TGS has entered a collaboration agreement with the analysis and machine learning company Earth Science Analytics to expand and promote innovation in data-driven geoscience.
This partnership has delivered insight through a range of derivative datasets for the TGS Utsira Ocean Bottom Node (OBN) survey, created through artificial intelligence (AI) analysis, the company reports.
The project is said to be the first example of AI geological interpretation on a large-scale, densely sampled OBN exploration dataset covering over 1,500 square kilometers.
The objective was to deliver a new suite of derivative seismic products to provide enhanced exploration insights through AI, especially in areas where infrastructure lead exploration (ILX) is drawing increased focus from the E&P industry.
“The collaboration with Earth Science Analytics is an opportunity for TGS to maximize extraction of the subsurface data insights within our energy data library with integrated, AI-powered workflows. Application of these workflows on our Utsira OBN dataset has already produced startling results, and we look forward to future successes” , said Will Ashby , EVP of Eastern Hemisphere at TGS.
TGS will install Earth Science Analytics’ EarthNet software into its cloud environment to create high-value derivates from the library of subsurface data.
The properties produced from seismic and well data analysis include porosity, lithology, and water saturation as well as seismic interpretations of faults and geobodies.
These outputs will be available for purchasing and accessing in a data room environment as a means for operators to maximize their potential findings and profits, minimize risk and support the best possible decision making.
“We are delighted to announce this collaboration with TGS and look forward to utilizing their extensive data library to provide a wealth of knowledge to our clients “, said Eirik Larsen , customer success officer at Earth Science Analytics.
“This is the beginning of an exciting partnership which will continue to drive forward innovation, boost insights and cement data-driven thinking in the sector”.