CODE: OG50
DURATION: 5 Days/10 Days
CERTIFICATIONS: CPD
This course gives an introduction to integrating artificial intelligence techniques with traditional reservoir engineering and simulation practices. It bridges the gap between conventional simulation workflows and advanced AI methodologies, offering both theoretical foundations and practical case studies to illustrate real-world applications. Participants will explore how machine learning, deep learning, and data-driven modeling can enhance reservoir characterization, optimize production strategies, and improve forecasting accuracy.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the role of AI in reservoir simulation and forecasting.
Apply machine learning and deep learning techniques to reservoir modeling.
Integrate AI workflows with traditional simulation methods to enhance accuracy and efficiency.
Perform data-driven production forecasting and uncertainty quantification.
Evaluate and implement AI-driven tools for improved reservoir management and decision-making.
At the end of this course, you’ll understand:
This course is designed for reservoir engineers, petroleum engineers, data scientists, and energy professionals seeking to enhance their skills at the intersection of AI and reservoir simulation. It is also highly relevant for researchers, and decision-makers in the oil and gas sector who want to leverage AI-driven insights for improved reservoir management and production forecasting. A basic understanding of reservoir engineering principles and data analytics is recommended but not mandatory.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
