Machine learning systems open up access to large volumes of valuable information lying dormant in unstructured documents

We discuss a feasibility study to access the 11,500 well headers and 450,000 documents from the United Kingdom Continental Shelf (UKCS) that were released by Common Data Access Limited. A cost-effective solution based on emerging machine learning technology “taught” and guided by data-management experts supports the reliable indexing and cataloging of these forms of data, paving the way for much more reliable E&P business decisions in the future.