I have been experimenting with text analytics on 500 public Mars Geology documents. Following on from my last post spatialising data on a map, I have also explored multivariate heat map clustering. Recognition to Metsalu and Vilo (2015) for clustering visualisations originally developed for Nucleic Acid research.
Mars Geology by text analytics
#mars #nasa #geology #naturallanguageprocessing
Natural Language Processing: Detecting evidence in text reports and comparing with existing structured data
Over 5,000 USGS reports were analysed using Natural Language Processing (NLP) and Machine Learning to detect potential environments for Copper. Over 1.5Million detections were made. The results were coarsely spatialised by country and shown on the map above. The larger the pie-chart the greater the tone of uncertainty / speculation. These data were displayed in... Continue Reading →
Google Searches Last 5 years: Critical Minerals , Oil and Gas Exploration , Green and Blue Hydrogen
Last 5 years Google Searches for Critical Minerals. #google #criticalminerals ..and for oil & gas exploration #petroleumexploration ..and Green and Blue Hydrogen #greenhydrogen #bluehydrogen
Language Comprehension Question and Answer models.
There are several Question & Answer OpenSource Language Comprehension models that can be applied to unstructured text. Even without tuning to a domain, they are capable of producing some quite remarkable answers buried in large amounts of text for simple factual questions. The image above is a simple example related to Carbon Capture, Utilisation and Storage... Continue Reading →
GeoClassifier® – A new way of automatically organising subsurface documentation
The GeoClassifer algorithm launched in December 2020 can automatically read the ‘body text’ of subsurface documentation (PDF, PPT, Word, Excel etc) and classify.... Full post here: http://www.infosciencetechnologies.com
OpportunityFinder® v4.2: State-of-the-art geo-tagging for subsurface, geoscience and Earth science documents
NEW: OpportunityFinder® v4.2 has options to detect 30% more geographical/geobody entities within the body text of documents. These can support spatial and map based search & discovery. Coverage includes from well/boreholes, leads, prospects & plays to fields, deposits, localities, tracts, blocks & licenses to mountains, foldbelts, seamounts and basins. Using state-of-the-art natural language processing and... Continue Reading →
Sentiment analysis of UK hydrology monthly reports (2013-2021)
Sentence based sentiment analysis was conducted for monthly hydrological summary reports for the UK, covering groundwater, river flows and rainfall over the past 9 years. The hypothesis was whether seasonal changes would be picked out using text based sentiment. Averaging smoothes out the 'edge cases' but nevertheless some consistent patterns may emerge. Further work ongoing.... Continue Reading →
Automatically detecting geo-resource evidence in reports.
Looking to extract evidence for petroleum systems, metals & minerals, heat flow, fluid flow or aquifers & seals in reports or semi-structured databases? Or chronostratigraphy, lithostratigraphy, tectonics, depositional environment and lithology? The patented algorithms from Infoscience Technologies may give your organisation a fast start.. contact@infosciencetechnologies.com
Need help searching for petroleum system elements for exploration?
Our algorithms combine over 75,000 different ways potential hydrocarbon occurrence, source rock, maturation, migration, reservoir, trap and seal clues may be mentioned in documents, reports and logs. Using traditional keyword search, explorers may miss up to 40% - 60% [1] of the relevant geoscience evidence buried in report collections. Based on years of research, our... Continue Reading →