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An offshore installation is exposed to ship collision risk from in-field and passing vessels. Both categories of collision have occurred on the United Kingdom Continental Shelf (UKCS), and both have the potential to result in catastrophic damage to the installation, although to date only significant consequences have been observed in UK waters. World-wide, catastrophic collisions with installations have occurred resulting in severe damage to vessels and installations, leading to loss of life and environmental damage. This led to the authors investigate the occurrence and reporting of ship to platform collisions on the UKCS 1971–2017. It was found that there were periodic fluctuations in the occurrence of collision accidents. This research analyses the accident trends in order to determine the whether the fluctuations were a regular occurrence and, if so, what was the cause. 511 ship to platform collision incidents between 1971 and 2017 were subject to analysis, in terms of damage classification, the vessel type, month of occurrence and a comparison of the release of regulations with the fluctuation of incidents. Subsequently, this analysis has identified a key trend between the reporting of offshore collision incidents and the release and enforcement of offshore Safety Case regulations. [ABSTRACT FROM AUTHOR]

Robust regulation has become a pursuit in risk governance of offshore drilling operations over the recent decade. However, the idea of robust risk regulation has not been fully developed in China. This paper aims to explore what affects the robustness of risk regulation and how can a robust regulatory regime for offshore drilling operations be achieved in China. It begins with an identification of risks and values of the offshore petroleum industry, highlighting that robust regulation is the primary means to manage such risks in offshore drilling operations. It then discusses dimensions of regulatory robustness and assesses and compares regulatory regimes for this high-risk offshore petroleum industry in the United Kingdom, Norway, the United States and China. In specific, the Chinese paths to govern the risks of offshore operations are summarized. A key theoretical debate on regulating offshore drilling operations is which regulatory modes can better facilitate the robustness of risk regulation. The command-and-control regulation and self-regulation represent two primary regulatory modes of offshore risk regulation. The former is strongly dependent upon public enforcement while the latter emphasizes internal continuous improvement of the offshore petroleum industry. To develop robust offshore regulation in China, this paper suggests that a certain combination of the two modes is necessary to deliver optimal regulatory outcomes.

Offshore drilling is a complex and hazardous operation. The safety of the drilling operation is a strong function of many time-dependent parameters. The traditional risk analysis model fails to capture the impact of spatial and temporal variations of these parameters. This paper presents a Bayesian Network (BN) model for the offshore drilling operation. The model uniquely considers the evolution of hazards as a function of time and space, and failure of the safety barriers. The model development is explained using the bowtie approach, which is routinely used in the industry for risk management. The bowtie model is subsequently transformed into a BN model and simulated for the well blowout scenarios. The blowout risk is updated based on operational field observations. An uncertainty analysis is also conducted to capture the spatial variability of the parameters. The results of the BN model provide a dynamic risk profile of the blowout accident during the drilling operation. Other possible accident scenarios, such as lost circulation, can also be analyzed using the proposed model. The proposed BN model serves as a robust tool for risk management of offshore drilling operations. [ABSTRACT FROM AUTHOR]

The background and rationale for the research reported in this paper is detailed in the companion paper subtitled Part A: Modelling the on-deck helicopter Reserve of Stability (ROS). This paper (Part B) derives the fundamental principles underpinning the safe operational envelope and the definition of Motion Severity and Wind Severity Indices (MSI/WSI), and then presents the probabilistic modelling methodology developed for calculating safe limits for these parameters (MSI/WSI limits curves). The introduction of the Relative Wind Direction (RWD) as an additional limiting parameter is also discussed, together with an explanation of how RWD limits have been derived and how they are linked with the MSI/WSI limits calculation. The MSI/WSI limits modelling methodology presented in this paper builds on the analytical helicopter stability modelling discussed in Part A. It uses a probabilistic approach to manage the variability in helicopter operations across the UK and to deal with the uncertainty of predicting helideck motion and wind conditions for the period the helicopter is landed on the helideck based on measurements taken prior to landing. This has been developed with the assistance of industry experts and has been subjected to consultation with stakeholders in the UK with the aim of identifying the right balance between enhancing safety and preserving operability. A new Helideck Monitoring System (HMS) standard has been developed which incorporates the MSI/WSI/RWD functionality. The standard was published by the Helideck Certification Agency in April 2018 with a compliance date of 31 March 2021. Operations to moving decks not equipped with HMS meeting the new standard will be restricted to stable helideck conditions. [ABSTRACT FROM AUTHOR]

