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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. EnjoyableBridging 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. 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
As the name Magneto-Telluric (MT) already suggests, it involves Magnetic as well as Telluric (Earth current) phenomena. We start with considering the Earth’s magnetic field, then continue with modeling the response of magnetizable bodies, followed by studying the influence of conductive/resistive bodies on electrical currents and understanding Electro-Magnetism (EM).
There are many ways in which EM is measured and used. For example, controlled-source EM (CSEM, TDEM) and natural-source generated fields in the Earth (MT), which enable observations of very long periods (low frequencies) enabling investigations to great depth. These data are (jointly with other data) inverted to derive Earth properties.
In the course you will study relevant chapters of a book, presentations, look at videos and make many exercises. Multiple-choice quizzes are provided to enhance the learning. Each possible answer of a quiz to the questions can be tried and might invite you to go back to the course material. The course uses a Blended Learning approach based on a user-friendly Learning Management System, called Moodle.
This course is a blended course. It is lead remotely by the instructor that has daily direct interactions with the trainees for several hours. Trainees are self-learning for the rest of the day by doing exercises and going through the course material.
The course consists of presentations, videos, and exercises. The presentations, also made available in pdf, are animated power point shows. The videos are either related to the exercises or general, some related to professional societies. In the exercises the methods discussed in the presentations are applied using computer programs. The solutions are discussed. Also, the course contains quizzes which are meant to reinforce the learning. Each quiz consists of multiple-choice questions.
Part 1
Part 2
Part 3
Part 4
Part 5
Geophysicists and interpreters who deal with the acquisition, processing and interpretation of MagnetoTelluric data, especially those involved in looking for reservoirs below salt or volcanics.
Although electromagnetics (EM) is fundamental to the topic of this course (MT), the aim is not to fully master the underlying physics, but to understand its importance in relation to the geophysical context of MagnetoTelluric. Other applications of electromagnetics (controlled-source EM, time-domain EM) in geophysics will be discussed, as the resulting data is often jointly inverted with MT. In relation to EM, an interesting question remains, do we deal with diffusion or wave propagation and if wave propagation, how are these waves refracted at resistivity contrasts. How is (joint) inversion of MT data best done? In addition, the importance of Machine Learning will be demonstrated.
A basic understanding of geophysics.
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