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Shahab Mohagegh

AI-based (Top-Down) Reservoir Simulation & Modeling

Shahab Mohaghegh
5:44 Hours
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Sample Lesson
This course offers an in-depth exploration of AI-based (Top-Down) Reservoir Simulation and Modeling, revolutionizing the traditional numerical reservoir simulation used in the petroleum industry over the past six decades. Unlike conventional Bottom-Up approaches, this innovative method employs historical production data and AI-driven Geo-Analytics to model reservoirs from a top-down perspective, eliminating assumptions and biases. The course covers the foundational concepts of artificial intelligence, distinctions between artificial general intelligence and artificial engineering intelligence, and their specific applications in reservoir engineering. Students will gain hands-on experience with advanced AI techniques, including explainable AI, automated history matching, forecasting, and production optimization using specialized software tools. Through this training, engineers will be equipped to leverage AI for faster, more accurate reservoir modeling and decision-making.

Who Should Take This Course
• Reservoir engineers
• Data scientists in oil and gas
• Petroleum industry professionals
• Engineering students and researchers

What You Will Learn
• Use of explainable and ethical AI
• Fundamentals of AI and machine learning
• AI applications in reservoir simulation
• Differences between AI and traditional statistics

Why This Course Works
• Improve accuracy of reservoir models
• Avoid biases with data-driven modeling
• Speed up history matching and forecasting
• Optimize operational and capital expenditures

1.00 – Introduction (12 min.) 
1.01 – Brief History Of Artificial Intelligence (12 min.)
1.02 – Definitions Of Artificial Intelligence And Machine Learning (16 min.)
1.03 – Artificial Intelligence Versus Traditional Statistics (17 min.)
1.04 – Correlation vs. Causation (7 min.)
1.05 – Science And Engineering Application Of Artificial Intelligence (14 min.)
1.06 – Importance of Domain Experts (7 min.)
1.07 – Modeling Physics Using Artificial Intelligence (26 min.)
1.08 – Ethics Of Artificial Intelligence (Ai-Ethics) (21 min.)
1.09 – Explainable Artificial Intelligence (Xai) (23 min.)

2.01 – Top-Down Modeling (10 min.)
2.02 – Characteristics of Top-Down Modeling (22 min.)
2.03 – Geo-Analytics – Ai-Based Geological Modeling (9 min.)
2.04 – Dynamic Conductivity Mapping (16 min.)
2.05 – Automated History Matching (13 min.)
2.06 – Top-Down Modeling Production Allocation (8 min.)

3.01 – Explanation Of The Imagine™ Software Application (4 min.)
3.02 – Using An Actual Case Study (16 min.)
3.03 – Geo-Analytics (9 min.)
3.04 – Data Importing (8 min.)
3.05 – Reservoir Delineation (9 min.)
3.06 – Dynamic Mapping (10 min.)
3.07 – Intelligent Data Patching (9 min.)
3.08 – Predictive Analytics (15 min.)
3.09 – Prescriptive Analytics (4 min.)
3.10 – Operations Optimization (14 min.)

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