Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

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.     

基于模糊数学钻井井喷概率计算模型研究

针对目前钻井井喷风险主要是单因素定量分析或者多因素的事故树定性分析,不够全面,定量性差等问题,基于层次分析法和模糊综合评价法,建立了钻井井喷的多因素定性定量分析方法.通过层次分析法对影响钻井井喷的地质、井型井别、钻井参数和人员资质等因素进行分析,根据各因素在钻井井喷中作用大小,采用“1-9”标度法确定各因素的权重.基于模糊数学理论,采用不同的隶属度函数确定方法,建立了适合不同因素的隶属度函数,在此基础上形成了钻井井喷概率计算方法.通过实例计算表明,此模型可以预测钻井井喷的概率,符合现场实际情况,对钻井过程中预防井喷具有一定的指导借鉴作用.     

水平井油基钻井液气侵溶解气膨胀运移规律研究

天然气进入井筒并溶解于油基钻井液会对钻井安全产生潜在威胁,溶解气随钻井液运移到井口附近突然发生析出 并膨胀,使气侵早期监测及预警的难度显著增加。为了降低井喷发生概率和钻井作业风险,针对水平井油基钻井液溶解 气运移规律进行了研究。采用气液两相流模型,模拟了不同初始气侵速率情况下甲烷溶解气和游离气随钻井液在水平段 和垂直段的运移过程,得到环空中钻井液的流速变化、甲烷析出过程、井筒环空气液两相流流型变化、泥浆池增量随时 间变化和截面含气率沿程分布等规律。模拟结果表明,油基钻井液发生气侵时的初始进气率存在临界值;在小气侵速率 情况下,侵入环空的甲烷将以溶解气的形式运移到井口,在井口分离释放,对钻井安全构成的威胁较小;而当气侵量超 过临界值时,在环空上部发生气体分离,分离点迅速下移,如不及时控制,在极短时间内便可演化为井喷,危险性极大 。     

复杂山区地形高含硫气井安全防护距离研究

通过对国内某重大高含硫井喷事故进行调查,采用大涡模拟方法对3口井井喷气体扩散进行模拟,计算不同风速风向在事故中造成的灾难后果,得出地形因素对于灾难的影响。通过计算不同浓度下的扩散距离,提出分析及计算安全防护距离的方法。根据计算结果的综合分析可以看到,其浓度扩散的最远距离位于带状分布以内。     

风险因子模糊评价法在钻机安全评价中的应用

钻机是石油与天然气钻井作业的重要设备,在使用过程中存在着极大风险,如果对其中的风险因素管理不善,风险转化为事故,将造成极大的损失,严重影响企业的形象与生产。为了预防石油与天然气钻井作业过程的事故发生,提高钻井队安全管理水平,论文采用通过对系统技术风险概率Pf和事故后果的严重程度Cf的估计和模糊评判的方法得到系统的风险状况Rf,为采取科学合理的风险消减措施提供了决策依据。论文以某型号电动钻机的电气控制系统为例进行风险分析,分析结果表明与实际情况比较符合。     

钻井井喷失控因素分析及预防对策

井喷失控是钻井中的灾难性事故,有必要开展井喷失控研究,找到井喷失控发生的原因和提出防止井喷失控的对策。在统计分析1970年到2009年间中石油发生在钻进过程中的48例井喷失控事故的基础上,通过对防喷器、节流压井管汇、套管、井喷后爆炸起火等井喷失控因素分析,并利用MLS法对上述各种井喷失控因素危险值进行评估。最后,根据井喷失控因素分析和危险值评估结果,结合现有的钻井井控设计,提出了防止钻井井喷失控的对策。     

新疆油田钻井井喷风险分级及井控管理

为了减少新疆油田钻井溢流井喷事件,杜绝井喷失控事故,在统计新疆油田影响钻井井喷风险的地质环境因素的基础上,利用模糊数学理论建立了油田基于地质环境因素的钻井井喷风险分级模型,对各个区块的钻井井喷风险程度进行了分级,结果表明南缘山前构造勘探开发区块及克拉美丽气田的钻井井控风险值最高。建议对新疆油田钻井井控进行分级管理,针对不同的钻井井喷风险等级,制定了针对性的井控对策,建议在井控设计时考虑钻井井喷风险分级设计。     

