OpportunityFinder® V4.4 Automatically create graphs from unstructured text – Turtle output.

NEW OpportunityFinder V4.4: Create Turtle output automatically from unstructured text. Creating a graph of subsurface & wells concepts automatically from unstructured data using Natural Language Processing (NLP).

The technique of creating a graph network of entities and concepts automatically from text into a Knowledge Graph is not new. However, OpportunityFinder(R) uses a unique patented approach to rank what might be the least obvious, less well known and therefore potentially the ‘most interesting’. 

This supports geoscientists and engineers in the geo-resource sector including metals & mining, oil and gas, renewables and underground storage.

Explore relationships between concepts, discover new connections, derive useful insights. 


#subsurface

#knowledgegraph

#nlp

#digitaltransformation


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Infoscience Technologies and Aramco Collaboration

We are pleased to be collaborating with Aramco and keen to see it put Infoscience’s OpportunityFinder® Natural Language Processing (NLP) algorithm to work. This aims to help geoscientists and engineers derive meaningful insights from unstructured data to speed up workflows and reduce risks.

About Infoscience Technologies Ltd
Infoscience is the market leader for Artificial Intelligence (AI) algorithms exploiting unstructured data in the geo-resource industry. Sectors include Energy, Renewables, Carbon Capture and Storage (CCS), Mining and Oil & Gas. These patented algorithms can unlock patterns and trends in digital records to derive unique business insights. Customers include some of the world’s largest companies.

S&P Global Commodity Insights sign enterprise software license for Infoscience AI software

We are delighted to confirm that Infoscience Technologies is partnering with S&P Global Commodity Insights to discover new insights in their extensive archive of unstructured data using our Natural Language Processing (NLP) algorithms.

The industry has always faced the challenge of deriving new valuable information from the growing archives of data – and something that S&P Global Commodity Insights have been gathering for decades.

“We are pleased S&P Global Commodity Insights has chosen to partner with Infoscience, using our algorithms to detect subsurface and commercial insights in their reports, documents and presentations. This provides further evidence of our market leading position in the provision of subsurface text analytics software. These patented AI algorithms intelligently machine read large volumes of unstructured data supporting the energy transition, mining, oil & gas and renewable sectors” says Dr Paul Cleverley, Director Infoscience Technologies.

S&P Global Commodity Insights
S&P Global Commodity Insights is the leading independent provider of information and benchmark prices for the commodities and energy markets. These include Oil, LNG, Natural Gas, Electric Power, Shipping, Petrochemicals, Metals, Coal, Agriculture and the Energy Transition. S&P Global Commodity Insights is a division of S&P Global (NYSE:SPGI), the world’s foremost provider of ratings, benchmarks and analytics in the global capital and commodity markets.

About Infoscience Technologies Ltd
Infoscience is a UK tech start-up pioneering Artificial Intelligence (AI) algorithms for the geo-resource sector such as mining, oil & gas and renewables. These unique patented algorithms detect hidden opportunities from subsurface, geoscience and commercial clues in unstructured text. Customers include some of the world’s largest companies based in North America, Europe, Asia and the Middle East.
#energytransition #artificalintelligence #bigdata 

Anglo American sign global license for Infoscience Technologies’ Natural Language Processing (NLP) Algorithms

We are pleased to announce that Anglo American, one of the worlds largest mining companies, has signed a global software license agreement to deploy Infoscience Technologies’ Natural Language Processing (NLP) algorithms.

Supporting its FutureSmart Mining™ Digitalisation initiative in Discovery (Exploration), Anglo American will apply these unique disruptive algorithms to its vast internal collection of documents. These will assist in the detection of new geological mineral deposits.

Dr Paul Cleverley, Infoscience Technologies Founder and Director commented, “Finding new deposits of critical minerals is essential for the transition to a lower carbon world. This agreement confirms Infoscience is a world leader in exploiting unstructured data in the subsurface and geo-resource sector”.

About Anglo American

Anglo American is a global mining company with a commodity portfolio that includes platinum group metals, diamonds, copper, iron ore, polyhalite, nickel, manganese and metallurgical coal for steel making. Anglo American employs over 100,000 people world-wide in 15 countries with annual revenues in excess of $40 Billion.


