Even amongst the hustle and bustle of New York City, Geological marvels can be found. I could not resist taking a photo of these 12 feet high boulders while visiting this week. Central Park is peppered with huge boulders that look precariously perched on top of the ancient glistening bedrock. These are rounded glacial 'erratics'... Continue Reading →
Transforming Text Extraction in Petroleum Geoscience through Machine Learning: 94.52% Accuracy
One of the key tasks in Natural Language Processing (NLP) for the Petroleum Geoscientist is detecting entities in text, such as 'source rock'. The challenge is that just using the term 'source rock' and it's plural form 'source rocks', would miss 22% (recall) of all occurrences (false negatives) for 'source' in its word sense of... Continue Reading →
Machine Learning in Oil & Gas Exploration: Clustering Annotations
I've clustered the labels I annotated recently for 22,528 sentences (extracted from randomly sampled public domain petroleum exploration reports). There are 73 labels, I've shown a subset in the poster above. The labels represent 96,197 label relations (arc edges). The hierarchical cluster heatmap (Metsalu and Vilo 2015) in the poster uses Pearson Correlation (rather than... Continue Reading →