Searcher has announced the launch of its latest Searcher Technology Product, GeoClerk — an advanced geo-imagery search engine that utilizes machine learning to intelligently extract imagery and surrounding data from all types of documents and classify them into intuitive and geologically relevant categories.
Traditional search functionality queries documents by text and are unable to instinctively provide context to an image beyond words. GeoClerk, through its use of algorithmic learning, interacts with internal document libraries, public sources, and institutional subscriptions to identify, define and present images in categories which are relevant to the exploration industry and the work of geoscientists.
Inefficiencies overcome
Paul Larsen, Vice President of Sales & Commercial at Searcher, said, “Images, tables and maps are generally created by great minds that interpret complex theories and a large magnitude of data. For companies to have access to such information only to be restricted by the inability to quickly identify the file location or which publication it exists in is severely inefficient and generally leads to re-creation of work and duplication of effort.”
GeoClerk as a web-based interface that allows for user-defined filtering on queries and retrieves results in categories such as maps, geosections, seismic, structure maps, stratigraphy and well logs. Information which was previously hidden within and around images in documents and file libraries, is now readily accessible and searchable, bringing to light decades of historic and uncategorised documents.
GeoClerk is available as an annual subscription service.
