or existence of data. This paper also illustrates the use of importance measures in sensitivity analysis. The result demonstrates that the approach is an apposite for the probabilistic reliability approach when quantitative historical failure data are unavailable. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process.     

Risk perception by offshore workers on UK oil and gas platforms

This paper reports the first investigation of risk perception by workers on offshore oil and gas installations on the UK Continental Shelf, following changes in offshore safety legislation in the wake of the Piper Alpha disaster in 1988. The Offshore Safety Case regulations (Health and Safety Executive, 1992, A Guide to the Offshore Installations (Safety Case) Regulations) put the onus on the operator to identify the major hazards and to reduce the risks to As Low As is Reasonably Practicable (ALARP). The regulations specifically state that Quantitative Risk Assessments (QRA) must be used when preparing the Safety Case. However, people do not use QRA when making everyday judgements about risk; they make subjective judgements known as risk perceptions, which are influenced by a number of different factors. This study was designed to complement the extensive QRA calculations that have already been carried out in the development of Safety Cases. The aim was to measure subjective risk perception in offshore personnel and examine how this relates to the more objective risk data available, namely accident records and QRA calculations. This paper describes the Offshore Risk Perception Questionnaire developed to collect the data and reports on UK offshore workers' perceptions of the risks associated with major and minor hazards, work tasks and other activities aboard production platforms.     

Conceptual compression discussion on a multi-linear (FTA) and systematic (FRAM) method in an offshore operation’s accident modeling

Risk assessment can be classified into two broad categories: traditional and modern. This paper is aimed at contrasting the functional resonance analysis method (FRAM) as a modern approach with the fault tree analysis (FTA) as a traditional method, regarding assessing the risks of a complex system. Applied methodology by which the risk assessment is carried out, is presented in each approach. Also, FRAM network is executed with regard to nonlinear interaction of human and organizational levels to assess the safety of technological systems. The methodology is implemented for lifting structures deep offshore. The main finding of this paper is that the combined application of FTA and FRAM during risk assessment, could provide complementary perspectives and may contribute to a more comprehensive understanding of an incident. Finally, it is shown that coupling a FRAM network with a suitable quantitative method will result in a plausible outcome for a predefined accident scenario.     

Integrating flare gas with cogeneration systems: Operational risk assessment

Flare gas utilization in a cogeneration plant is an attractive proposition considering its environmental and economic incentives. Evaluation of the operational risk of integrating flare gas with cogeneration is complex due to the uncertainty in flare gas quality and process conditions. The current study delves into the change in operational risk after modifying the existing cogeneration process with the addition of fuel from flare gas. Based on the process hazards evaluation, the current study identified two critical loss control events (or top events) - boiler gas temperature exceeding operating design temperature and rich fuel mixture in the boiler firebox. The underlying causes that may contribute and lead to these loss control events were identified using fault trees and were updated to the existing cogeneration scenarios. Similarly, different consequential events that may arise from the loss control events were analysed using event trees with existing system safeguards. A Bayesian network model with its explanatory power mapped all the identified dangerous scenarios from the fault trees and event trees to predict integrated systems reliability and diagnose causal factors. Bayesian Network analysis illustrates the dynamic cause-effect relationship and determines the risk escalation due to the changes in the composition of flare gas that is fed to the boiler. The presence of a higher percentage of hydrogen (above 40 mol%) in the flare gas escalates the risk of lean air to fuel ratio in the boiler firebox and increases boiler radiation zone duty. These conditions are detrimental to the boiler firebox operation and can result in critical scenarios such as flame impingement and tube rupture. Additionally, other consequences-a steam explosion and boiler stack explosion were also investigated. However, their probability of occurrence was relatively insignificant with the given frequency of flare gas utilization in the cogeneration system.     

Risk assessment of rare events

Rare events often result in large impacts and are hard to predict. Risk analysis of such events is a challenging task because there are few directly relevant data to form a basis for probabilistic risk assessment. Due to the scarcity of data, the probability estimation of a rare event often uses precursor data. Precursor-based methods have been widely used in probability estimation of rare events. However, few attempts have been made to estimate consequences of rare events using their precursors. This paper proposes a holistic precursor-based risk assessment framework for rare events. The Hierarchical Bayesian Approach (HBA) using hyper-priors to represent prior parameters is applied to probability estimation in the proposed framework. Accident precursor data are utilized from an information theory perspective to seek the most informative precursor upon which the consequence of a rare event is estimated. Combining the estimated probability and consequence gives a reasonable assessment of risk. The assessed risk is updated as new information becomes available to produce a dynamic risk profile. The applicability of the methodology is tested through a case study of an offshore blowout accident. The proposed framework provides a rational way to develop the dynamic risk profile of a rare event for its prevention and control.     

