A Framework for Identification of Lessons Learned from Offshore Operational Data Using Barriers and Success Paths

PresentationOne of the most pressing challenges facing the offshore industry today is the effective interpretation, decision making, and action identification using the large volumes of operational data that are being collected and stored. Offshore operators, drilling contractors, and third party suppliers have developed real time operations centers designed to support offshore operations. The Bureau of Safety and Environmental Enforcement (BSEE) has proposed requirements for the collection of offshore real time monitoring data, but how such data will be used to support regulatory decision making is not yet clear. Operating companies and original equipment manufacturers are designing and implementing new equipment with a very high degree of instrumentation and advanced diagnostics capabilities, leading to new sources of operational data that could be analyzed to further enhance reliability, reduce downtime, and increase safety. The potential benefits to be realized from the collection and interpretation of such volumes of operational data are substantial. Individual organizations are already using the data to provide remote decision support for offshore operations as well as off-line analysis to enhance equipment reliability and plan maintenance activities. At a higher level, the potential benefits of analysis and interpretation of large volumes of operational data across organizational boundaries and at the industry level have been recognized but not yet realized. There has been much discussion regarding the promise of “big data analytics” to address these industry-level issues, but practical solutions are not yet available to deliver on the promises. However, a number of promising initiatives are underway. For example, the Society of Petroleum Engineers (SPE) and BSEE have initiated collaborative efforts to assess the processes, tools, and value of sharing and learning from offshore safety related data. A critical component that must be developed for effective utilization of operational data at the industry level is a framework for interpreting operation experience that will protect data confidentiality while allowing consistent interpretation and identification of lessons learned. Such a framework could support consistent application to identify lessons learned across discipline and organizational boundaries and the development of a “common language” for communication and consensus for action amongst industry and regulatory organizations. DNV GL has developed a framework for interpreting operational data that is built on a combination of barriers and success paths. Using this approach, data from operational incidents can be interpreted in light of the effects on barrier health and the utilization of effective success paths for responding to degraded or failed barriers. The approach is built upon experience gained in interpretation of aviation incidents in the NASA Aviation Safety Reporting System (ASRS), identification of lessons learned from incidents and accidents in nuclear power plants, and assessment of lessons learned from major pipeline leak accidents. The approach is currently being used in a project with an offshore operator and a drilling contractor to support development of diagnostic algorithms and regulatory compliance assessment for new well control equipment and procedures for deepwater drilling. A unique feature of this application is the utilization of the barrier-success path framework to form the foundation of a common language for regulatory approval of the new equipment and procedures, as well as continuous regulatory compliance assessment during operations. The development process includes proactive interaction with regulatory personnel to identify pre-defined decision criteria and communication protocols for continuous compliance assessment during operation. This paper summarizes experience gained in application of the barrier-success path approach for identification of lessons learned from operational experience in the commercial aviation, nuclear and pipeline industries and current developments for design of diagnostics and compliance assessment for deepwater drilling. The paper also summarizes the potential benefits for broader application of the approach for interpretation of operational data to support communication, decision making, and consensus for action across the industry including offshore operators, industry groups, regulatory authorities, and external stakeholders

Crosswalk of Human Reliability Methods for Offshore Oil Incidents

PresentationHuman reliability analysis (HRA) has long been employed in nuclear power applications to account for the human contribution to safety. HRA is used qualitatively to identify and model sources of human error and quantitatively to calculate the human error probabilities of particular tasks. The nuclear power emphasis of HRA has helped ensure safe practices and risk-informed decision making in the international nuclear industry. This emphasis has also tended to result in a methodological focus on control room operations that are very specific to nuclear power, thereby potentially limiting the applicability of the methods for other safety critical domains. In recent years, there has been interest to explore HRA in other domains, including aerospace, defense, transportation, mining, and oil and gas. Following several high profile events in the oil and gas industry, notably the Macondo well kick event in the U.S., there has been a move to use HRA to model and reduce risk in future oil drilling and production activities. Organizations like the Bureau of Safety and Environmental Enforcement are adapting the risk framework of the U.S. Nuclear Regulatory Commission for offshore purposes. In this paper, we present recent work to apply HRA methods to the analysis of offshore activities. We present the results of retrospective analyses using three popular HRA methods: SPAR-H, Petro-HRA, and CREAM. With the exception of Petro- HRA, these HRA methods were developed primarily for nuclear power event analysis. We present a comparison of the findings of these methods and a discussion of lessons learned in applying the methods to offshore events. The objective of this paper is to demonstrate the suitability of HRA methods for oil and gas risk analysis but also to identify topics where future research would be warranted to tailor these HRA methods

Human reliability analysis: exploring the intellectual structure of a research field

