Engineers and analysts spend 80% to 90% of their time cleaning up hybrid datasets for machine learning models and analytics. Listen in as Novi Technical Advisors Ted Cross and Kiran Sathaye talk about oil and gas industry challenges with an emphasis on managing data quality, cumbersome workflows and spacing calculation complexity.
Novi Data Engine addresses these challenges and more by shortening time to insights through automation and enabling scalability. As a result, our software empowers teams to invest their valuable time deriving accurate insights that matter.
The end game is all about maximizing the return on your data. As Kiran explains, “The way that a manager in an oil company should think about this is if you have data and are not getting the max value out of it, it is wasted. That is just as much of an economic waste as pumping profit into a well that you didn’t get any uplift from. It’s money going down the drain.”


Click here for more background on Novi Data Engine, and watch a short release video demonstrating the latest features here.
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[URTeC 2023] Revealing the Production Drivers for Refracs in the Williston Basin (ID 3864951)
[URTeC 2023] Understanding the Drivers of Parent-child Depletion: A Machine Learning Approach​ (ID 3862321)
[URTeC 2023] How Much Data is Needed to Create Accurate PDP Forecasts?​ (ID 3870872)
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