Oct 29, 2014 -- Exprodat, the oil and gas GIS services, software and training supplier, has released a new version of Data Assistant, the ArcGIS extension that allows oil and gas companies to transfer data between the ArcGIS platform and common exploration and production file formats such as Schlumberger Petrel, IHS KINGDOM, Landmark OpenWorks and SeisWorks, amongst others.
Data Assistant v221 has been extended and enhanced with a host of new features, all focused on speeding up and simplifying data integration.
In line with the release schedule of Esri, this latest version of Data Assistant now supports the soon-to-be released ArcGIS 10.3 for Desktop and includes translators for a wider range of data formats. So now Data Assistant users are able to benefit from using the powerful features of the latest spatial analysis software with more of their own data to increase the quality of their exploration and production decisions.
Developing this theme of improving the working day for exploration and production staff, Data Assistant is now able to automatically detect the format of input files, import multiple data files in one go and export data using ‘on-the-fly’ projection.
Exprodat’s technical director Chris Jepps explains more about how Data Assistant is used with E&P departments and how the new version will provide further benefits; “The main aim of Data Assistant at version 221 was to make it even easier to use - to enable geoscientists and spatial analysts to spend less time grappling with data and more time using it. We’ve also expanded the data footprint of the tool by introducing support for new OGP formats and building generic format data loaders, in order to make the application even more useful – and these are trends we expect to develop further in future releases.”
Exploration Analyst, Data Assistant and Unconventionals Analyst are a series of ArcGIS extensions developed, supplied and supported by Exprodat for use in the petroleum industry. Users of these tools are able to improve their decision making through better data integration and spatial analysis.