The digital learning ecosystem An efficient management approach to capability development, delivering smarter teams, improved productivity and better business outcome for the managers.
Bridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
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Training provider of the year: 2013, 14 and 15
Digital Technology Courses Understand the impact of digital technologies on E&P business and industry
Upstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableUpstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableBridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
Develop measurable skills and capabilities
Risks and uncertainties are everywhere in E&P projects. Risk and uncertainty impact decision making by the projects chosen, how they are developed, and their economic performance. Improving the quality of decisions is the main goal, not just understanding risk and uncertainty for their own sake.
Although probabilistic concepts and tools are commonly used to describe projects under risk and uncertainty, the principles underlying these concepts and tools are not always well understood. Upon completion of this course, participants will become more comfortable with probabilistic thinking and how it can be used to improve decision making.
The instructor, Dr. Pierre Delfiner, is the recipient of the 2018 Society of Petroleum Engineers' International Award for Management & Information.
Risk and Decision Analysis
In Day 1 basic concepts of probability and economics will be recalled, and decision analysis tools presented. A case study will illustrate the value of perfect information and another will combine decision trees and Bayesian inversion to show how the probability of geologic success should be revised to incorporate new seismic information and how the quality of this information impacts its value.
Day 2Decision continued and Uncertainty
After completion of the VOI case study Day 2 will follow with psychological aspects of decision making. The rest of the day will be devoted to a review of the most common descriptive statistics and a discussion of estimation in general.
Day 3Monte Carlo and Applications
Day 3 will focus on Monte Carlo simulation and hands-on applications. A case study of estimation of the production increase expected from a workover program will demonstrate the importance of scale in assessing uncertainty. The issues of multi-prospect evaluation will close the day.
Day 4Cluster Developments
Half of Day 4 will be devoted to modeling the development of geologically dependent reservoirs drilled by a single well and of a cluster of dependent, geographically dispersed, fields drilled separately, and to providing scenarios for planning and economics. Portfolio issues will be briefly discussed and an exercise will illustrate the effects of diversification. The day will close with correlation and its significance.
Day 5
Trend Lines and Review
In Day 5 uncertainty on fluid densities computed from pressure data will take participants through the various steps involved in establishing and checking a regression model and deriving prediction uncertainty. The session will end with a wrap-up of the week, main technical messages, and answering questions from the audience.
Anyone interested in learning more about the approach and techniques of risk, uncertainty, and decisions in E&P projects.
Some basic statistics knowledge would be a plus but is not required.
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