Interesting paper published in Computers and Geosciences. “3D lithological mapping of borehole descriptions using word embeddings” Fuentes et al (2020). Applied to groundwater studies in New South Wales, Australia. https://www.sciencedirect.com/science/article/pii/S0098300419306533 Also an interesting paper published in the AGU. Dictionary‐Based Automated Information Extraction From Geological Documents Using a Deep Learning Algorithm - Qiu - 2020 -... Continue Reading →

OpportunityFinder Milestone: the geoscience algorithm is now trained on over 25,000 terms & phrases for identifying clues for source rock, maturation, migration, reservoir, hydrocarbon occurrence, trap and seal in unstructured text (reports, presentations and papers). This is used by its one-of-a-kind pattern based discovery method to assist the Geoscientist and surface possible leads, analogues, opportunities... Continue Reading →

I recently ran 1 million sentences from public domain geoscience literature articles & reports through the OpportunityFinder® algorithm. The aim was detecting hydrocarbon exploration play elements and interesting combinations using Natural Language Processing (NLP) and Machine Learning. This involved analysing over 2 Trillion possible permutations hidden within the text. Through iterative design, I arrived at... Continue Reading →

Delighted to be invited by Petrobras this week to give a presentation of OpportunityFinder at the SIMGEO 'Digital Transformation in the Geosciences' symposium. OpportunityFinder(R) is a Python based algorithm which surfaces non-obvious exploration opportunities hidden in unstructured text (reports, documents) and can be adapted to other geosciences based work tasks. http://www.infosciencetechnologies.com

I attended the 3 hour virtual summit on the Future of Geoscience hosted by the Geological Society of London today (10th June 2020). Over 1,000 people attended from as far afield as Indonesia, Pakistan, Canada and Milton Keynes! It was excellently led by Tom Backhouse and joined by a range of people representing different areas... Continue Reading →

Along with some colleagues I'm writing up a paper over the summer looking at the impact COVID-19 has had on Enterprise Search and Scholarly Search behaviour, with so many people working remotely. There are some fascinating patterns in the search engine usage logs. One pattern in particular was unexpected and significant. This could have theoretical... Continue Reading →

Spot where many of the lockdowns occurred due to COVID-19 and mass remote working started...

In 2015 we conducted an experiment to see how well people performed searching for geoscience information in an organization using search engines. In total 26 experienced staff from several countries in an exploration company participated using their own company information and subsurface search engine. To our knowledge, it was the first and remains the only,... Continue Reading →

Over 25 years ago Collins and Poras (1994) studied successful companies and noted their ability to often embrace what appear to be competing constructs. This may be akin to machine learning (statistical) and knowledge engineering (linguistics-taxonomies). On many occasions I've seen one 'camp' explain all the pitfalls of the other, without acknowledging the limitations of... Continue Reading →

Thirty years ago I started my MSc in Computing in Earth Sciences. Since then much of my time has been spent applying computing & data science to geoscience in industry. For the past ten years or so, my focus has turned to academia; further developing the information science to underpin Natural Language Processing (NLP), Taxonomy,... Continue Reading →