Read through our posts covering real world applications of machine learning in oil & gas using AI-driven software and data tools. Learn from seasoned, experienced industry veterans as they go into technical topics related to machine learning, artificial intelligence, risk, and digital oilfield.
We welcome guest writers working in the oil and gas industry. They work with oil and gas machine learning models using AI software to solve complex problems and optimize capital. If you would like to contribute a post or have an idea for us, send us a note.
change of plans: how QEP could optimize returns in their Midland asset in a low-price environment
In this post, we analyze QEP’s Midland Basin inventory, studying the impact of a range of completions designs.
5 ways digital oilfield solutions might save the Shale industry
DIGITAL OILFIELD TECHNOLOGY OVERVIEW : Let’s face it, the last two to three weeks have been a complete train smash for shale operators and investors. We are price takers at the end of the day, so we as an industry are all trying to do what we always do – pick ourselves up by the bootstraps and find a way forward. I have some ideas utilizing digital oilfield applications that we can use as a foundation to stand on.
In this post, I’m going to discuss where things are at, Level set on what response vectors the shale industry has taken thus far and much more. Read the full report here.
less than 10% of remaining Bakken inventory is in the play core
With the current oil price downturn, many have started to wonder whether activity in the Bakken will ever return to its previous heights. Using our …
oil and gas well spacing and completions: untangling complex interactions with machine learning
How much of the oil & gas industry’s recent underperformance comes from misapplication of large completions designs with tight spacing configurations?