“三高”气田钻井过程硫化氢泄漏动态风险分析

传统的H2S泄漏风险分析方法不能很好地对事故发展过程进行动态分析,导致分析结果偏离实际。基于贝叶斯方法,构建了高温、高压、高含硫（“三高”）气田钻井过程中H2S泄漏的蝴蝶结模型并提出将其转化为贝叶斯网络,在事故已发生的情况下更新基本事件发生的概率。然后,假定事故后果在确定的时间段内发生的累积次数已知的条件下,更新安全屏障及事故后果发生的概率,从而完成对H2S泄漏的动态风险分析。结果表明,该方法克服了传统静态定量分析方法中的不足,可动态评估导致H2S泄漏的基本事件发生的概率和对顶事件发生的影响程度,并动态反映安全屏障和事故后果的风险变化,能为钻井过程中H2S泄漏的风险分析及防控措施提供参考。     

A capping technique for emergency response in offshore blowout accidents

Capping stack is an emergency shut-in technique that can effectively control offshore blowout accidents. This technique stemmed the spilled oil well (Macondo) in 2010 Deepwater Horizon blowout accident. However, few efforts have been devoted to studying the way to efficiently and safely conduct the operation of capping stack. In this paper, program evaluation and review technique (PERT) was employed to quantitatively design the operation procedure of capping stack. A mechanical model was established to determine the configuration scheme of capping stack. And a sensitivity analysis of operational factors of capping stack was conducted through orthogonal tests. Experimental results recommend to optimize the operation process by reducing the working time of diamond cutting tool down-pass, Lower Marine Riser Package (LMRP) upper riser incision, LMRP and original Blowout Preventer (BOP) separation, and LMRP recovery, in order to guarantee that the whole operation can be completed as scheduled. The results show that the number of ram BOPs has little effect on the equivalent stress of conductors. To improve system reliability, a five-ram capping stack is recommended to be applied in the defined accident scenario. The maximum equivalent stress of conductors rates the drilling vessel offset as the primary factor, followed by shut-in pressure, ocean current and top tension. The drilling vessel offset needs to be given the priority control and the shut-in pressure should be jointly monitored.     

Quantitative sensitivity and reliability analysis of sensor networks for well kick detection based on dynamic Bayesian networks and Markov chain

Kick is considered as an early warning sign to the blowout that is among the most undesired and feared accidents during drilling operations. Kick detection system is commonly used to timely identify the occurrence of a kick. The method commonly used for kick detection relies on the proper selection of monitoring indicators. A kick detection system should not only have very high accuracy but also maintain reliable over a long time. Different from the existing studies focusing on improving the detection accuracy, this paper presents a frame emphasizing on quantitatively analyzing and enhancing the reliability of the kick detection sensor networks. The dynamic Bayesian network (DBN) for the sensor networks is established that employs Markov chain to obtain the reliability degradation of measurement sensors over time. The proposed method is applied and evaluated by case studies to conduct reliability and sensitivity analysis for kick detection sensor networks. The reliability analysis results demonstrate that the proposed method can quantitatively analyze the reliability of a kick detection sensor networks consisting of various sensors over given time periods. The sensitivity analysis results indicate that the proposed method is effective in identifying the critical sensors that have the greatest effect on the reliability of one certain kick detection system. Based on the analysis results, optimized logical combination of sensors of a kick detection system can be achieved. An improved sensor network for the unreliable case was proposed and evaluated.     

Dynamic accident modeling for high-sulfur natural gas gathering station

Dynamic accident modeling for a gas gathering station is implemented to prevent high-sulfur natural gas leakage and develop equipment inspection strategy. The progress of abnormal event occurring in the gas gathering station is modeled by the combination of fault tree and event sequence diagram, based on accident causal chain theory, i.e. the progress is depicted as sequential failure of safety barriers, then, the occurrence probability of the consequence of abnormal event is predicted. Consequences of abnormal events are divided into accidents and accident precursors which include incidents, near misses and so on. The Bayesian theory updates failure probability of safety barrier when a new observation (i.e. accident precursors or accidents data) arrives. Bayesian network then correspondingly updates failure probabilities of basic events of the safety barriers with the ability of abductive reasoning. Consequence occurrence probability is also updated. The results show that occurrence probability trend of different consequences and failure probability trend of safety barriers and basic events of the safety barriers can be obtained using this method. In addition, the critical basic events which play an important role in accidents occurrence are also identified. All of these provide useful information for the maintenance and inspection of the gas gathering station.     

