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QEP

DUC, DUC, GOOSE: In a sub-$30 oil environment how can NBL maximize returns with less CAPEX spend in their Delaware asset?

March 25, 2020

In this post, we analyze Noble’s Delaware DUC inventory during the great coronavirus shut-in. How can smart operators optimize their activity to survive low prices?

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog Tagged With: QEP, Midland, Permian, Prediction Engine, Masters Series

change of plans: how QEP could optimize returns in their Midland asset in a low-price environment

March 19, 2020

In this post, we analyze QEP’s Midland Basin inventory, studying the impact of a range of completions designs.

Filed Under: Well Completions, Machine Learning in Oil and Gas Blog Tagged With: QEP, Midland, Permian, Prediction Engine, Masters Series

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Recent posts

PUD and PDP Forecast Uncertainty: Why You Need it and How Novi Delivers

April 1, 2021

Ahead of the Curve: Introducing Novi PDP Oil & Gas Forecasting

March 15, 2021

What can chess teach us about artificial intelligence in oil and gas?

December 16, 2020

Machine Learning Regional Profiles for Geologic Insights: Mapping Unconventional Production Drivers in the Williston Basin

December 14, 2020

Investing in Shale Oil and Gas Wells: Are you the House or the Player?

November 17, 2020

Analyzing Vista’s Record-Setting Vaca Muerta Wells with Oil and Gas Machine Learning Models

August 26, 2020

Making sense of it all: extracting actionable core-data from pXRF using PCA and K-means cluster analysis

August 7, 2020

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