Humans play a crucial role in modern socio-technical systems. Rooted in reliability engineering, the discipline of Human Reliability Analysis (HRA) has been broadly applied in a variety of domains in order to understand, manage and prevent the potential for human errors. This paper investigates the existing literature pertaining to HRA and aims to provide clarity in the research field by synthesizing the literature in a systematic way through systematic bibliometric analyses. The multi-method approach followed in this research combines factor analysis, multi-dimensional scaling, and bibliometric mapping to identify main HRA research areas. This document reviews over 1200 contributions, with the ultimate goal of identifying current research streams and outlining the potential for future research via a large-scale analysis of contributions indexed in Scopus database

Using risk data as a source for human reliability assessment during shipping LNG offloading work

This manuscript has been made open access under a Creative Commons Attribution (CC BY) licence under the terms of the University of Aberdeen Research Publications Policy. https://creativecommons.org/licenses/by/4.0/Peer reviewe

Comparative Analysis of Nuclear Event Investigation Methods, Tools and Techniques

Feedback from operating experience is one of the key means of enhancing nuclear safety and operational risk management. The effectiveness of learning from experience at NPPs could be maximised, if the best event investigation practices available from a series of methodologies, methods and tools in the form of a ‘toolbox’ approach were promoted. Based on available sources of technical, scientific, normative and regulatory information, an inventory, review and brief comparative analysis of information concerning event investigation methods, tools and techniques, either indicated or already used in the nuclear industry (with some examples from other high risk industry areas), was performed in this study. Its results, including the advantages and drawbacks identified from the different instruments, preliminary recommendations and conclusions, are covered in this report. The results of comparative analysis of nuclear event investigation methods, tools and techniques, presented in this interim report, are of a preliminary character. It is assumed that, for the generation of more concrete recommendations concerning the selection of the most effective and appropriate methods and tools for event investigation, new data, from experienced practitioners in the nuclear industry and/or regulatory institutions are needed. It is planned to collect such data, using the questionnaire prepared and performing the survey currently underway. This is the second step in carrying out an inventory of, reviewing, comparing and evaluating the most recent data on developments and systematic approaches in event investigation, used by organisations (mainly utilities) in the EU Member States. Once the data from this survey are collected and analysed, the final recommendations and conclusions will be developed and presented in the final report on this topic. This should help current and prospective investigators to choose the most suitable and efficient event investigation methods and tools for their particular needs.JRC.DDG.F.5-Safety of present nuclear reactor

Data-Based Semi-Automatic Hazard Identification for More Comprehensive Identification of Hazardous Scenarios

As chemical process plants have become more involved and complex, the likelihood of hazardous incidents has increased simultaneously. That is, the more complex a facility’s systems, the more factors engineers must consider. This results in a higher likelihood of potential hazards being overlooked; thus, the possibility of incidents occurring increases. Many companies and organizations are struggling to identify their weaknesses and reduce hazardous issues by developing hazard identification (HAZID) tools, particularly for large and complex processes. Even though a considerable number of companies merely pursue this objective to conform to government regulations, their efforts play a critical role in improving their reputations and financial profits. Therefore, the advancement of HAZID tools in the process industries has taken significant strides over the last 40 years. Despite the substantial development of HAZID methods, traditional HAZID tools need further development because of their weaknesses in identifying possible hazards. In other words, it is evident that unintended incidents that occasionally occur in the chemical process industry require more enhanced HAZID methodologies. Therefore, this study attempts to ascertain the drawbacks of existing HAZID tools so that a new HAZID methodology, data-based semi-automatic hazard identification (DAHAZID), is proposed. Considering potential HAZID methodologies, this study seeks to identify possible scenarios with a semi-automatic and systemic approach. Based on the two traditional HAZID tools, Hazard Operability study (HAZOP) and Failure Mode, Effects, and Criticality Analysis (FMECA), the DAHAZID method will minimize the limitations of each individual method. Additionally, rather than depending on the HAZID tools to achieve the connectivity of the process system, this study will consider connections with other new technologies in advance. Then, this method can be integrated with proper guidelines regarding process design and safety analysis. To examine its usefulness, the method will be applied to two case studies, and its outcome will be compared to the actual result, performed previously by a traditional HAZOP meeting. Hopefully, this research can contribute to the further development of the process safety field in practice

