Quantification of Risks Associated With a Representative Production Well in the Gulf of Mexico

2015 ◽  
Author(s):  
Muhammad Zulqarnain ◽  
Mayank Tyagi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Gulf Of Mexico ◽  
Fault Tree ◽  
Quantitative Risk Assessment ◽  
Delayed Response ◽  
Production Well ◽  
Reservoir Properties ◽  
Worst Case ◽  
Sand Control

After Macondo incident a great effort is under way to improve the safety of deepwater drilling and production operations and enhance the capabilities of different well barrier to stop the oil spill on its earliest stages. This study is a part of that collective effort to make offshore operations safe and decrease the associated risks. The main objective of this study is to quantify and categorize the risk associated with a representative well in the Gulf of Mexico during its normal production operations. In order to achieve an appropriate balance between safety and economics of deepwater oil and gas operations, Quantitative Risk Assessment (QRA) techniques can be successfully used. Quantified risk is computed from the product of blowout frequency and volume of oil spilled as a consequence. Blowout frequency is calculated from Fault Tree Analysis (FTA) and spilled oil volume is estimated from simulating multiphase fluid flow and heat transfer in wellbores. A large number wells are completed with some sort of bottom hole sand control elements to prevent production of sand. The failure of these control elements may have severe consequence and in some cases may result in uncontrolled hydrocarbon flow to the environment as well. A representative production well from the Mississippi Canyon in the Gulf of Mexico is selected for the for quantitative risk assessment (QRA) analysis. The well is completed with cased hole gravel pack and with sand control elements in place. The representative reservoir properties for this well are selected from the literature and uncertainties in properties are accounted for by fitting lognormal distribution and carrying out Monte Carlo simulations. P50 value for the reservoir properties from Monte Carlo simulation is used to find worst case discharge rates by using a commercially available multiphase flow simulator with black oil model. A Fault Tree is constructed to find the blowout probability based on the equipment failure data. From the minimal cut set method the importance and sensitivity of different well barrier is analyzed and most important areas to focus on are identified. The analysis showed that the constructed fault tree is most sensitive to sand screen failures, followed by subsea production tree and delayed response to a situation of immediate concern.

Quantitative Risk Assessment (QRA) of an Exploratory Drilling Oil Spill in Deepwater Gulf of Mexico

2014 ◽  
Author(s):  
Muhammad Zulqarnain ◽  
Mayank Tyagi
Keyword(s):  
Risk Assessment ◽  
Gulf Of Mexico ◽  
Drill Pipe ◽  
Quantitative Risk Assessment ◽  
Reservoir Properties ◽  
Worst Case ◽  
Equipment Reliability ◽  
Discharge Rates ◽  
First Case ◽  
Technological Improvements

Major offshore accidents such as Macondo well incident highlight one of the possible failure modes and subsequent disasters when an offshore engineering project could go wrong. Such events can potentially happen during any phase of an offshore well’s life — starting from the exploratory drilling phase to the final phase of plug and abandonment. Major factors that significantly contribute in defining such accident scenarios are the geological and operational complexities, equipment reliability, human factors, geographical/economy location, and environmental conditions. The path taken by the reservoir fluids to reach the sea floor is also an important factor in determining the worst case discharge rates. It is expected that the environmental risks from an oil/gas spill would also be function of the type of hydrocarbons released and duration of the spill. A representative Neogene well is studied for quantitative risk assessment (QRA) for spill in exploratory phase from the Mississippi Canyon in the Gulf of Mexico with a water depth of 3,000ft and total vertical depth of 16,726 ft and the representative reservoir properties for this area are selected from the literature. Due to the large variation of reservoir properties, lognormal distributions have been assumed for some of the reservoir properties and from the Monte Carlo simulations P10, P50 and P90 values are estimated. Based on P50 and P90 values, the worst case discharge rates are calculated using a commercially available multiphase flow simulator with black oil model. Based on historical trends, release of hydrocarbons during blowouts are simulated for the following circumstances: seabed and topside releases, restricted and unrestricted flow through BOP, flow with drill pipe inside the wellbore and open hole flow without drill pipe and flow from the reservoir when it is either fully or partially penetrated. To incorporate the technological improvements and study their effects on the reduction of the overall risk associated with deepwater drilling activity, two cases are considered and compared to each other. First case is based on the historical data and the second case is a modified version of the first case by incorporating some of the recent technological improvements and newly built oil spill response systems e.g. capping stacks. The historical kick statistics and the equipment reliability data available in the literature is used to analyze various scenarios and corresponding flow rates. Risk is analyzed using the failure probability and consequence analysis and is presented in the form of a risk matrix for the different case studied and for the overall drilling activity as well.