The oil and gas industry relies heavily on helicopters for transporting personnel and cargo to and from offshore installations and support vessels. A growing number of offshore helicopter operations are to moving helidecks, which include large vessels such as FPSOs, drill ships, and semi-submersibles, as well as smaller service vessels. Landing a helicopter on a moving helideck presents additional challenges to those faced on fixed helidecks, not only at the point of touchdown but also for the entire period the helicopter remains on the helideck. The UK Civil Aviation Authority (CAA), on behalf of the joint CAA/industry Helicopter Safety Research Management Committee has led a comprehensive programme of research over a number of years, aimed at improving the operational safety of helicopters landing on moving helidecks. The work focused on the aspect of the stability of helicopters once landed on a moving helideck, this being the main source of in-service incidents and accidents as evidenced in the Mandatory Occurrence Reports. The project culminated in the development of a new standard for Helideck Monitoring Systems (HMS), which was published by the Helideck Certification Agency in April 2018 with an implementation compliance date of 31 March 2021. Operations to moving helidecks not equipped with HMS meeting the new standard will be restricted to stable deck conditions from this date. The research underpinning the new standard is presented in two papers. This paper (Part A), presents the analytical approach that has been developed to model the Reserve of Stability (ROS) for all modes of failure of a helicopter on a moving offshore helideck. The analytical model covers all modes of on-deck failure (roll-over and sliding), for any nose wheel tricycle undercarriage helicopter. The mathematical expressions that have been derived are remarkably simple, physically intuitive, and make the relative contribution of all the destabilising factors easy to understand and assess. These analytical expressions can be used to calculate the ROS of any helicopter in real time, as well as for calculating an envelope of safe operating limits. This approach has many advantages compared to conventional 'black box' modelling methods. The main advantage is that it simplifies the modelling of the destabilising effect of helideck motion and allows the most salient parameters governing on-deck ROS to be defined, namely the Measure of Motion Severity, the instantaneous wind speed as the Measure of Wind Severity, and the wind direction relative to the helicopter (Relative Wind Direction). The main rotor lift generated during the time the helicopter remains on-deck (at Minimum Pitch on Ground, MPOG) has been one of the most important unknowns that this research programme has sought to address. An empirical model for estimating the lift at MPOG has been developed, based on experimental and field data. Practical methods for quantifying fuselage wind drag and the vertical position of the centre of gravity were also developed, which allow different helicopter types to be assessed without recourse to helicopter Original Equipment Manufacturer (OEM) proprietary information or models. Finally, a comparison and evaluation of the model against dedicated field trial measurements is presented, together with a discussion of the modelling strengths and weaknesses, and recommendations for further work. [ABSTRACT FROM AUTHOR]

This research proposes the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore gas driven turbine, used for electrical power generation. The focus of the research is centred on the potential release of fuel gas from a turbine and the potential consequences that follow the said release, such as fire, explosion and damage to equipment within the electrical generation module. The Bayesian network demonstrates the interactions of potential initial events and failures, hazards, barriers and consequences involved in a fuel gas release. This model allows for quantitative analysis to demonstrate partial verification of the model. The verification of the model is demonstrated in a series of test cases and through sensitivity analysis. Test case 1 demonstrates the effects of individual and combined control system failures within the fuel gas release model; 2 demonstrates the effects of the 100% probability of a gas release on the Bayesian network model, along with the effect of the gas detection system not functioning; and 3 demonstrates the effects of inserting evidence as a consequence and observing the effects on prior nodes. [ABSTRACT FROM AUTHOR]

Abstract Logistics support to offshore operations is challenging, especially under severe environmental conditions such as those in the Arctic and sub-Arctic. The dominant environmental conditions, including waves, wind, poor visibility and the presence of icebergs and sea ice determine the mode and success of logistics support. Use of helicopters as a mode of logistics transport becomes ineffective when the distance is longer, the visibility is low, or the weather is stormy. Marine logistics support is more reliable and versatile. The present work focuses on developing a model for assessing risk associated with marine logistics operations in remote offshore locations (beyond helicopter reach) frequented with harsh environmental conditions (high winds, waves, and icy conditions). The key factors that affect such operations are identified and failure models are developed using fault trees. As an improvement, advance fault trees are adopted to relax the inherent limitations of the primary model. Uncertainties in both data and model are considered using the fuzzy inference system and evidence theory. Application of the proposed model is demonstrated through a case-study concerning a remote North Atlantic offshore operation. The contribution of this study is the identification of the key factors controlling the marine logistics operation and the development of a robust risk model that helps to analyze criticality of the contributing factors. The proposed model has the potential to help to develop innovative risk management strategies to support offshore operations. Highlights • A novel marine logistics model to support offshore operations is challenging environmental conditions. • The model identifies and consider key failure modes and develop appropriate failure models. • Model relaxes assumption of independence of causes. • Data and model uncertainties are considered. • Application of the proposed model is demonstrated through a case-study concerning a remote North Atlantic offshore operation. [ABSTRACT FROM AUTHOR]

