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

A. Yasseen, S. Peresypkin
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Abstract

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 well-established 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.
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人力绩效科学在油田服务供应商动态作业风险评估过程中的主动应用
人类绩效原则在航空和医疗领域得到了很好的发展,在石油和天然气行业仍然是一门新兴的科学。根据IOGP和IADC的事故统计数据,在过去的十年里,油气行业通过从HSE领导到基于行为的安全等多个项目,成功地显著减少了事故的发生。这引发了人们对人类绩效最佳实践及其在油气行业的适用性的深入研究。本文旨在提供一种替代方法,将人力绩效科学应用于油田服务公司的动态作业风险评估过程。在分析了现有的人为可靠性评估工具后,决定采用一种称为人为错误评估与减少技术(HEART)的人为性能工具,用于服务提供商的风险评估过程,主要关注错误产生条件(EPC)。我们进行了一项内部调查,以定义误差生产条件,这与油气服务作业的动态特性最为相关,并将其与Reasons的性能模式及其对误差出现的影响相结合。这种方法允许大大简化风险评估过程,并充分关注已知的产生人为错误条件的关键因素。这自然与我们现有的定性风险评估相结合,重新计算某项任务的整体风险,提高工人识别潜在危险的外部和内部因素的能力。改进的人员绩效风险评估的现场测试重塑了标准的风险评估做法,将重点转移到复杂系统中不可避免的人为相互作用造成的错误产生条件所导致的任务固有的不可靠性上。事实证明,这种方法有效地提高了一线员工对动态人力可靠性相关风险的整体理解,提高了约30%。其假设是,通过在日常风险评估中引入关键的人的表现因素,将有助于建立对人的因素及其与现有风险可能性的关系的认识。同时,利用一个已经有效的系统-风险评估-来引入人为因素方法将有助于避免与实施额外的人为可靠性工具相关的复杂性,并且仍然可以从一个成熟方法的关键要素中获益。该方法结合了两种现有的有效系统:标准风险评估和综合人为因素,在定制的保护伞下,完全适合油服公司的具体工作。本文提供了关于人为因素如何影响风险水平的见解,并概述了针对这些因素的控制措施,如果应用标准风险评估,这些因素可能会被遗漏。
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