Developing safety indicators for preventing offshore oil and gas deepwater drilling blowouts

An important question with respect to the Macondo blowout is whether the accident is a symptom of systemic safety problems in the deepwater drilling industry. An answer to such a question is hard to obtain unless the risk level of the oil and gas (O&G) industry is monitored and evaluated over time. This article presents information and indicators from the Risk Level Project (RNNP) in the Norwegian O&G industry related to safety climate, barriers and undesired incidents, and discusses the relevance for deepwater drilling. The main focus of the major hazard indicators in RNNP is on production installations, whereas only a limited number of incident indicators and barrier indicators are related to mobile drilling units. The number of kicks is an important indicator for the whole drilling industry, because it is an incident with the potential to cause a blowout. Currently, the development and monitoring of safety indicators in the O&G industry seems to be limited to a short list of “accepted” indicators, but there is a need for more extensive monitoring and understanding. This article suggests areas of extensions of the indicators in RNNP for drilling based on experience from the Macondo blowout. The areas are related to schedule and cost, well planning, operational aspects, well incidents, operators’ well response, operational aspects and status of safety critical equipment. Indicators are suggested for some of the areas. For other areas, more research is needed to identify the indicators and their relevance and validity.     

基于DEMATEL/ISM的深水井喷风险影响因素研究*

为提高深水井喷事故风险管理水平,提出研究深水井喷风险影响因素的分析方法。从技术、人员、环境和管理4个方面,识别深水井喷事故风险致因因素,建立深水井喷事故风险评价指标体系;运用矩阵决策实验室分析法（DEMATEL）,研究风险因素之间的相互影响关系,计算不同风险因素的中心度和原因度,确定关键风险因素;进一步基于解释结构模型（ISM）划分不同影响因素的层次结构,分析风险因素之间的综合影响关系,建立深水井喷事故风险影响因素模型。结果表明:层级1为近邻致因,可直接导致井喷事故的发生;层级2~7为过渡致因,在风险传递过程中起到桥梁作用,对井喷事故的直接影响较小;而层级8则为本质致因,重视本质致因的改善有利于从根源上降低井喷事故的风险。研究结果可为深水井喷事故风险的预防和控制提供理论依据。     

海上钻井平台安全风险预警模型应用研究

2010年美国墨西哥湾“深水地平线”钻井平台爆炸和2011年我国蓬莱钻井平台井涌事故,引发社会各界对海上钻井平台安全问题的关注.介绍了海洋钻井平台的组成结构,对海洋钻井平台的危险源进行了系统辨识,试图通过对海上钻井平台作业现场危险因素加以观察,诊断、分析警源、警情,警兆,警级,结合专家意见,从人员、设施设备、安全管理、工程地质、海上环境等几个方面建立海上钻井平台安全风险预警体系,采用改进的层次分析法,得出指标权重,构建海洋钻井平台安全风险预警模型,得到量化的预警结果.并通过对某钻井平台的实例分析,提出安全风险的预控对策,以期本模型对海上钻井平台的事故的发生起到一定的防范作用.     

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.     

基于FMECA与模糊FTA的余热锅炉安全分析

为了保证余热锅炉安全运行,预防爆炸事故发生,利用FMECA方法和模糊FTA方法,研究余热锅炉事故致因。通过对余热锅炉潜在危险因素的分析辨别,探讨设备故障类型、原因及相应处理方法,引入模糊FTA对余热锅炉爆炸事故定性和定量分析,进而构建了基于FMECA与模糊FTA的余热锅炉安全分析框架,并计算得出事故发生的模糊概率以及对基本事件的敏感性分析。研究表明,余热锅炉系统的可靠度大约为96.92%,未按规定排污,报警器失灵,安全阀压力连接管堵塞及除氧器不合格事件对顶事件发生概率的影响最大,从而为该系统的安全决策提供支持。     

作业条件危险性评价法在深水钻完井作业评价中的应用研究

深水钻完井作业长期暴露于危险环境中,被普遍认为是高危作业。同时深水事故的发生给人类带来深刻的教训,例如墨西哥漏油事件造成恶劣的海洋环境污染,有必要提高钻完井作业的安全性。由于深水钻完井作业复杂,其危险性复杂多样,需从作业单元入手详细分析其危险性。本文采用作业条件危险性评价法（LEC）对深水钻完井作业进行危险性评价。首先,辨识危险有害因素;其次,在对作业条件危险性评价法进行改进的基础上分析深水油气田钻完井作业火灾爆炸危险性。分析结果表明改进后的作业条件危险性评价法能够更准确地确定危险等级,为对深水钻完井作业其它危险因素评价提供了参考。     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

飞行事故概率模型与风险评估方法

以事故统计为基础,建立了飞行事故概率模型与随机过程模型,对飞行安全可靠性指标进行定量评估。根据独立性假设,推导了飞行风险的概率分布,并给出飞行安全重要指标间的关系。假设飞行事故发生是Poisson过程,导出了飞行安全可靠性概率指标的区间估计计算方法。实例计算表明,通过统计量可以对飞行安全进行风险评估,根据飞行事故风险概率等级要求得到评定等级。