This article proposes the initial stages of the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore system. The main focus is the construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity. The majority of the data required to complete the Bayesian network was gathered from various databases and past risk assessment experiments and projects. However, where data were incomplete or non-existent, expert judgement was applied through pairwise comparison, analytical hierarchy process and a symmetric method to fill these data gaps and to complete larger conditional probability tables. A normally unattended installation–Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed to ensure safe operations in situations whereby physical human-to-machine interaction is not occurring. The Integrity Case can be said to be dynamic as it shall be continually updated for an installation as the quantitative risk analysis data are recorded. This allows for the integrity of the various systems and components of an offshore installation to be continually monitored. The Bayesian network allows cause and effect relationships to be modelled through clear graphical representation. The model accommodates for continual updating of failure data. [ABSTRACT FROM AUTHOR]

Accidental damage to underwater cables caused by ship traffic seems to be a current problem. According to the statistics more than 44 percent of such damage is caused by fishing vessels. The reason for the next 14 percent is damage from ships' anchors. The construction of the underwater installation risk model was based on the determination of the density of the traffic in the area where the installation is located. There are several models used to assess the risk of underwater cable damage requiring the implementation of data on the density of traffic of fishing vessels. For this purpose, they usually use AIS (Automatic Identification System) data or statistical data on traffic density in the areas called fishing squares. The aim of this article was to compare traffic data that was based on two independent systems AIS and VMS (Vessel Monitoring System) and verify the reliability of them. The research was carried out in the area of the Slupsk Bank where an underwater cable has been damaged several times. The authors have demonstrated the need to verify the data from both systems in order to obtain reliable information about fishing vessels. [ABSTRACT FROM AUTHOR]

This study presents a new safety methodology that is capable of transforming qualitative expert judgement into probabilistic risk outcomes for offshore engineering systems. In the framework, fuzzy set theory is applied to describe variables. Fuzzy data of each input is expressed in terms of the belief degree format representing the extent to which the fuzzy data belongs to the associated fuzzy set. Such data is subsequently combined to derive appropriate consequents using a fuzzy rule approach considering the weights of each input. The information generated in the antecedent and consequent of each rule are then synthesized to reach the fuzzy conclusions using the Bayesian reasoning approach. Such fuzzy conclusions are defuzzified and consequently transformed into the probabilistic nature. The framework is validated using two axioms and demonstrated by a risk study of the propulsion malfunction of an offshore Floating Production, Storage and Offloading (FPSO) during tandem offloading operations. The results are consistent with the axioms since the outcomes are sensitive to the minor alterations of input data and weights. It is concluded that the new approach produces reasonable results considering input weights and the logicality between inputs and outputs without losing too much useful information in the inference process. [ABSTRACT FROM AUTHOR]

The paper discusses issues of the impact of traffic density of the vessels on the sea surface to offshore underwater pipelines. The risk includes vessel foundering, sinking, grounding, dropping and dragging anchors, trawling fishing gear. The density of merchant, offshore field support vessels and fishing vessels presented by this paper is base for build risk model for underwater infrastructures. As an example it has been analyzed ships traffic over underwater gas pipeline between platform Baltic Beta and Wladyslawowo power plant. [ABSTRACT FROM AUTHOR]

Highlights: [•] We outline a conceptual framework for fitness-to-operate (FTO). [•] We develop an assessment guide designed for offshore facilities. [•] The framework and guide provide new insights into safety capability. [ABSTRACT FROM AUTHOR]

This paper begins with a very brief review of the current status of offshore safety with particular reference to the UK sector. The risk-based verification concept is then described. Following identification of the research needs, a general risk-based verification framework is proposed with appropriate risk assessment contents incorporated into it. An example is then followed to demonstrate the proposed framework. The Health, Environment and Safety Information System (THESIS) software package is also used to facilitate the implementation of the framework. Finally, both the benefits and the limitations of risk-based verification in offshore applications are highlighted. The emphasis of the paper is focused on industrial applications. [ABSTRACT FROM PUBLISHER]