Risk assessment of Campylobacter species in shellfish: identifying the unknown

1997 ◽  
Vol 35 (11-12) ◽  
pp. 29-34 ◽  
Author(s):  
P. Teunis ◽  
A. Havelaar ◽  
J. Vliegenthart ◽  
G. Roessink
Keyword(s):  
Risk Assessment ◽  
Quantitative Risk Assessment ◽  
Contamination Level ◽  
Risk Of Infection ◽  
Worst Case ◽  
Considerable Uncertainty ◽  
Risk Estimates ◽  
Consumption Data ◽  
Campylobacter Infection ◽  
Campylobacter Spp

Shellfish are frequently contaminated by Campylobacter spp, presumably originating from faeces from gulls feeding in the growing or relaying waters. The possible health effects of eating contaminated shellfish were estimated by quantitative risk assessment. A paucity of data was encountered necessitating many assumptions to complete the risk estimate. The level of Campylobacter spp in shellfish meat was calculated on the basis of a five-tube, single dilution MPN and was strongly season-dependent. The contamination level of mussels (<1/g) appeared to be higher than in oysters. The usual steaming process of mussels was found to completely inactivate Campylobacter spp so that risks are restricted to raw/undercooked shellfish. Consumption data were estimated on the basis of the usual size of a portion of raw shellfish and the weight of meat/individual animal. Using these data, season-dependent dose-distributions could be estimated. The dominant species in Dutch shellfish is C. lari but little is known on its infectivity for man. As a worst case assumption, it was assumed that the infectivity was similar to C. jejuni. A published dose-response model for Campylobacter-infection of volunteers is available but with considerable uncertainty in the low dose region. Using Monte Carlo simulation, risk estimates were constructed. The consumption of a single portion of raw shellfish resulted in a risk of infection of 5–20% for mussels (depending on season; 95% CI 0.01–60%). Repeated (e.g. monthly) exposures throughout a year resulted in an infection risk of 60% (95% CI 7–99%). Risks for oysters were slightly lower than for mussels. It can be concluded that, under the assumptions made, the risk of infection with Campylobacter spp by eating of raw shellfish is substantial. Quantitative risk estimates are highly demanding for the availability and quality of experimental data, and many research needs were identified.

Seismic Quantitative Risk Assessment of Process Plants Through Monte Carlo Simulations

2016 ◽  
Author(s):  
Silvia Alessandri ◽  
Antonio C. Caputo ◽  
Daniele Corritore ◽  
Renato Giannini ◽  
Fabrizio Paolacci
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Seismic Risk ◽  
Quantitative Risk Assessment ◽  
Damage Propagation ◽  
Process Plants ◽  
Physical Effects ◽  
Level 1 ◽  
Level I ◽  
Seismic Hazard Curve

This paper describes the application of Monte Carlo method for the quantitative seismic risk assessment (QSRA) of process plants. Starting from the seismic hazard curve of the site where the plant is located, the possible chains of accidents are modelled using a sequence of propagation levels in which Level 0 is represented by the components directly damaged by the earthquake whereas the subsequent Levels represent the resulting consequence propagation. In greater detail all units damaged by energy and materials releases from level 0 units are included in level 1 and so forth, so that referring to process units belonging to a generic i-th Level, they are damaged by level (i-1) units and damage units of level (i+1). The sequence of levels represents the damage propagation across the plant through any multiple interacting sequences of accidents. For each unit a damage (DM) - loss of containment (LOC) matrix is generated allowing to estimate the amount of energy and material releases as well as resulting physical effects based on which the scenario at i-th level is generated. The process stops when no further damage propagation is allowed.

