Monday, June 07
This course starts with the basic Machine Learning concepts, application workflows and the supervised and unsupervised learning algorithms. The commonly used algorithms in both categories such as Clustering, Artificial Neural Networks, Decision Trees, Support Vector Machine will be presented, allowing participants to reach a clear understanding on their strengths. Specific examples will be discussed to demonstrate the application of each algorithm in the development of unconventional tight/shale reservoirs. The course is devoted to field applications of this technology with a focus on reservoir characterization, production analysis and prediction, and recovery enhancement.
Tuesday, June 08
With advancing analytics tools and techniques across the oil and gas industry companies are now, more than ever able to unlock the value of their data. These advancements are allowing companies to find and produce more hydrocarbons, in economically sound and environmentally friendly ways. In this session, you will hear from industry leaders on the journey they took to gain value from implementing these strategies to date, as well as how they plan to invest more resources into analytics and other digital solutions moving forward.
Opening Keynote Presentation
Vice President Data and Analytics
Moderator: Melanie Popp, Senior Engineering Advisor, geoLogic
Chris Carlsen, VP, Engineering, Birchcliff Energy
Sasha Schmick, Data Science and Analytics Manager, ConocoPhillips
Sheldon Wall, Manager Advanced Analytics, Suncor Energy
Nick Wallat, Senior Manager, Development and Innovation, CNOOC International
There is immense opportunity for digital innovation in the oil and gas industry, but how do you get started? Tune in to hear stories of how innovative professionals took their interests from “side of the desk” to priority number one in their organizations. This session will also feature best practices for the successful implementation of scalable processes in both projects and organizations.
- Good Practices for Useful ML Models in O&G Development
- Tyler Schlosser, McDaniel & Associates
Pivoting Products to Profit: Intrapreneurship
- Jocelyn McMinn, Peloton Frac
Panel Discussion: Be the Change - Tips for Grassroots Innovation
Moderator: Mark Derry, Cenovus Energy
- Marc Boulet, Cenovus Energy
- Darcy Redpath, PETRONAS Canada
- Theresa Smith, TransAlta
Every successful digital strategy, analytics program or analytics project is built on a solid foundation of best practices that are spread across the digital ecosystem and throughout the enterprise. This session will showcase key strategies and best practices that enable successful analytics initiatives and support the integration of analytic tools and models into engineering workflows. Presentations will focus on strategies for data accessibility, security and governance, as well as data product development and deployment.
- Lessons from the Trenches: Cloud Migration of Completion Optimization
- Scott McKean, Chevron
- Using Dashboards as a Tool for QC for Well Databases
- Akshay Gulati
- Cloud Paradigms: Designing and Creating Data Products for the Age of Cloud
- Ted Kernan, geoLOGIC
Wednesday, June 09
Decision making in presence of large amount of hard to synthesize and conflicting data is an everyday problem in the fully integrated areas of asset development & subsurface. Application of Data Analytics, Machine Learning and Artificial Intelligence has provided a viable and effective solution to overcome these challenges. This session focuses on application of Data Analytics in subsurface design and development planning to ultimately support better decision making.
- How to Approach Subsurface Processes Using Machine Learning Challenges and Lessons Learnt
- Nithya Mohan, ConocoPhillips Norway
- Bayesian Mixed Models and Workflow for Optimizing Well Design and Predicting Future Well Performance
- Sean Kristjansson, Ovintiv
Drilling and completions operations are an operators’ fleeting opportunity to impact a wells long term production and economic performance – seizing every optimization opportunity is critical. Learn how our speakers are leveraging data and advanced analytics to streamline their operations leading to more profitable wells. Doing so requires more than just technology - our speakers discuss the impacts of the ongoing digital shift on workflows and the changes needed to fully realize the potential.
- Semi-Supervised Approach to Clustering Time-Series Based Sand Schedules for Hydraulic Fracture Stages
- Pierce Anderson, Ala Qabaja, ARC Resources
- Streamlining Organizational Capability in Well-Construction Using Data Analytics
- Chris Schneider, Corva; Michael Lowder, Corva
- AI-Enabled Automated Digital Dull Bit Analysis, Forensics and Analytics
- Ron Schmitz, Trax Electronics
Optimizing existing producing assets is the most capital efficient way to add production. This session will showcase how operators are leveraging data analytics and machine learning to increase asset performance and efficiencies based on their high resolution data.
- Leveraging Machine Learning to Optimize Gas Lift Injection
- Neale Wilken ARC Resources; Dave Shook, Uptake
- Unlocking WellView: Using Natural Language Processing to Classify Well Workovers
- Amin Fardi, Kirk Duval, Cenovus
Thursday, June 10
Some of our near-term opportunities require a shift in mindset: sourcing more innovation from outside our companies. The status quo of developing proprietary R&D is being frequently outpaced by those working with open-source initiatives or with independent startups. We’ll share examples from our industry to help you learn how data and analytics projects can benefit from these new ways of working, as well as thoughts on how to effectively tap into these external opportunities.
- The Role of Startups and Accelerators to Accelerate Analytics Innovation
- Steve Liang, SensorUp
- Tapping Into Alberta's Innovation Ecosystem
- Nella Brodett, Alberta Machine Intelligence Institute
As the world continues to accelerate development of technology enabled by inexpensive data storage and tremendous computational power, how can we as an industry identify which technologies of the future will solve the problems of today? This session will explore how we can evolve our culture and our competencies to benefit from these disruptive technologies, better enabling us to compete globally while meeting ESG targets and driving operational efficienies.
Friday, June 11
Data science and machine learning are growing fields that have applications in any type of industry and has shown to improve the profit of companies that implement a data science group in them. Recently, companies from the Oil&Gas industry are starting to get on board of this new tendency and are creating and implementing new technologies with the help of machine learning algorithms. Demand for data scientists is increasing every year as new methods are required on each industry. This course focuses on the data preparation and machine learning application on different case of study examples...