Nov 2, 2022
"I felt the industry needed a more advanced methods of determining outcomes before millions of dollars were spent..."
In this episode, I’m in conversation with Jon Ludwig who is the President and co-founder of Novi Labs, a data platform for the upstream oil and gas industry. Jon is a serial entrepreneur with a background in finance and oil and gas, who was struck by the challenge facing on-shore oil and gas producers when they allocate capital to well programs. Legacy ways of forecasting well performance and optimal well delivery, based on one or two wells at a time, simply don’t work when operators are aiming for 500 well manufacturing programs. Using new tools and methods to aggregate data and machine learning algorithms to crunch the numbers, NoviLabs helps improve capital allocation and economic performance of the industry.
"Secure energy independence is really important. It's fundamental. Everyone likes to know that when they flip the light switch, the lights are gonna go on. But for some of us that live in Texas, there is a period where the lights didn't go on for a whole week in 2021. We had no lights, no power, no water. And suddenly people knew what it was like to not have energy independence right or not have a reliable infrastructure."
Jon Ludwig is the President and co-founder of Novi Labs, a software company that develops a machine learning driven software platform that drives improvement in economic outcomes for upstream oil & gas companies and investors.
Prior to Novi, Mr. Ludwig was a Director at Hess Corporation where he founded the company’s data analytics program, which gave rise to a move of critical business systems to the AWS Cloud, and unlocking the concept of a next generation platform for upstream oil & gas predictive analytics.
Jon has also worked at Cap Gemini as a Principal leading the Enterprise Portal and Search practice, as a Partner for iPath Solutions in Houston, and as Founder and CEO of eLinear, a publicly traded software company based in Boulder CO.
"Our products act, and our data acts as an advisor that informs the design of the drilling program? Meaning, how far apart? How many wells? Do you stack horizontally? How do you stagger them? Or how do you complete the wells?"