• Products
    • Products Overview
    • Oil and Gas Data
    • Oil and Gas Software
  • ML in Oil & Gas Blog
  • Resources
  • News & Events
    • Company News
    • Conference Presentations
  • About
    • About Novi Labs
    • Careers
  • Contact
Novi Labs
  • Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
get started on your future of well planning with Novi

Novi Labs

  • Products
    • Products Overview
    • Oil and Gas Data
    • Oil and Gas Software
  • ML in Oil & Gas Blog
  • Resources
  • News & Events
    • Company News
    • Conference Presentations
  • About
    • About Novi Labs
    • Careers
  • Contact

Machine learning in oil & gas blog

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 typically publish a post every two to three weeks sharing our machine learning models and use cases for clients. Topics range from ML basics to deal evaluations and groundbreaking completions studies. We also feature thought pieces that cover bias, uncertainty and decision making, like this post on the risks of developing big discoveries.

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.

Is it worth It? Quantifying the value of collecting and interpreting subsurface data. [URTeC 2022 Novi Paper Summary]

April 12, 2022

Rejoice geologists, geophysicists and petrophysicists!  We provide a novel approach to answer the question: Is it worth it for the industry to spend hundreds of millions of dollars each year to collect and interpret subsurface data?  In short, you bet!  

Filed Under: Machine Learning in Oil and Gas Blog

Overcoming barriers to data-driven workflows: introducing Novi Model Engine

March 2, 2022

Although shiny machine learning algorithms get most of the attention, data preparation takes the most work. Erroneous completions data must be fixed or removed. Messy formation names need to be cleaned up.

Filed Under: Machine Learning in Oil and Gas Blog

Novi Labs Announces the Release of Novi Model Engine

March 2, 2022

Novi Model Engine completes Novi’s energy-focused, machine-learning platform comprising Data Engine, Model Engine, and Forecast Engine. Novi’s software now provides an industry-first capability that allows operators and energy investors to leverage AI-driven digital workflows to make higher-quality investment decisions with a fully integrated data to decision workflow.

Filed Under: Machine Learning in Oil and Gas Blog, Company News

Public Data Models: Better Than Anyone Expected

February 17, 2022

We have all heard the saying “garbage in = garbage out” when it comes to creating any sort of statistical model. You may have even seen it here. In an ideal world, we would be able to create forecasting models with perfect data quality, representing the exact details of each well stimulation, and the exact […]

Filed Under: Machine Learning in Oil and Gas Blog

Founder Point of View :: Novi Acquisition of ShaleProfile

January 19, 2022

Jon Ludwig, Novi’s Founder and President, explains the thesis behind the acquisition of ShaleProfile, a leading provider of data and analytics to energy investors.

Filed Under: Machine Learning in Oil and Gas Blog, Company News

Upcoming Webinar :: Primexx’s Journey with Novi

October 4, 2021

In this open discussion, Michael Mast of Primexx will present a case study on his experience leveraging Novi’s Machine Learning technology to optimize development and execute strategic planning.

Michael and Novi’s Ted Cross will dive into:

How has Primexx implemented Machine Learning to optimize development planning?
How can accurate forecasts make a case for acreage quality?
How do Machine Learning workflows stack up against traditional methods?
What are the most important criteria for gaining confidence in your forecasts?

Filed Under: Machine Learning in Oil and Gas Blog, Company News

Novi to Speak at SPE – Permian Cube Development Panel!

August 9, 2021

We are honored to participate in the inaugural event of the SPE Permian Basin Reservoir Study Group — a panel on cube developments! We’ve been working hard on the cube development problem, and are looking forward to discussing it with these great panelists! Details: Wednesday, August 18, 2021 11:30 AM – 1:00 PM CDT Bush […]

Filed Under: Machine Learning in Oil and Gas Blog, Company News

THREE Novi papers recognized as Best of URTeC 2020!

August 2, 2021

We are excited to announce that three of our papers have been recognized as Best of URTeC 2020! At Novi, our team pushes the industry forward every day with advances in machine learning for oil and gas developments, and we are thrilled to see the hard work of the team recognized. Click through for the […]

Filed Under: Machine Learning in Oil and Gas Blog, Company News, Conference Presentations

Novi Attends URTeC 2021! Click for presentation schedule & booth details.

