The Digital Transformation Conference will draw together members of the Oil & Gas engineering and data science communities, offshore and onshore wind engineering industry, energy storage engineering industry, and university students from around the world who are working on practical, real-world, end-to-end digital solutions that involves machine learning and artificial intelligence. (This is a presentation only conference in 2024)
Track 1: Digital Challenges in Oil & Gas Industry
- Suggested Topics
- Digital Solutions for Onshore – Unconventional Production Optimization
- Real-Time Digital Asset Monitoring and ML/AI Failure Prediction
- Hybrid Modeling in Machine Learning/ Artificial Intelligence for Offshore and Unconventional Wells
- Data Quality (Preparing data for analytics) in Oil & Gas
- Data Governance in Oil & Gas
- Machine Learning Applications for IOTs/ Edge Devices
- Machine Learning/ Artificial Intelligence Standards/Standardization in Oil & Gas
- Machine Learning and Automation in Oil & Gas
- Digital Transformations for Chemical Treatment of Production Wells
- Digital Solutions/ Transformation for Unconventional and Offshore Drilling
- Digital Solutions for Artificial Lift Technologies (Rod, Plunger, PAGL, GAPL, ESPs)
- Digital Solutions for Gas Emissions (Drones, Airplanes, Surface Detectors)
- Generative A.I. (How ChatGPT works) in Oil & Gas
- Computer Vision ML/AI in Oil & Gas
- Case Studies in ML/AI for O&G
- Entrepreneurial Company Showcase – Case Studies
- Cybersecurity in Oil & Gas
- General Topics
Track 2: Digital Challenges in Renewable Energy / Storage
- Suggested Topics
- Digital Solutions for Offshore Wind Generation
- Real-Time Digital Asset Monitoring and ML/AI Failure Prediction
- Digital Solutions for Energy Storage (Batteries, etc…)
- Digital Solutions for Hydrogen Generation, Hybrid Systems, and Storage
- Government Regulations/Compliance for Digital Solutions in Renewable Energy
- Machine Learning/ Artificial Intelligence Standards/Standardization in Renewables
- US Digital Projects in Renewables
- Case Studies in ML/AI for Renewables
- Data Governance in Renewables
- ML/ AI with Optimization
- Adaptive Models for Data Analytics
- Data Analytics for System-of-Systems (multi-physics systems such as mechanical/fluid system)
- Neural Networks-What it is and how it works and how is it trained
- Classifiers and regularization
- Information Content in Data (Does your data have enough information to make analytics worthwhile)
- Entrepreneurial Company Showcase – Case Studies
- Cybersecurity in Renewables
- General Topics