IGI prides itself on innovating in the domain of geochemistry. We often publish updates and short notes on areas of interest, as well as notifications of events or major developments within IGI.
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05/01/22
The second article in the “Art of Science” series, by Dan Cornford. This article extends the initial article[/news/patterns-in-the-mind-part-1/] which reviewed the notion of clustering and looks at some of the practical implications.
Go to: Patterns in the mind - Part 207/12/21
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.
Go to: The extinction of machine learning?18/11/21
IGI (Marianne Nuzzo) contributed to a research article published this month in Geology...
Go to: Slow advection of deep-sourced methane-enriched fluids shown to be quantitatively significant over time along oceanic strike-slip faults14/10/21
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.
Go to: Patterns in the mind – Part 104/08/21
by Marianne Nuzzo and Mischa Gehlen
Go to: How the “Rayleigh fractionation effect” is used to model the source and maturity of hydrocarbon gases: principles and potential problems16/04/21
Kerogen is the semi-solid polymeric material that is insoluble in both water and organic solvents, and which forms the majority of the organic matter present in a petroleum source rock.
Go to: Biomarkers in kerogen by Paul Farrimond05/02/21
by Marianne Nuzzo and Mischa Gehlen
Go to: Forensic use of diagnostic biomarker ratios in environmental oil spill geochemistry04/11/20
Andrew Murray and Ken Peters recently presented an interesting paper on mixing of oils and gas condensates, and the use of Alternating Least Squares (ALS) and Hierarchical Cluster Analysis (HCA) for interpreting such mixtures.
Go to: Unmixing mixtures - a mathematical perspective on using peak concentrations versus ratios03/11/20
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+.
Go to: Further reading on Principal Components Analysis in p:IGI+07/07/20
By Marianne Nuzzo
Go to: Detection of micro-seepage of deep-sourced fluids by modelling geochemical and heat flow signals