Big Data for Reservoir Surveillance
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For PEA Members Only
This workshop examines how big data technologies are reshaping reservoir surveillance, enabling faster insights and more accurate decision-making. Participants will learn how to leverage data integration, analytics, and visualization tools to monitor reservoir performance and optimize field development strategies.
Workshop Objectives
• Understand the role of big data in modern reservoir surveillance.
• Learn methods for integrating and analyzing large, diverse datasets.
• Explore applications of predictive analytics and real-time monitoring.
• Apply data-driven insights to enhance production and reservoir management.
About the Presenter
The workshop will be delivered by an experienced professional in reservoir engineering, data analytics, and digital oilfield solutions. Combining technical knowledge with practical field experience, the presenter shares actionable strategies to help participants unlock value from data in reservoir surveillance.
Premium Workshop
For PEA Members Only
Machine Learning for Drilling Engineering with Python
Drilling generates huge amounts of data — but most of it sits unused. This hands-on workshop shows you how to turn that data into better decisions using Python and machine learning.Over the sessions, you'll work with real drilling datasets to build models that predict problems before they happen — stuck pipe, ROP optimization, bit wear, formation changes, and more. No heavy math theory. You write code, run it on actual data, and see the results.By the end, you'll have working Python scripts you can adapt to your own field data, plus a clear understanding of where ML adds value in drilling and where it doesn't.Built for drilling engineers, not data scientists. If you can read a drilling report, you can follow this course.