Competence management in the UK heritage railway industry

The research underpinning this work takes place in the context of the United Kingdom heritage railway industry with the focus of the study being how competence can be managed effectively in a predominately volunteer environment. Aspects such as the volunteer culture, motivations, the prevailing language, the diversity of skills, qualifications and learning abilities are all taken into account and considered as key factors to be addressed in managing competence effectively. In particular, the impending “cliff edge” associated with the founding generation of volunteers leaving the heritage railway industry has provided the impetus for carrying out this work. There is an urgent need to capture and transfer their knowledge in a way that can be interpreted and understood by today’s generation of volunteers. Furthermore, the cost constraints affecting the industry, especially in the light of the impact of Covid-19, mean that a process to manage the transfer of competences across heritage railways is urgently required, thereby ensuring that scarce resources can be shared and applied at different heritage railway settings. Providing effective solutions to these issues will be critical to ensuring the future viability of the industry. As reality with respect to competence exists through people’s claims, the ontological position for this research is subjective (specifically, materialism), where reality is considered to shape the values, beliefs and understandings of those involved in managing, operating, maintaining and regulating heritage railways. Given the subjective constructs at the core of competence management, the epistemological position is interpretivist, an approach which acknowledges that findings can be generated through the analysis of data in a way that is able to reveal the truths therein. This approach also best enables the inclusion of the many physical entities found within the UK heritage railway environment, as well as its people. Such material elements include the assets of the railways, from infrastructure to the various locomotives and rolling stock that are operated. They also include the rules, processes and procedures that are documented and used to manage the day to operation of the railway, including competence management. The research questions were explored through the author’s own involvement in both the UK heritage and main-line rail industries, where personal experience has been applied to inform the research methods. The key methods employed were interview, both formal (digitally recorded and transcribed as “verbatim with dialect”) and informal, of workers at a selection of UK heritage railways, observation and reflection. Thematic analysis of the results has been compared through practice analysis (questionnaires) with how competence is currently managed to develop a new understanding of the factors to be taken into consideration for an approach to competence management that “makes sense” to volunteers, thereby assuring safety whilst maintaining staff engagement and the viability of the industry. This research has shown that there is currently no common industry-wide recommended approach to competence within this context, even though existing legislation places a legal obligation on UK heritage railways to manage competence in the workplace. Although there is an understanding by both volunteers and permanent staff of the need for effective competence management, variations in how this is understood and articulated suggests this is a complex phenomenon with a number of contributory aspects and barriers, and that any underpinning processes must be appropriate to the unique nature of the UK heritage railway industry and the associated risks. Volunteer motivation and engagement is key to the future viability of the industry and competence must be managed in such a way as to ensure that this is maintained and, where possible, enhanced. It could be suggested that for each railway to be developing their own systems in isolation is a missed opportunity in terms of sharing best practice and ensuring consistency, an ever more important factor as many volunteers work on more than one railway, and in terms of resources is unlikely to be a viable approach in the longer term. The unique contribution to knowledge from this research into competence management within the UK heritage railway industry is an understanding of how heritage railway volunteers actually make sense of competence management as revealed through thematic analysis of detailed interview transcripts. Much of this knowledge is also applicable and transferable to many other areas within the growing UK volunteer sector where increasing numbers of people are engaged on this basis, often to provide vital public services. This research matters because it identifies real themes, from volunteers actively engaged in running the UK’s heritage railways. Further work is required to formulate a new approach for a competence management system that will address the issues highlighted by this research, and that is appropriate to the unique heritage railway environment, with a trial implementation and assessment on a UK heritage railway. In this way, the aspiration is that a new approach to competence management can be adopted and applied on an industry-wide basis, potentially under the auspices of the Heritage Railway Association

Lessons learned from past accidents - The integration of human and organizational factors with the technical aspect

It is of prime importance to ensure the safety of chemical process plants due to volatile nature of the industry and drastic consequences of the accidents. A number of parameters can affect the safety of the process plants. One of the main parameters that has the influence on the safety of operations is the Human and Organizational Factors (HOF) as suggested by numbers of existing studies. Therefore, in order to enhance the safety of operations it is required to improve the HOF. These factors can be improved by an integrated approach as proposed in this work, instead looking at these factors in an isolation. A number of existing risk assessment approaches have been analysed in this work and their compliance requirements to the relevant International Standards with respect to the HOF. A new quantitative methodology “Method for Error Deduction and Incident Analysis (MEDIA)” has been developed in this work. During the development of this methodology, practicality; consistency; integration with other risk assessment techniques and efficient use of information were explicitly ensured. The MEDIA can help to integrate the HOF around the technical aspect and can prioritize the follow up actions based on risk. The quantification of this methodology is based on results of the accident analysis, that has been carried out in this work. The accidents of 25 years (1988-2012) in the Seveso establishments and that were reported to the European Commission’s Major Accident Reporting System (eMARS) have been studied. The results from the accident analysis have further used in order to learn lessons and to propose future recommendations. These recommendations are mainly aimed at further integration of the HOF and to improve the overall safety of chemical process plants. More specifically, these recommendations are addressed to the use of organizational checklist during the Hazard Identification (HAZID) study; improvement of existing eMARS reporting structure and the legal obligation towards the EU Member States to report their accidents to the European Commission