DATA - Characterization, Drilling and Completions Analytics
Wednesday, 13 March
PALOMINO F-H
Technical_and_Invited_Presenter
In this session, we present a diverse range of topics in the realm of Characterization and Drilling Completion Analytics, offering insights into cutting-edge techniques and methodologies:
Explore the prediction of mineralogical composition in unconventional reservoirs, comparing data-driven and chemistry-based models.
Discover the application of physics-informed neural networks for CH4/CO2 adsorption characterization and learn about implementing continuous feedback loops for autonomous drilling, optimizing operations between surface and downhole.
Explore the prediction of mineralogical composition in unconventional reservoirs, comparing data-driven and chemistry-based models.
Discover the application of physics-informed neural networks for CH4/CO2 adsorption characterization and learn about implementing continuous feedback loops for autonomous drilling, optimizing operations between surface and downhole.
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1000-1030 218116Prediction of Mineralogical Composition in Heterogeneous Unconventional Reservoirs: Comparisons between Data-driven and Chemistry-Based Models
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1030-1100 218117Continuous Feedback Loop between Surface and Downhole for Autonomously Drilling a Section
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1100-1130Towards Optimized Completion: A Data-Driven Proxy for WCSB Wells
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Alternate 218029Physics-Informed Neural Network for CH4/CO2 Adsorption Characterization