This research is intended to present probabilistic sliding displacement and liquefaction hazard assessment procedures where expected sliding displacement of offshore slopes and factor of safety against liquefaction potential of subsoils are derived for extreme level earthquake and abnormal level earthquake conditions, as defined in the ISO 19901-2 guideline. These probabilistic approaches rigorously account for the variability in the intensity measure (e.g. ground acceleration), the variability in the engineering demand parameters (EDP) (e.g. sliding displacement and factor of safety against liquefaction), and the variability in the soil input parameters required to compute the EDP. The procedures are applied to a hypothetical site in the vicinity of oil and gas platforms located in the Santa Barbara Channel in Southern California. [ABSTRACT FROM PUBLISHER]

Risk evaluation of offshore wells is a challenging task, given that much of the available data is highly uncertain and vague, and many of the mechanisms are complex and difficult to understand. Consequently, a systematic approach is required to handle both quantitative and qualitative data as well as means to update existing information when new knowledge and data become available. Each Basic Risk Item (BRI) in a hierarchical framework is expressed as a fuzzy number, which is a combination of the likelihood of a failure event and the associated failure consequence. Analytical Hierarchy Process (AHP) is used to estimate weights required for grouping non-commensurate risk sources. Evidential Reasoning (ER) is employed to incorporate new data for updating existing risk estimates. It is envisaged that the proposed approach could serve as a basis for benchmarking acceptable risks in offshore wells. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. Method: The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason''s “Swiss cheese” model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. Results: This paper shows that Reason''s “Swiss cheese” model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts'' personal experiences and is therefore highly domain specific. Impact on Industry: “Swiss cheese” model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology. [Copyright &y& Elsevier]

Abstract: As the capability of polar plots becomes better understood, improved dynamic positioning (DP) systems are possible as the control algorithms greatly depend on the accuracy of the aerodynamic and hydrodynamic models. The measurements and estimation of the environmental disturbances have an important role in the optimal design and selection of a DP system for offshore platforms. The main objective of this work is to present a new method of predicting the Capability-Polar-Plots for offshore platforms using the combination of the artificial neural networks (NNs) and the capability polar plots program (CPPP). The estimated results from a case study for a scientific drilling vessel are presented. A trained artificial NN is designed in this work and is able to predict the maximum wind speed at which the DP thrusters are able to maintain the offshore platform in a station-keeping mode in the field site. This prediction for the maximum wind speed will be a helpful tool for DP operators in managing station-keeping for offshore platforms in an emergency situation where the automation of the DP systems is disabled. It is obvious from the obtained results that the developed technique has potential for the estimation of the capability-polar-plots for offshore platforms. This tool would be suitable for DP operators to predict the maximum wind speed and direction in a very short period of time. [Copyright &y& Elsevier]

Process operation is the most hazardous activity next to the transportation and drilling operation on an offshore oil and gas (OOG) platform. Past experiences of onshore and offshore oil and gas activities have revealed that a small mis-happening in the process operation might escalate to a catastrophe. This is of especial concern in the OOG platform due to the limited space and compact geometry of the process area, less ventilation, and difficult escape routes. On an OOG platform, each extra control measure, which is implemented, not only occupies space on the platform and increases congestion but also adds extra load to the platform.Eventualities in the OOG platform process operation can be avoided through incorporating the appropriate control measures at the early design stage. In this paper, the authors describe a methodology for risk-based process safety decision making for OOG activities. The methodology is applied to various offshore process units, that is, the compressor, separators, flash drum and driers of an OOG platform. Based on the risk potential, appropriate safety measures are designed for each unit. This paper also illustrates that implementation of the designed safety measures reduces the high Fatal accident rate (FAR) values to an acceptable level. [Copyright &y& Elsevier]

• The safety and economic risk model is presented for the marine support system. • A risk-based cost-benefit analysis to evaluate the feasibility of the offshore Resource Centre is provided. • The novel probabilistic loss function models are proposed to assess the impact of potential accident and response time. • The effectiveness of the proposed models is demonstrated through a real case study. Marine Logistics support during regular and emergency operations in remote North Atlantic regions is risky due to longer helicopter flying distances and extreme environmental conditions. In this paper, the safety and economic aspects of the previously introduced concept of an intermediate offshore resource centre (ORC) are evaluated. The ORC goals are to provide an intermediate helicopter landing station and a forward staging area for emergency response. Among many advantages, an ORC mitigates the logistical risk associated with the extended distance from shore support by reducing the response time in the case of accidents. This paper presents a risk-based cost-benefit analysis of the ORC. A probabilistic loss function model is developed based on the costs of historical offshore blowout incidents and their corresponding response times. The cost and benefit model is simulated in a probabilistic framework using a Monte Carlo simulation. The developed methodology and model help to assess the financial viability of an ORC in order to assist in informed decision-making regarding risk reduction measures. [ABSTRACT FROM AUTHOR]