Development and Implementation of a Liquid Pipeline Quantitative Risk Assessment Model

2014 ◽  
Author(s):  
Jerico Perez ◽  
David Weir ◽  
Caroline Seguin ◽  
Refaul Ferdous
Keyword(s):  
Risk Assessment ◽  
Risk Reduction ◽  
Assessment Tool ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Pipeline System ◽  
Risk Assessment Model ◽  
Worst Case ◽  
Risk Appetite ◽  
Assessment Results

To the end of 2012, Enbridge Pipelines employed an in-house developed indexed or relative risk assessment algorithm to model its liquid pipeline system. Using this model, Enbridge was able to identify risk control or treatment projects (e.g. valve placement) that could mitigate identified high risk areas. A changing understanding of the threats faced by a liquid pipeline system and their consequences meant that the model changed year over year making it difficult to demonstrate risk reduction accomplished on an annual basis using a relative scoring system. As the development of risk management evolved within the company, the expectations on the model also evolved and significantly increased. For example, questions were being asked such as “what risk is acceptable and what risk is not acceptable?”, “what is the true risk of failure for a given pipe section that considers the likelihood of all threats applicable to the pipeline”, and “is enough being done to reduce these risks to acceptable levels?” To this end, starting in 2012 and continuing through to the end of 2013, Enbridge Pipelines developed a quantitative mainline risk assessment model. This tool quantifies both threat likelihood and consequence and offers advantages over the indexed risk assessment model in the following areas: • Models likely worst case (P90) rupture scenarios • Enables independent evaluation of threats and consequences in order to understand the drivers • Produces risk assessment results in uniform units for all consequence criteria and in terms of frequencies of failure for likelihood • Aggregates likelihood and consequence at varying levels of granularity • Uses the risk appetite of the organization and its quantification allows for the setting of defined high, medium, and low risk targets • Quantifies the amount of risk in dollars/year facilitating cost-benefit analyses of mitigation efforts and risk reduction activities • Grounds risk assessment results on changes in product volume-out and receptor sensitivity • Balances between complexity and utility by using enough information and data granularity to capture all factors that have a meaningful impact on risk Development and implementation of the quantitative mainline risk assessment tool has had a number of challenges and hurdles. This paper provides an overview of the approach used by Enbridge to develop its quantitative mainline risk assessment model and examines the challenges, learnings and successes that have been achieved in its implementation.

scholarly journals Analysis and risk assessment of risk technical systems to develop of methodology for teaching students using the method fault tree

2019 ◽  
Vol 6 ◽  
pp. 17-27
Author(s):  
Tsvetelina Simeonova
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Fault Tree ◽  
Quantitative Risk Assessment ◽  
Web Based ◽  
Qualitative And Quantitative ◽  
Student Training ◽  
Technical Systems ◽  
Risk Analysis And Management ◽  
Tree Method

The aim of the present work is to develop a methodology for conducting exercises for analysis, assessment and management of risk, using a web based tool by identifying and analyzing the risk of occurrence of a dangerous event through the fault tree method. As a result, a framework is presented according to the proposed methodology applicable to the students' training in risk analysis, evaluation and management, and according to accepted assumptions. Approaches for qualitative and quantitative risk assessment are presented at the assumed value of the damages. In addition, a methodology for risk analysis, assessment and management applicable to student training on risk analysis and management has been developed and proposed.

The Application of Quantitative Risk Assessment to Microbial Food Safety

1998 ◽  
Vol 61 (5) ◽  
pp. 640-648 ◽  
Author(s):  
DAVID JOHN VOSE
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Food Safety ◽  
Probability Distributions ◽  
Simulation Models ◽  
Practical Method ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Suitable Model

Quantitative risk assessment (QRA) is rapidly accumulating recognition as the most practical method for assessing the risks associated with microbial contamination of foodstuffs. These risk analyses are most commonly developed in commercial Computer spreadsheet applications, combined with Monte Carlo simulation add-ins that enable probability distributions to be inserted into a spreadsheet. If a suitable model structure can be defined and all of the variables within that model reasonably quantified, a QRA will demonstrate the sensitivity of the severity of the risk to each stage in the risk-assessment model. It can therefore provide guidance for the selection of appropriate risk-reduction measures and a quantitative assessment of the benefits and costs of these proposed measures. However, very few reports explaining QRA models have been submitted for publication in this area. There is, therefore, little guidance available to those who intend to embark on a full microbial QRA. This paper looks at a number of modeling techniques that can help produce more realistic and accurate Monte Carlo simulation models. The use and limitations of several distributions important to microbial risk assessment are explained. Some simple techniques specific to Monte Carlo simulation modelling of microbial risks using spreadsheets are also offered which will help the analyst more realistically reflect the uncertain nature of the scenarios being modeled. simulation, food safety

Quantitative Risk Assessment for Human Salmonellosis through the Consumption of Pork Sausage in Porto Alegre, Brazil