July 7, 2021

Novi is excited to be exhibiting at BOOTH 4601 and presenting five papers! Click through for the full schedule.

Filed Under: Digital Oilfield Technology, Machine Learning in Oil and Gas Blog, Company News, Conference Presentations

Oil and Gas Cube Development: How Dense is Too Dense??

May 28, 2021

Of all the levers available to an operator, perhaps none has a greater impact on unit economics than wells per section. Over the past few years, operators have stopped thinking of developments on the well-level and have shifted to “cube-level” or unit-level economics. However, deciding on the right unit design for cube development in oil […]

Filed Under: Machine Learning in Oil and Gas Blog

The SECOND ANNUAL Novi Labs Machine Learning in Oil & Gas Blog Student Contest

May 26, 2021

Attention students! Novi’s annual Student Blog contest has returned! This is a great chance to differentiate yourself and hone those writing & visualization skills. We will pay $500 each to any posts selected for publication to our blog! Check out last year’s winner here! DETAILS: We welcome any submissions as long as they fit under […]

Filed Under: Machine Learning in Oil and Gas Blog

Energy Tech Talk with Novi: Capitalizing on Data Automation

May 11, 2021

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 […]

Filed Under: Automated Well Planning, Predictive Analytics, Big Data Management, Machine Learning in Oil and Gas Blog Tagged With: Data Engine, data automation, data quality

Energy Tech Talk with Novi: PDP & PUD Forecast Uncertainty

April 23, 2021

Technical Advisor Ted Cross and Data Scientist Kris Darnell talk about why PDP and PUD forecast uncertainty quantification is so critical to making smart business decisions and how easy it is to get it wrong. Listen in as they take a deep dive into our machine learning technology and the data science behind it. For […]

Filed Under: Automated Well Planning, Predictive Analytics, Machine Learning in Oil and Gas Blog Tagged With: PDP, forecast

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

April 1, 2021

Machine learning models that forecast production for PDP or PUD oil and gas wells may increase accuracy, save engineering time, or replace deterministic models in comparison to in-house methods. These are good reasons to switch to machine learning models and, not coincidentally, these are often the focal points of machine learning sales pitches. However, when […]

Filed Under: Automated Well Planning, Predictive Analytics, Machine Learning in Oil and Gas Blog Tagged With: PDP, forecast

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

March 15, 2021

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 — they were that accurate. Machine learning for PDP oil and gas forecasting was the next frontier. What we had discovered is that existing methods were leaving a whole lot of […]

Filed Under: Automated Well Planning, Predictive Analytics, Machine Learning in Oil and Gas Blog Tagged With: PDP, forecast

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

December 16, 2020

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.

Filed Under: Artificial Intelligence in Oil and Gas, Machine Learning in Oil and Gas Blog

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

December 14, 2020

Use of predictive analytics to understand well performance and production drivers across the bakken-three forks play

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.

Filed Under: Predictive Analytics, Well Designs, Artificial Intelligence in Oil and Gas, Machine Learning in Oil and Gas Blog

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

November 17, 2020

are you the house or the player when it comes to shale well investing?

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.

Filed Under: Automated Well Planning, Drilling Optimization, Well Designs, Digital Oilfield Technology, Artificial Intelligence in Oil and Gas, Machine Learning in Oil and Gas Blog

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

August 26, 2020

Machine learning in oil and gas model showing SHAP values (colored bars), and baseline production expectation (gray) for Vista Pad 3, including the record setting wells (MDM-2061 and MDM-2063).

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.

Filed Under: Well Completions, Well Designs, Machine Learning in Oil and Gas Blog

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

August 7, 2020

WHY CARE ABOUT PXRF DATA? Thanks to relatively short scanning times and low operating cost, portable X-ray Fluorescence (pXRF) scanning of geologic core samples has become a burgeoning big data in oil and gas industry, with the technique capable of generating high resolution datasets containing comprehensive major and trace element abundances present in the rock.