About Infoscience Technologies Ltd
Infoscience is a UK tech start-up founded in 2018, pioneering Artificial Intelligence (AI) algorithms for the geo-resource sector (oil & gas, mining and renewables). These patented algorithms detect hidden opportunities from geoscience and commercial clues in unstructured text. Customers include some of the worlds largest companies.

#miningindustry #geology #artificialintelligence

Disruptive algorithms for geo-resources – oil and gas, metals and mining unstructured text

Unlock the value in your oil & gas, mining, subsurface and geoscience documents. Disrupt existing business workflows. Automatically classify, extract data and names, find problems and opportunities. Assisting the subsurface professional and Geoscientist.

Save time searching for information, reduce the risk of missing key information and increase the chances of ideation & discovering new knowledge.

Patented state-of-the-art Python algorithms using the industry’s largest subsurface clue taxonomy/lexicons:

OpportunityFinder®

GeoClassifier®

From the pioneer in subsurface & geoscience unstructured text analytics.

OpportunityFinder® Customer survey

A recent survey was undertaken of a large organisation that has been using the Natural Language Processing / Machine Learning Python algorithm OpportunityFinder for the past 12 months.

They have been applying the algorithm to millions of documents to extract knowledge and ideas.

Compared to their existing traditional search engines they estimated:

1. The algorithm has reduced the time they spend searching for technical information by over 50%.

2. The algorithm has increased the chance they will discover new knowledge they would not have found otherwise (using traditional search engines) by 75%.

contact@infosciencetechnologies.com

File system migration to a document management system, support for acquisitions and mergers: GeoClassifier® – A new way of automatically organising geoscience, subsurface and wells documentation

The GeoClassifer(R) Python algorithm launched back in December 2020 (for petroleum, mining and renewables) can automatically read the ‘body text’ of geoscience, subsurface & wells documentation (PDF, PPT, Word, Excel etc) and:

  • Classify by document type
  • Classify by document category
  • Classify by chronostratigraphy
  • Classify by Lithostratigraphy
  • Classify by well / borehole name
  • Classify by prospect / lead name
  • Classify by survey name
  • Classify by deposit / orebody name
  • Classify by reservoir / aquifer name
  • Classify by field name
  • Classify by block / license name
  • Classify by play name
  • Classify by basin / geobody name
  • Classify by area /region name
  • Classify by country and region
  • Categorise by discipline/topics
  • Extract dates, people’s names & company names (ootb models)
  • Classify to machine learnt topics (custom geoscience model)
  • Also extract all of the names above that occur in the document if required
  • Extract drilling & operation problems
  • Many more features..

The resultant tags can be used to help organise records & document management and improve search & discovery of geoscience, subsurface and wells documents.

The GeoClassifier algorithm achieves this in a unique and novel way using several techniques.

– Knowledge Engineering (a taxonomy with thousands of clues for document types and categories)

– Machine Learning (250,000 labelled topic examples in an ensemble model), custom SpaCy NER models.

– Natural Language Processing (NLP) state-of-the-art geoscience name extraction

There are many limitations and problems when taking a taxonomy or thesaurus built for manual tagging of documents – then trying to apply that automatically to text. Unlike traditional methods (and taxonomies), GeoClassifier(R) was built from the ‘get-go’ for automated not manual document tagging – supporting digital transformation.

The Python algorithm can be applied immediately to diverse documentation, from any geographical location without using prior lists of names. Lists of names (e.g. well names) can be added to improve detection.

The algorithm can run stand alone against files on a filesystem and/or a company can take parts of it and embed in their existing tooling that may be more integrated with SharePoint / EDMS and Search systems.

The algorithm also uses an automatic document scoring system based on a number of criteria to identify those documents that will have tendencies to be ‘most important’ from a search and document & records retention point of view. This can aid file system migration projects, as well as acquisition, divestment and mergers.

More: contact@infosciencetechnologies.com

Patented next generation algorithms: The GeoClassifier(R) algorithm disrupts traditional document classification and extraction whilst OpportunityFinder(R) disrupts traditional business ideation processes, targeting associative extraction of petroleum, mining and renewables concepts and opportunities.