事故树分析法在LPG储罐火灾爆炸事故中的应用

LPG(液化石油气)属于危险化学品之一,LPG储罐发生火灾爆炸的机率大,造成的损失比较严重,故对其火灾爆炸事故进行研究具有重要意义。LPG储罐爆炸根据其发生机理分为化学爆炸(燃爆)和物理爆炸两种模式。本文通过对LPG储罐燃爆﹑物理爆炸两类事故进行系统分析,建立了以LPG储罐燃爆、物理爆炸为顶事件的事故树。通过对其事故树的定性分析,得到了影响顶事件的各个最小割(径)集。通过计算底事件的结构重要度,确定了影响LPG储罐火灾爆炸事故的主要因素,并提出了相应的改进措施,进而提高LPG储罐的安全性和运行可靠性。     

Model-based information fusion investigation on fault isolation of subsea systems considering the interaction among subsystems and sensors

The offshore oil industry has expanded to deep water and Arctic. The harsh operating conditions (e.g., ice and strong wind) and increasing complicated system raise the occurrence likelihood of system faults. This requires timely fault isolation and management in the subsea system. However, the offshore oil industry mainly relies on humans to isolate faults based on alarms. With harsh operating conditions and increasing complicated system, this industry urgently needs research on more efficient fault isolation and cause diagnosis methods. Unfortunately, limited research is conducted on fault isolation method in the offshore oil industry. Furthermore, in industry 4.0 era, large amounts of information are obtained. This provides precondition for the application of information fusion technique which aims to improve diagnosis results. However, to the authors’ knowledge, information fusion has not been much studied in the fault isolation of the offshore oil industry. Moreover, the interaction of different subsystems contains valuable information. How the interaction of different subsystems can influence the fault diagnosis has not been explored. This paper proposes a Bayesian network (BN) based method for timely fault isolation and cause diagnosis for the offshore oil industry. The work fuses different information, and it also includes the dependency among different subsystems in the fault diagnosis. As an important alarm source, false alarms are also taken into account in the model. A case study on the subject of the subsea wellhead and chemical injection systems is conducted to demonstrate the functions and merits of the proposed method.     

FMEA在乙烯罐区风险分析中的应用研究

详细介绍国际上先进的风险管理方法故障类型和影响分析(FMEA)的评价理论和分析方法。为了能够在系统使用阶段进行故障类型和影响分析(FMEA),并缩减其工作量,对故障源分析过程进行改进,并对乙烯罐区进行FMEA风险评价。对乙烯罐区安全操作中的各种不期望发生事件,潜在的故障类型、故障因素、后果严重度、发生概率及风险等级进行逐个分析,并根据评价结果制定相应的风险削减措施。研究表明,FMEA不仅能保证系统运行过程的可靠性,而且通过研究导致不期望发生事件(事故)的故障源(故障类型),从源头消除故障隐患。     

民航机务维修系统安全风险监测

从人的因素、飞机的因素、环境因素和管理因素4方面分析了民航机务维修系统安全风险影响因素,结合专家调查意见建立了机务维修系统安全风险监测指标体系,并给出各个指标的含义及其衡量方法。根据机务维修系统安全风险指标及其数据特点,建立了行业机务维修系统安全风险模糊综合评价模型,并进行实例分析。结果表明,采用笔者建立的指标体系和风险模型可以方便地进行机务维修系统的安全风险评价和预警,从而找出主要的安全风险影响因素,为采取安全风险管理措施提供依据。     

On the analysis of hydrocarbon leaks in the Norwegian offshore industry

There have been several major offshore accidents in different offshore regions since 2005. In Norway there have been several very serious near-misses during the last ten years, several of which involving serious hydrocarbon leaks with catastrophic fire and explosion potential. All these severe occurrences demonstrate the importance of learning from major accident precursors in order to appraise the risk potential involved in critical offshore operations. This paper is based on analysis of about 175 hydrocarbon leaks in the period 2001–2010. Regulatory requirements in Norway are aimed at preventing as far as possible such occurrences during night time, but the analysis shows that this has been far from successful. The industry has for many years claimed that the maintenance personnel are the main group of employees involved in causing these leaks. This study has shown that leaks during the execution of maintenance and modification are less than half of the leaks, and that failures during the preparation for carrying out maintenance tasks are more frequent. Such preparations have often been conducted during night shift. The analysis gives a strong incentive to change this practice.     

A safety barrier-based accident model for offshore drilling blowouts

Blowout is one of the most serious accidents in the offshore oil and gas industry. Accident records show that most of the offshore blowouts have occurred in the drilling phase. Efficient measures to prevent, mitigate, and control offshore drilling blowouts are important for the entire offshore oil and gas industry. This article proposes a new barrier-based accident model for drilling blowouts. The model is based on the three-level well control theory, and primary and secondary well control barriers and an extra well monitoring barrier are established between the reservoir and the blowout event. The three barriers are illustrated in a graphical model that is similar to the well-known Swiss cheese model. Five additional barriers are established to mitigate and control the blowout accident, and event tree analysis is used to analyze the possible consequence chains. Based on statistical data and literature reviews, failures of each barrier are presented. These failures can be used as guidance for offshore drilling operators to become aware of the vulnerabilities of the safety barrier system, and to assess the risk related to these barriers. The Macondo accident is used as a case study to show how the new model can be used to understand the development of the events leading to the accident. The model can also be used as an aid to prevent future blowouts or to stop the escalation of events.     

氧气站类项目环境风险分析与计算

针对氧气站生产的特点,从风险评价技术导则(HJ/T169-2004)出发,进行风险识别,分析得出风险评价因子和类型,计算液氧贮罐爆炸的影响范围,并进行影响分析。风险管理主要是选址、具体防范措施、操作规程、应急预案和突发事故下的环境监测方案等方面的要求。