Broadcast Date:Wednesday, 8 November, 2023
Broadcast Time:11:00 AM CST (Central Time, US)
Duration:60 minutes
Abstract:
This talk goes over transformational potential of artificial intelligence (AI) for automating the various integration pipelines. In particular we look into two case studies including the feasibility for carbon capture and storage (CCS) monitoring, and also earthquake prediction in case of waste water disposal. We propose an innovative AI-driven workflow that not only streamlines the process but also enhances the accuracy of feasibility predictions. In addition, we present a detailed discussion of the potential benefits of our approach, such as greater cost-effectiveness, increased accessibility and scalability, and reduced manual labour.
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Speakers
Amir Shamsa Domain Data Scientist SLB Amir Shamsa is a senior consultant who has been working in SLB for past 10 years. During his time at SLB, he has developed his skills in reservoir characterizations, software development and domain data science in last three years.
He has graduated with a PhD in Geophysics from University of Calgary in 2015. Amir has conducted many conventional and unconventional reservoir characterization, and more recently data driven projects. He has numerous journal publications and conference presentations.
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