2011 ◽  
Vol 74 (4) ◽  
pp. 553-558 ◽  
Author(s):  
LISANDRA MÜRMANN ◽  
LUIS GUSTAVO CORBELLINI ◽  
ALEXANDRE ÁVILA COLLOR ◽  
MARISA CARDOSO
Keyword(s):  
Risk Assessment ◽  
Cooking Time ◽  
Quantitative Risk Assessment ◽  
Average Risk ◽  
Porto Alegre ◽  
Case Scenario ◽  
Worst Case ◽  
Pork Sausage ◽  
The People ◽  
Pork Sausages

A quantitative microbiology risk assessment was conducted to evaluate the risk of Salmonella infection to consumers of fresh pork sausages prepared at barbecues in Porto Alegre, Brazil. For the analysis, a prevalence of 24.4% positive pork sausages with a level of contamination between 0.03 and 460 CFU g−1 was assumed. Data related to frequency and habits of consumption were obtained by a questionnaire survey given to 424 people. A second-order Monte Carlo simulation separating the uncertain parameter of cooking time from the variable parameters was run. Of the people interviewed, 87.5% consumed pork sausage, and 85.4% ate it at barbecues. The average risk of salmonellosis per barbecue at a minimum cooking time of 15.6 min (worst-case scenario) was 6.24 × 10−4, and the risk assessed per month was 1.61 × 10−3. Cooking for 19 min would fully inactivate Salmonella in 99.9% of the cases. At this cooking time, the sausage reached a mean internal temperature of 75.7°C. The results of the quantitative microbiology risk assessment revealed that the consumption of fresh pork sausage is safe when cooking time is approximately 19 min, whereas undercooked pork sausage may represent a nonnegligible health risk for consumers.

scholarly journals Risk Assessment Models to Improve Environmental Safety in the Field of the Economy and Organization of Construction: A Case Study of Russia

2021 ◽  
Vol 13 (24) ◽  
pp. 13539
Author(s):  
Arkadiy Larionov ◽  
Ekaterina Nezhnikova ◽  
Elena Smirnova
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Rapid Development ◽  
Environmental Safety ◽  
Quantitative Risk Assessment ◽  
Optimal Decision ◽  
Environmental Damage ◽  
The Monte Carlo Method ◽  
The Future

This article assesses risks in order to substantiate the economic and organizational efficiency of housing and industrial construction. This topic is relevant because it is necessary for sustainable development. In Russia, environmental safety in construction and housing, as well as communal services, is poorly developed and not regulated by the legal system. As building construction, housing, and communal services should be based on environmental safety, this topic requires rapid development. Methods related to quantifying environmental risk and making decisions under conditions of uncertainty were studied. A quantitative risk assessment was performed using the Monte Carlo method for pessimistic and optimistic options to prevent environmental damage. The model reproduced the distribution derived from the evidence-based fit. The results of sensitivity analysis are also presented to prove the hypothesis. The selection of the most appropriate probability density functions for each of the input quantities was implemented through settings in a computer program. The simulation modeling results clearly illustrate the choice of the general principle of assessment and the adoption of the optimal decision. In conditions of uncertainty, the decision to choose the optimistic options with high cost (to maintain the reliability of the technical system) but less risk plays a decisive role in the future environmental safety strategies of construction projects. The Monte Carlo method is preferable for environmental impact assessments. In the future, the amended methodology can be applied to raise environmental safety in the field of construction.

scholarly journals Analysis and risk assessment of risk technical systems to develop of methodology for teaching students using the method dynamic fault tree

2019 ◽  
Vol 6 ◽  
pp. 115-123
Author(s):  
Tsvetelina Simeonova
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Fault Tree ◽  
Quantitative Risk Assessment ◽  
Web Based ◽  
Qualitative And Quantitative ◽  
Dynamic Fault Tree ◽  
Student Training ◽  
Risk Analysis And Management ◽  
Tree Method

The aim of the present work is to develop a methodology for conducting exercises for analysis, assessment and management of risk, using a web based tool, by identifying and analyzing the risk of occurrence of a dangerous event through the dynamic fault tree method. As a result, a framework is presented according to the proposed methodology applicable to the students' training in risk analysis, evaluation and management, and according to accepted assumptions. Approaches for qualitative and quantitative risk assessment are presented at the assumed value of the damages. In addition, a methodology for risk analysis, assessment and management applicable to student training on risk analysis and management, through the dynamic fault tree method, has been developed and proposed.  

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