Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database.

Organized into a global network of critical infrastructures, the oil & gas industry remains to this day the main energy contributor to the world's economy. Severe accidents occasionally occur resulting in fatalities and disruption. We build an oil & gas accident graph based on more than a thousand severe accidents for the period 1970-2016 recorded for refineries, tankers, and gas networks in the authoritative ENergy-related Severe Accident Database (ENSAD). We explore the distribution of potential chains-of-events leading to severe accidents by combining graph theory, Markov analysis and catastrophe dynamics. Using centrality measures, we first verify that human error is consistently the main source of accidents and that explosion, fire, toxic release, and element rupture are the principal sinks, but also the main catalysts for accident amplification. Second, we quantify the space of possible chains-of-events using the concept of fundamental matrix and rank them by defining a likelihood-based importance measure γ. We find that chains of up to five events can play a significant role in severe accidents, consisting of feedback loops of the aforementioned events but also of secondary events not directly identifiable from graph topology and yet participating in the most likely chains-of-events.

MCDA Index Tool: an interactive software to develop indices and rankings.

A web-based software, called MCDA Index Tool (https://www.mcdaindex.net/), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices' scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers' and stakeholders' preferences.

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non-OECD Countries with Focus on Time Trend Analysis.

This study presents probabilistic analysis of dam accidents worldwide in the period 1911-2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.

An aftermath analysis of the 2014 coal mine accident in Soma, Turkey: Use of risk performance indicators based on historical experience.

On the 13th of May 2014 a fire related incident in the Soma coal mine in Turkey caused 301 fatalities and more than 80 injuries. This has been the largest coal mine accident in Turkey, and in the OECD country group, so far. This study investigated if such a disastrous event should be expected, in a statistical sense, based on historical observations. For this purpose, PSI's ENSAD database is used to extract accident data for the period 1970-2014. Four different cases are analyzed, i.e., OECD, OECD w/o Turkey, Turkey and USA. Analysis of temporal trends for annual numbers of accidents and fatalities indicated a non-significant decreasing tendency for OECD and OECD w/o Turkey and a significant one for USA, whereas for Turkey both measures showed an increase over time. The expectation analysis revealed clearly that an event with the consequences of the Soma accident is rather unlikely for OECD, OECD w/o Turkey and USA. In contrast, such a severe accident has a substantially higher expectation for Turkey, i.e. it cannot be considered an extremely rare event, based on historical experience. This indicates a need for improved safety measures and stricter regulations in the Turkish coal mining sector in order to get closer to the rest of OECD.

Bayesian data analysis of severe fatal accident risk in the oil chain.

We analyze the risk of severe fatal accidents causing five or more fatalities and for nine different activities covering the entire oil chain. Included are exploration and extraction, transport by different modes, refining and final end use in power plants, heating or gas stations. The risks are quantified separately for OECD and non-OECD countries and trends are calculated. Risk is analyzed by employing a Bayesian hierarchical model yielding analytical functions for both frequency (Poisson) and severity distributions (Generalized Pareto) as well as frequency trends. This approach addresses a key problem in risk estimation-namely the scarcity of data resulting in high uncertainties in particular for the risk of extreme events, where the risk is extrapolated beyond the historically most severe accidents. Bayesian data analysis allows the pooling of information from different data sets covering, for example, the different stages of the energy chains or different modes of transportation. In addition, it also inherently delivers a measure of uncertainty. This approach provides a framework, which comprehensively covers risk throughout the oil chain, allowing the allocation of risk in sustainability assessments. It also permits the progressive addition of new data to refine the risk estimates. Frequency, severity, and trends show substantial differences between the activities, emphasizing the need for detailed risk analysis.

Risk of large oil spills: a statistical analysis in the aftermath of Deepwater Horizon.

The oil spill in the Gulf of Mexico that followed the explosion of the exploration platform Deepwater Horizon on 20 April 2010 was the largest accidental oil spill so far. In this paper we evaluate the risk of such very severe oil spills based on global historical data from our Energy-Related Severe Accident Database (ENSAD) and investigate if an accident of this size could have been "expected". We also compare the risk of oil spills from such accidents in exploration and production to accidental spills from other activities in the oil chain (tanker ship transport, pipelines, storage/refinery) and analyze the two components of risk, frequency and severity (quantity of oil spilled) separately. This detailed analysis reveals the differences in the structure of the risk between different spill sources, differences in trends over time and it allows in particular assessing the risk of very severe events such as the Deepwater Horizon spill. Such top down risk assessment can serve as an important input to decision making by complementing bottom up engineering risk assessment and can be combined with impact assessment in environmental risk analysis.

In-depth analysis of accidental oil spills from tankers in the context of global spill trends from all sources.

This study gives a global overview of accidental oil spills from all sources (> or =700t) for the period 1970-2004, followed by a detailed examination of trends in accidental tanker spills. The present analysis of the number and volume of tanker spills includes temporal and spatial spill trends, aspects of spill size distribution as well as trends of key factors (i.e., flag state, hull type, tanker age, accident cause and sensitivity of location). Results show that the total number and volume of tanker spills have significantly decreased since the 1970s, which is in contrast to increases in maritime transport of oil and to popular perceptions following recent catastrophic events. However, many spills still occur in ecologically sensitive locations because the major maritime transport routes often cross the boundaries of the Large Marine Ecosystems, but the substantially lower total spill volume is an important contribution to potentially reduce overall ecosystem impacts. In summary, the improvements achieved in the past decades have been the result of a set of initiatives and regulations implemented by governments, international organizations and the shipping industry.

Severe accidents in the energy sector: comparative perspective.

This paper addresses one of the controversial issues in the current comparative studies of the environmental and health impacts of energy systems, i.e. the treatment of severe accidents. The work covers technical aspects of severe accidents and thus primarily reflects an engineering perspective on the energy-related risk issues, though some social implications are also touched upon. The assessment concerns fossil energy sources (coal, oil and gas), nuclear power and hydro power. The scope is not limited to the power production (conversion) step of these energy chains but, whenever applicable, also includes exploration, extraction, transports, processing, storage and waste disposal. With the exception of the nuclear chain the focus of the work has been on the evaluation of the historical experience of accidents. The basis used for this evaluation is a comprehensive database ENSAD (Energy-related Severe Accident Database), established by the Paul Scherrer Institut (PSI). For hypothetical nuclear accidents the probabilistic technique has also been employed and extended to cover the assessment of economic consequences of such accidents. The broader picture obtained by coverage of full energy chains leads on the world-wide basis to aggregated immediate fatality rates being much higher for the fossil chains than what one would expect if only power plants were considered. Generally, the immediate fatality rates are for all considered energy carriers significantly higher for the non-OECD countries than for OECD countries. In the case of hydro and nuclear the difference is in fact dramatic. The presentation of results is not limited to the aggregated values specific for each energy chain. Also frequency-consequence curves are provided. They reflect implicitly the ranking based on the aggregated values but include also such information as the observed or predicted chain-specific maximum extents of damages. This perspective on severe accidents may lead to different system rankings, depending on the individual risk aversion.