Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study

Skogdalen, Jon Espen; Vinnem, Jan Erik

doi:10.1016/j.ress.2011.12.002

Cited by 130 publications

(55 citation statements)

References 26 publications

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“…The formation condition and well structure design can also be taken into consideration in terms of the contribution to the lost circulation. Therefore, totally 21 potential root causes in fault tree was found based on the work of Fuh et al (1992), Skogdalen and Vinnem (2012) and Abimbola et al (2015).…”

Section: Risk Identification For Lost Circulationmentioning

confidence: 99%

“…For example, the well-known Macondo blowout that occurred during the last stage of a drilling operation resulted in 11 fatalities and the largest oil spill in the history of offshore oil and gas industry. Predicting early kick or lost circulation, and taking necessary precautions, have been regarded as key measures to avoid such kind of disastrous accidents (Khan and Abbasi, 1999;Skogdalen and Vinnem, 2012).…”

Section: Introductionmentioning

confidence: 99%

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A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

Zhang

Zheng

et al. 2016

Journal of Natural Gas Science and Engineering

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Abstract:Drilling operations of offshore oil and gas fields are characterized by high reliance on advanced technology, high risk, and high costs due to operating in harsh ocean environments, under complicated geological factors, and extreme operating condition. Lost circulation or well "kick" are examples of hazardous events that may occur while drilling wells and such events may develop into a blowout accident if not handled. Identification and analysis of root causes and consequences are effective measures to prevent serious accidents from happening. The risk of having a blowout may change with time, depending on the stage of the drilling operation, and such kind of dynamics should be captured in risk assessment. This paper presents an approach for determining the conditional probabilities of hazardous events and their consequences. The approach includes models that take into account the influence of degradation and (if used in operation) new real-time information which represents the change in a state of a model parameter (such as state change of mud density) that can be captured while the drilling operation is ongoing.The approach presents a newly-developed model based on the basic theory of Dynamic Bayesian network (DBN) and this proposed model can incorporate some additional nodes to handle the uncertainty issues involving the model uncertainty and relevant parameters' uncertainty and also consider the effect of degradation, which are missed in other papers when using the DBN method for risk assessment of similar systems and operations. The main objective of this newly-developed model is to demonstrate how dynamic risk assessments can be used for incident prediction evolution as well as root cause reasoning during offshore drilling operation, given that a specific event has occurred. A bowtie model is established firstly to link the potential incident scenarios with pressure regimes and formation load capacity, and then the model is translated into a DBN. DBN inference is adapted to perform predictive and diagnostic analysis in different time slices for risk assessment and root cause reasoning. A sensitivity analysis is carried out to find the relative importance of each root cause in generating the potential drilling incidents. A case study with focusing on lost circulation during three drilling scenarios is used to illustrate and verify the feasibility of the proposed approach.Key words: Dynamic Bayesian network (DBN); drilling incidents; dynamic risk assessment; prediction of incident evolution; root cause reasoning Highlights: Potential incident scenarios with pressure regimes and weak formation are presented.  A newly-developed model based on Dynamic Bayesian Network is proposed for offshore drilling incidents.  Effects of model and parameter uncertainty are taken into account.  Prediction of risk evolution and root cause reasoning are performed based on the influence of degradation and occurred events.

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Section: Risk Identification For Lost Circulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

Zhang

Zheng

et al. 2016

Journal of Natural Gas Science and Engineering

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“…The exploration and production of oil at sea is a risk-filled activity (Skogdalen and Vinnem, 2012;Small et al, 2014), as well its research (Abimbola et al, 2014;Neff et al, 1987). It requires dangerous tasks such as drilling rocks in ultra-deep regions, facing very high pressures and handling large volumes of oil and gas.…”

Section: Introductionmentioning

confidence: 99%

Influence of underwater hydrodynamics on oil and gas blowouts off Amazon River Mouth

et al. 2018

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RESUMO.O estudo está focado na análise do comportamento das plumas de vazamento de óleo/gás em águas profundas, localizadas na plataforma continental do norte do Brasil. O modelo Regional Ocean Modeling System (ROMS) é utilizado para simular a dinâmica oceânica na região 60.5°-24°W/5°S-16°N com 0.25° de resolução, 32 níveis verticais e considerando as descargas dos rios Amazonas e Pará. A saída do modelo ROMS é comparada com o conjunto de dados SODA (Simple Ocean Data Assimilation). ABSTRACT. This study is focused on analyzing the behavior of oil/gas plumes from blowouts into deepwater, located at the northern Brazil continental shelf. The Regional Ocean Modeling System (ROMS) model is used to simulate ocean dynamics in the region 60.5°-24.0°W/5°S-16°N with 0.25° of resolution, 32 vertical levels and considering the discharges of the Amazon and Pará Rivers. The ROMS output are compared to Simple Ocean Data Assimilation (SODA) dataset. Three points were selected to make the numerical simulations, located at (50°W, 5.25°N), (44.5°W, 0.5°N) and (42.75°W, 1°S). The time step suggested by Lee and Cheung (1990) was adjusted due to the particular oceanographic conditions at each point, in which, the initial velocity tends to zero and the coefficient 0.1 of the original equation was replaced by 0.0250 and 0.0375. All the plumes behaved as type 3. The seasonal current speed was small from the bottom to the surface, usually not exceeding 0.25 ms -1 ; the maximum displacement of the plumes from its point of origin was not greater than 1 m. The mean plumes diameter on the surface ranged 54 -79.7 m and the arrival time to the surface was from 7.25 to 8.05 hours.

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“…Other authors have suggested that this is predominantly true, as major crises/disaster situations have been contributed to human errors along with unresponsive culture, bad planning, dishonest behaviour, material failure, the lack of good training and development and management failures. 6,[12][13][14] According to the previously published data, the energy sector has been recognised as one of the main contributors to man-made disasters since the 1970's. [15][16][17][18] In their review of accidents in this sector, Sovacool 17 said that there has been 279 major energy accidents in the coal, oil, natural gas, hydroelectric, renewable, and nuclear sectors resulting in approximately 200,000 deaths and $41 billion in damages from 1907 to 2007.…”

Section: Introductionmentioning

confidence: 99%

“…It is management's role to ensure that employees received adequate training so that human errors are reduced. 6,[12][13][14]36 For these reasons it is important that employees are supported by a strong and competent management team that understands the value of building a competent employee based. 37 Management practices in an organisation have been identified as the "strongest influences on the cultural norms of employees" because it affects employee's expectation and responsibilities about the role of training and innovative behaviour in the workplace".…”

Section: Introductionmentioning

confidence: 99%

An Analysis of the Role of Management in Nuclear Disasters using Text Mining

Novak¹,

Brunetto²,

Brown³

2014

ITMR

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This study uses text mining as a method of examining the role of management and culture in three disasters in the nuclear energy sector, Three Mile Island nuclear reactor explosion (USA 1979), Chernobyl nuclear plant explosion (Ukraine then USSR 1986) and the Fukushima Daiichi nuclear disaster (Japan 2011). The findings identify the role of management in shaping the quality of the crisis and disaster mitigation and preparedness management process employed by organisations. The implications of the findings are that it is imperative for organisations to develop and employ effective crisis/disaster management practice.

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Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study

Cited by 130 publications

References 26 publications

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

Influence of underwater hydrodynamics on oil and gas blowouts off Amazon River Mouth

An Analysis of the Role of Management in Nuclear Disasters using Text Mining

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