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.
Machine learning models that forecast production for Proved Developed Producing (PDP) or Proved Undeveloped (PUD) oil and gas reserves may increase accuracy, save engineering time, …
It all started as an accident. We passed early time production to a “pre-drill” Novi model. When we saw the results, we were stunned — …
If, like me, you haven’t seriously played chess since you were young, you may find the advancements in chess artificial intelligence (or chess “engines”) incredible. But can chess teach us about the future of artificial intelligence in oil and gas?
Chess has long been a focus of artificial intelligence research. The game offers both clear rules (to easily measure success) and sufficient complexity (with at least 10^120 possible moves, no computer will ever be able to “solve” the game, unlike checkers). We certainly have complexity in the oilfield – but we also have the ability to measure success in the form of barrels produced, feet of pay encountered, or time to process a seismic volume.
In this post, we’ll walk through the latest AI in oil and gas market developments in chess and how they might impact the oilfield. Read the full post here.
Machine Learning Regional Profiles for Geologic Insights: Mapping Unconventional Production Drivers in the Williston Basin
What drives unconventional oil production? Of course completions, parent-child, and well spacing all play a huge role — but it all starts with the rocks.
We walk through a powerful new way of visualizing machine learning insights — regional profiles.
Are you the House or the Player?
Industry execGarth Stotts continues his series on bias, probability, and risk in the Shale patch with his latest message: successful investments in shale require an understanding of the REAL probabilities of your opportunities, from inputs all the way to cashflow.
Only then will you be in control — and be able to win repeatedly.
After the Great Coronavirus Shut-In, Vista Oil & Gas turned back on their new Vaca Muerta pad. A pleasant surprise greeted them. Their oil and gas machine learning model showed the highest production the play had ever seen. Both the MDM-2063 and MDM-2061 wells produced over 2,000 bbl/d on average for the month, with peak daily rates breaching 3,000 boe/d.
Why did these wells produce so much? Was it a novel completion design, a geologic hot spot, or a heavy tailwind of flush production? Lets explore this oil and gas machine learning use case. We will put these wells under the microscope with our Vaca Muerta public-data model.