The IGI User Group 2025 meeting, held in June at Hallsannery, was one of our best-attended events to date, welcoming 15 participants from 10 different companies.
Managing Director & Data Scientist
He will be talking about the challenges of applying our new machine learning tools to geochemical data, motivated by work with DNO ASA on producing a holistic understanding the oils and source rocks of the North Sea.
Managing Director & Data Scientist
Equations are a key part of the IGI software family. Here we explain how they work...
Product Owner
Version 2.3 of p:IGI+ and Metis introduce a number of new features including enhanced support for auto-artefacts, uncertainty, graphs, maps and more ...
Managing Director & Data Scientist
Improved artefact management is a key update delivered in v2. 3. Auto-artefacts cover the majority of artefacts including graphs, palettes, maps, pages, rule sets, dynamic sample sets and statistics. In the new release, existing autographs have been reviewed and updated, and a range of new auto-artefact templates added.
Senior Geochemist/Basin Modeller
The second article in the “Art of Science” series, by Dan Cornford. This article extends the initial article which reviewed the notion of clustering and looks at some of the practical implications. IntroductionRecently we have added k-means clustering to p:IGI+, to supplement the data exploration capabilities of the software.
Managing Director & Data Scientist
A short note by Dan Cornford on the place of machine learning in the geosciences, part of the Art of Science series of technical notes. Please click here to read the full technical note:
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Managing Director & Data Scientist
An article in the “Art of Science” series, by Dan Cornford exploring and explaining the use of statistics, machine learning and more widely data science in the geosciences. IntroductionRecently we have added k-means clustering to p:IGI+, to supplement the data exploration capabilities of the software.
Managing Director & Data Scientist
In this article, which extends the piece in our newsletter, we explore what Principal Components Analysis (PCA) is, where it is useful, address some key points to be aware of in usage, and describe how to undertake PCA in p:IGI+.
Managing Director & Data Scientist
