Agenda

Coding has been a common cornerstone for data enthusiasts. This session will reveal approaches on how to start coding and persevere through debugging, examine common pitfalls in coding and showcase effective approaches in data manipulation without writing gazillion lines of code. Come and become a pro or remain a noob. YOUR CHOICE! 

Presentations:

1. SQL (Relational) vs NoSQL (Non-relational) Database

• Noha Salem,PwC

2. How to Start Coding

• Thomas Zhao, McDaniel

3. Core Principles and Concepts for Navigating Complex Data Science: From Non-Coding Engineer to "Unicorn"

• Scott McKean, Chevron

Case studies are stories about how people navigate real life challenges. In this session, presenters will share their experience with data analytics and machine learning applications which bridge the gap between theory and practice. Get ready to take a deep dive into advanced topics, engage, and learn together.

Presentations: 

1. Automated Detection of Wellhead Steam Release from Video Feed

• Michael Tenove, ConocoPhillips

2. Wells, Python, & Workflows. Using ORM to Interface with Data

• Scott Pinckston, Crescent Point Energy

3. Prediction and Explanations for Geothermal Machine Learning

• Roman Shor and Gias Uddin, University of Calgary

For those who are starting out in the sea of analytics and data science and wondering, ‘What’s the best tool for the job?’ and ‘What are some foundational skills in exploring data with R, Python, PowerBI, Spotfire and other tools?’. This session will explore matching the right tools for the right job, basic best practices and building sustainable data science projects that can be updated and maintained well into your data science journey. Descriptive tools (PBI, Tableau); predictive tools (governance, version control, how you use them).

Presentation:

1. Getting Data Back into Data Analytics

• Trudy Curtis, PPDM Association

2. Data Pipelines and Tools to Integrate with Power BI and Spotfire

• Steve Dolha and Ryan Mross, Cadeon

2. Sustainable Practices and Clean Code

• Chris Petr, CNOOC International

How is machine learning being leveraged today within the oil and gas sector? In this session learn from multiple real world machine learning use cases taking a deep dive into various aspects of the ML workflow with a focus on providing tools and techniques to be applied to your next ML project.

Presentations:

1. Evolution and Workflow of Electrical Demand Model and the First Regulator-Approved PEMS Model

• Brett Wiens, Cenovus Energy

2. Feature Selection and Optimization for Modeling Liquids Production in Western Canada

• Ian Vincelli and Trevor Rix, Enverus 

3. Valuing Our Data and Avoiding Scam Artists

• Tyler Schlosser, McDaniel

It’s not all coding in python and R, and it’s not all geology and engineering. Analytics has been a part of this industry since the early days and this session will introduce the audience to broad applications of analytics in our industry and how some of the traditional analytical methods may be evolving.

Presentations:

1. Marketing Analytics

• Slavko Uzelac, Shell

2. Evolution of Reserves and Evaluations

• Oluyemisi Jeje, Sproule

3. Pumpjack/Artificial Lift Analytics

• Kim St.Georges, Microsoft

Near real time analytics session shares the best practices of data analytics, and artificial intelligence, that are being developed/adopted by the companies in/out of oil and gas sector. In this session exciting projects using real-time/near-time analytics will be showcased for example using real-time data to predict screen out or emission quantification using image processing, etc.

Presentations:

1. Remote Operating Centre - Real-time Analytics

• Mike Mutrie and Michael Clark, PETRONAS Canada

2. Drilling Optimization Using Real-Time Analytics

• Ignacio Garda, Halliburton

3. Real-Time Setpoint Optimization at the Edge

• Vikas Jain, SLB

4. Extraction Optimization Advisor

• Rajan Patel, Suncor