We will be using Scikit-learn, an open source machine learning library that supports supervised and unsupervised learning towards a variety of applications. Here we will be utilizing principal component analysis and k-means clustering algorithms to manipulate and segment the big data before visualization.

The process outlined in this blog post develops labeled datasets that can be tied to the core, ahead of the implementation of a neural network. Read the full post here.

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog

Novi geoSHAP – estimating rock quality using SHAP values in machine learning models: URTeC 2020 Novi Paper Summary

July 14, 2020

geoSHAP: estimating rock quality using SHAP values in machine learning models

Can a machine learning model learn where the play sweet spots are, just from raw well logs? The answer is YES. Using logs (or any input geo variables), plus a principal components analysis, gives the model everything it needs to learn what drives production.

This is the subject of our most requested URTeC 2020 paper — geoSHAP: A Novel Method of Deriving Rock Quality Index from Machine Learning Models and Principal Components Analysis. Click through to learn more!

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog, Conference Presentations

Water, water everywhere: oil well water analysis with machine learning models to improve produced water forecasts in the Williston Basin: URTeC 2020 Novi Paper Summary

July 6, 2020

Oil well water production with average 90-day cum for Bakken and Three Forks

How often does an engineer dash off a simple produced water analysis, doing something like applying a flat WOR to their oil prediction? It’s easy to ignore water, but unexpectedly high production, leading to more produced water, can damage well economics. In the worst cases, it can force shut-in if disposal capacity is full.

Fortunately, advanced machine learning methods developed for oil can be applied to water. These technique help disentangle the complex interactions of completions, geology, and spacing.

This is the subject of our URTeC 2020 (and JPT-featured) paper. Read the summary here.

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog, Conference Presentations

The Changing Impact of Oil Well Design Completions Through Time: URTeC 2020 Novi Paper Summary

June 26, 2020

Average SHAP Value to forecast oilfield completions

Using a single scaling factor instead of a time series can ruin your well economics. An upsized completion might increase your production 20%, but knowing whether that applies to peak rate or EUR can have a huge impact on your well economics.

Machine learning models can predict a time series of production. This means you can evaluate the impact of completions design over the life of a well. Read the URTeC paper summary here.

Filed Under: Predictive Analytics, Well Completions, Well Designs, Machine Learning in Oil and Gas Blog, Conference Presentations

Building Unbiased Benchmarks with Machine Learning Oil and Gas Modeling: URTeC 2020 Novi Paper Summary

June 15, 2020

Machine learning can help you build unbiased benchmarks for operator performance! Operators, financial services, and investors will all appreciate this one.

We take a look at EOG and MRO performance in The Bakken.

Filed Under: Predictive Analytics, Machine Learning in Oil and Gas Blog, Conference Presentations

Announcing the Novi Labs Machine Learning in Oil & Gas Blog Student Contest

June 10, 2020

We know that many current students have had their summer plans upended with internships canceled or delayed. To give those students a chance to still differentiate themselves, we are announcing the Novi Labs Machine Learning in Oil & Gas Blog Student Contest. We will pay $500 each to any posts selected for publication to our […]

Filed Under: Machine Learning in Oil and Gas Blog

how does a 3 billion barrel discovery turn into a $3 billion impairment in oil and gas plays?

May 15, 2020

Why do operators stay in oil and gas plays long after it’s clear that they are uneconomic?

There’s a big difference between finding Big Tuna and getting it in the boat. You must understand uncertainty and feedback loops to make good decisions. Data-driven models offer one potential solution.

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog

the power of analogy : using novi’s contributing oil well data to understand machine learning predictions

April 30, 2020

All Training Oil and Gas Well Production Data Tree

Whether exploring for oil offshore Brazil or scaling type curves in Lea County, engineers and geologists rely upon the power of analogy to estimate the productivity of a given area or engineering design choice. Tree-based machine learning models can quantify similarity based on what matters: how it contributes to production.

