Skip to main content
Computer, Electrical and Mathematical Sciences and Engineering
CEMSE
Computer, Electrical and Mathematical Sciences and Engineering
Home
Study
Prospective Students
Current Students
Internships
Research
Research Overview
Research Areas
Research Groups
Programs
Applied Mathematics and Computational Sciences
Computer Science
Electrical and Computer Engineering
Statistics
People
All People
Faculty
Affiliate Faculty
Instructional Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Students
Alumni
Administrative Staff
News
Events
About
Who We Are
Message from the Dean
Leadership Team
Apply
Eye
Dark Vision: A Sensory Eye into Subsurface Wellbore Casings
Shehab Ahmed, Professor, Electrical and Computer Engineering
Aug 29, 12:00
-
13:00
KAUST
Dark Vision
Sensory
Eye
Subsurface
Wellbore
After a quick overview of the ECE Graduate Seminar logistics, I will share a quick introduction to the wellbore construction process. This will help build the case for maintaining wellbore integrity in order to protect assets, people, the environment and production. The synergistic integration of electromagnetics, electronics and machine learning to create a novel mechatronic solution to address wellbore integrity needs is then discussed. The solution utilizes a full maxwell equations solver deployed on KAUST’s super computing platforms to enable next generation physics informed wellbore integrity solutions based on non-contact EM field propagation circuits. While downhole camera technologies are used today, they require illumination and an optically clear environment. Our electromagnetic ‘vision’ system overcomes these limitations and provides additional capability to ‘see through’ nested wellbore tubulars.