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Oil & Gas Training
and Competency Development 1
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#### Courses  # Risk and Reliability Engineering

This course provides the basic knowledge and tools to determine the risk and reliability of equipment, a process and a system. It is designed to be 50% theoretical and 50% practical.

Day 1
• Introduction
• Basic Concepts
• Risk
• Risk Analysis
• Reliability
• Reliability Engineering
• Uncertainty – Uncertainty Management
• Asset Life Cycle Economic Analysis
• Deterministic Model
• Probabilistic Model
• Risk-Based Life Cycle Economic Analysis
• An Integrated Approach to Optimize the Economy of the Asset Life Cycle”
• Concept, Applications and Benefits
• Integrated Reliability Toolkit
• Disciplines
• Methodologies
Day 2
• Statistics for Risk and Reliability Analysis
• Basic Terms (Probability, Population, Sample, Descriptive Statistics, Random Variable)
• Descriptive Statistics
• Sample Statistics
• Histograms •
• Statistics (Sample Mean, Sample Mode, Sample Standard Deviation, Percentiles)
• Using Excel™ for sample statistics
• Population Statistics
• Probability Distribution Models
• Probability Distribution Formats (pdf, CDF, Inverse CDF)
• Statistics of probability distributions (Mean, Mode, Median,
• Probabilistic characterization of a sample or How to select a probability distribution model for a given sample.
• Goodness of fit Tests
• Use of software for goodness of fit tests. Statistics for Risk and Reliability Analysis
• Solving mathematical models (equations) random variable input parameters
• Sampling from a random variable
• Monte Carlo Simulation
• Using Excel™ for Monte Carlo Simulation
• Probabilistic Dependence
• Correlated Random Variables – Correlation Factor
• How to consider probabilistic dependence in Monte Carlo Simulation
Day 3
• Principles of Production Processes Reliability Analyisis
• Reliability, Availability and Maintainability (RAM)
• Analysis for Repairable Items
• Samples Data for RAM Analysis of repairable items
• Up-Time Data (Failure Data and Censored Data)
• Down Time Data
• Probability Distribution for Up -Time Samples in Repairable Items
• Probability Distribution for Down-Time Samples in Repairable Items
• Methodology for Availability and Expected Number of Failures calculations for Repairable items
• Availability and Expected Number of Failures Calculations
• Sources of Data for Reliability Analysis
• Evidence, Expert Opinion, Generic Data • Combining different sources of data
• Bayes Theorem
• Combining Generic Data with Evidence
• Combining Expert Opinion with Evidence
• System Availability and Expected Number of Failures Calculations
• Forecasting failures and availability of a pumping system
• Forecasting failures and availability in an ESP Oil Well
Day 4
• Principles of Financial Analysis
• Basics Terms and Definitions
• Life time of an investment , Projected Cash Flow, Discount Rate
• Financial Indicators • Net Present Value (Deterministic Model, Probabilistic Model)
• Annualized Present Value (Deterministic Model, Probabilistic Model)
• Principles of Risk Analysis
• Basic Terms and Definition
• Undesired Events
• Basic Model
• Qualitative and Semi-Quantitative Methods for Risk Analysis
• Quantitative Risk Analysis (QRA)
• An ESP Oil Well QRA Example
Day 5
• Risk Based Asset Economic Life Cycle Analysis
• General Model
• Monte Carlo calculation of NPV
• Sensitivity Analysis of Probabilistic NPV
• Determining the Risk Mitigation Actions Portfolio
• Comparing Investments Options – Risk / Profitability Matrix
• Final Exercise: Life Cycle Economic Analysis of an ESP Oil Well

Production engineers, Surface facilities Engineers, Reliability Engineers and Maintenance Engineers

Currently there are no scheduled classes for this course.

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