Filed Under: Predictive Analytics, Digital Oilfield Technology, Big Data Management, Machine Learning in Oil and Gas Blog

trust me, I’m an objective engineer: uncovering the inherent bias in oil and gas forecasts

April 29, 2020

SHAP values by formation for mapping oilfield forecasts

Capital allocation decisions made by engineers that work at E&P companies are completely rational and based on unbiased P50 oil and gas forecasts.

If this is your belief, and it must be a belief, don’t read this post!!

Filed Under: Automated Well Planning, Predictive Analytics, Machine Learning in Oil and Gas Blog

first large bankruptcy filing begs the question :: is there hidden value in Whiting’s un-drilled acreage worth bidding on?

April 14, 2020

When Whiting declared bankruptcy, we put their acreage under the machine learning microscope.

What do production expectations and breakevens look like across their Williston portfolio? Read the answers in this post.

Filed Under: Drilling Optimization, Machine Learning in Oil and Gas Blog

playing enough short game to get to the long game :: revisiting the Parsley-Jagged deal at $30 strip

April 8, 2020

When Parsley Energy announced their acquisition of Jagged Peak in October 2019, WTI was trading at $55/bbl. Though the all-stock nature of the transaction protected their downside, Parsley still faced the question: “how can we economically develop the Jagged Peak acreage?”

In this post, we study completions and spacing options to maximize acreage value. Click through to read our analysis.

Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog

the confidence game: optimizing completions for XEC DUC wells in the Delaware using model confidence as a proxy for risk

March 30, 2020

Optimizing DUC inventory is something that many operators unfortunately have to wrestle with after pauses in completions activity.

Machine learning models can help you design the right completions for each well — and Lead-in sentence then understand the risk and uncertainty to prioritize your capital allocation.

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

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

five ways smart digital oilfield technology & applications might save the Shale industry

March 18, 2020

Bloomberg break-even costs curve can be improved by digital oilfield technologies.

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.

Filed Under: Digital Oilfield Technology, Machine Learning in Oil and Gas Blog

less than 10% of remaining Bakken inventory is in the play core

March 16, 2020

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 machine learning models, we estimate that <10% of the remaining inventory is Tier 1, with the real number perhaps <5% due to surface constraints. With lower-tier locations predicted to produce […]

Filed Under: Machine Learning in Oil and Gas Blog Tagged With: williston, fringe vs. core, geoSHAP

oil and gas well spacing and completions: untangling complex interactions with machine learning

February 20, 2020

How much of the oil & gas industry’s recent underperformance comes from misapplication of large completions designs with tight spacing configurations?

Filed Under: Well Completions, Machine Learning in Oil and Gas Blog

Primary Sidebar

NOVI ML IN OIL & GAS BLOG TOPICS

  • Automated Well Planning
  • Predictive Analytics
  • Well Completions
  • Drilling Optimization
  • Well Designs
  • Digital Oilfield Technology
  • Big Data Management
  • Artificial Intelligence in Oil and Gas
  • Conference Presentations

Recent posts

Is it worth It? Quantifying the value of collecting and interpreting subsurface data. [URTeC 2022 Novi Paper Summary]

April 12, 2022

Overcoming barriers to data-driven workflows: introducing Novi Model Engine

March 2, 2022

Novi Labs Announces the Release of Novi Model Engine

March 2, 2022

Public Data Models: Better Than Anyone Expected

February 17, 2022

Founder Point of View :: Novi Acquisition of ShaleProfile

January 19, 2022

Upcoming Webinar :: Primexx’s Journey with Novi

October 4, 2021

Novi to Speak at SPE – Permian Cube Development Panel!

August 9, 2021

Reach out

If you would like more information, please reach out using the form below.
  • This field is for validation purposes and should be left unchanged.

Reach out

Novi’s AI-driven well planning software is the only product of its kind that revolutionizes the way oil & gas investments are made. Drop us a line to request more information by clicking the button below!

Contact us today

Footer

Connect

  • LinkedIn
  • YouTube

oil and gas analysis by novi

Contact

1905 Aldrich Street, Suite 220
Austin, Texas 78723

intro@novilabs.com
512.368.9042

  • Home
  • Products
  • Resources
  • About
  • ML in O&G Blog
  • Privacy Policy

Copyright © 2022 Novi Labs
All rights reserved.