CCS Analytics – AI-based Carbon Capture and Storage

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Disciplines: Data Science and Engineering Analytics | Production and Operations | Reservoir

Course Description

Engineering application of Artificial Intelligence & Machine Learning will significantly address Climate Change in the next several decades. The main reason of positive and important contribution of Artificial Intelligence to Climate Change has much to do with its engineering application that mainly uses reality and facts and avoids marketing, business, and political ideas. Part of the CCS-Analytics incorporates Reservoir Engineering application of Artificial Intelligence & Machine Learning for CO2 Storage in geological formations in order to positively impact Climate Change through science and technology.

Topics:

• Climate Change
• Carbon Capture and Storage (Sequestration)
• Basics of Artificial Intelligence (AI) and Machine Learning (ML)
• Engineering Application of Artificial Intelligence
• CCS-Analytics
• CCS-Analytics for Greed Fields
• CCS-Analytics for Depleted Hydrocarbon Reservoirs
• CCS-Analytics Case Studies

Learning Level

Intermediate to Advanced

Course Length

1 day

Why Attend

This course will play a crucial role for the enthusiasts of engineering application of Artificial Intelligence and Machine Learning technology in Carbon Capture and Storage. It covers the scientific and realities foundation of Artificial Intelligence and Machine Learning and its true application in Reservoir Engineering used for CCS. If you are interested to be knowledgeable with the most up-to-date and accurate AI and Machine Learning technology? This class will get you there!

Who Attends

This course is designed for geo-scientists, engineers, and managers. Specifically, those involved with geology, drilling, reservoir, completion, and production in operating and service companies. In general, those involved in planning, completion, and operation in assets are the main target audience.

CEUs

0.8 CEUs are awarded for this 1-day course.

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructor

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