
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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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. Enjoyable
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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During this course quick-look methods will be expanded on, to include deterministic and probabilistic evaluations. Several various tools will be introduced, such as NMR, image logs, production surveillance, and other special interest devices. LWD and MWD concepts will be discussed and compared to wireline logs. Quality assurance of data and interpretation will be emphasized throughout the week. The physics of measurements along with practical discussions of theory will allow each participant to follow simple procedures for the rapid and accurate interpretation of logs.
The learning objectives for intermediate formation evaluation will include improved estimates of intrinsic reservoir properties, petrophysical analysis for improved saturation predictions, define analysis methods, reservoir compartmentalization, and MDT/RFT data components in reservoir characterization studies. Understanding how dip and image logs are used, as well as using mechanical rock properties will also be covered.
To help participants accomplish the daily learning objectives the will be given hands-on problems and exercises with field examples to reinforce the course instruction.
Petrophysicists, geoscientists, and reservoir and petroleum engineers are the intended audience for this course.
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