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Proactive Application of Human Performance Science in Risk Assessment Process within Dynamic Operations of an Oilfield Service Provider

机译:油田服务提供商动态运作风险评估过程中人力绩效科学的主动应用

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Human performance principles, which are well developed in aviation and healthcare, still represent an emerging science within the oil and gas industry. The industry managed to significantly reduce injuries over the last decade with multiple programs ranging from HSE Leadership to Behavior-Based Safety to the point when the incidents plateaued according to IOGP and IADC incident statistics. This triggered a deeper look into human performance best practices and their applicability within the oil and gas sector. This paper aims to provide an alternative approach to adopt Human Performance science to the dynamic operations risk assessment process within an Oilfield Services Company. After the analysis of the existing human reliability assessment tools, a decision was made to adopt a human performance tool known as Human Error Assessment & Reduction Technique (HEART) into a service provider's risk assessment process with a primary focus on Error Producing Conditions (EPC). An internal survey was undertaken to define Error Producint Condition, which are most relevant to the dynamic nature of oil and gas services operations and couple them with the Reasons's performance modes and their effect on error appearance. This approach allowed to significantly simplify the risk assessment process and adequately focus on key factors known to produce conditions for human error. This naturally integrated into our existing qualitative risk assessment to recalculate the overall risk of a certain task and enhanced workers' ability to recognize potentially dangerous external and internal factors. The field tests of the improved human performance risk assessments reshaped the standard risk assessment practices, moving the focus to and targeting the inherent unreliability of the task as a result of error producing conditions caused by unavoidable human interactions within the complex systems. This approach proved effective in improving the overall understanding of dynamic human reliability related risks among the front line employees by around 30%. The hypothesis is that by introducing key human performance factors to the day-to-day risk assessment will help build awareness of human factors and their relationship to the probability of an existing risk. At the same time, utilizing an already effective system - risk assessment - to introduce human factors methods will help avoid the complexity associated with its implementation of an additional human reliability tool and still get the benefit of key elements of a wellestablished method. This approach has undertaken to combine two existing effective systems: a standard risk assessment with integrated human factors under a customized umbrella fully suitable for Oilfield Service Company's work specifics. This paper provides insights on how human factors can impact the level of risk and outlines the control measures targeted at such factors that can be missed if a standard risk assessment is applied.
机译:在航空和医疗保健方面发达的人类绩效原则仍然代表石油和天然气行业的新兴科学。该行业设法在过去十年中,在据IOGP和IADC事件统计数据达成的意见,在过去十年中,在过去十年中,在过去十年中,在过去十年中有多个方案。这引发了深入了解人类性能最佳实践及其在石油和天然气部门的适用性。本文旨在提供一种替代方法,以采用油田服务公司的动态运营风险评估过程。在分析现有的人力可靠性评估工具后,决定采用称为人为错误评估和减少技术(心)的人力绩效工具,进入服务提供商的风险评估过程,主要关注产生错误的条件(EPC) 。承担了内部调查以定义错误的生产线情况,这与石油和天然气服务运营的动态性质最相关,并以原因的绩效模式耦合,以及它们对误差外观的影响。这种方法允许大大简化风险评估过程,并充分关注已知为人为错误的条件产生的关键因素。这自然融入了我们现有的定性风险评估,以重新计算某项任务的总体风险,并加强工人识别潜在危险的外部和内部因素的能力。改善人类绩效风险评估的现场测试重塑了标准风险评估实践,将重点移动到并定位任务的固有不可靠性,因为由于复杂系统内的不可避免的人类交互引起的产生条件而导致的任务的固有不可靠性。这种方法证明有效地改善了对前线员工之间的动态人类可靠性相关风险的整体理解约为30%。假设是,通过向日常风险评估引入关键人力绩效因素,将有助于建立对人类因素的认识及其与现有风险的概率的关系。同时,利用已经有效的系统 - 风险评估 - 引入人类因素方法将有助于避免与其实施额外的人类可靠性工具相关的复杂性,并且仍然可以获得具有合成方法的关键要素的好处。这种方法已经采取了两个现有的有效系统:在定制的伞下完全适用于油田服务公司的工作细节的标准风险评估。本文提供了对人类因素如何影响风险程度的洞察,并概述了如果应用标准风险评估,则可以错过的因素所针对的控制措施。

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