Total to develop AI solutions with Google Cloud

The agreement focuses on the development of AI programs that will make it possible to interpret subsurface images, notably from seismic studies (using Computer Vision technology) and automate the analysis of technical documents (using Natural Language Processing technology). These programs will allow Total’s geologists, geophysicists, reservoir and geoinformation engineers to explore and assess oil & gas fields faster and more effectively.

Under this partnership, Total geoscientists will work side-by-side with Google Cloud’s machine learning experts within the same project team based in Google Cloud’s Advanced Solutions Lab in California.

“Total is convinced that applying artificial intelligence in the oil and gas industry is a promising avenue to be explored for optimising our performance, particularly in subsurface data interpretation. We are excited to work with Google Cloud towards this goal. This builds on the strategy being developed at Total, where A.I. is already used, for example, in predictive maintenance at facilities,” said Marie-Noëlle Semeria, Senior Vice President, Group CTO at Total.

“We believe that the combination of Total’s geoscience expertise and Google’s artificial intelligence skills will ensure the project’s success. Our ambition is to give our geoscience engineers an AI personal assistant in the next few years that will free them up to focus on high value-added tasks.” said Kevin McLachlan, Senior Vice President Exploration for Exploration & Production at Total.

“We are thrilled to welcome Total in our Advanced Solutions Labs for the development of AI solutions,” said Paul-Henri Ferrand, President of Global Customer Operations Google Cloud. “We are keen to engage our best AI engineers to work with Total’s geosciences’ experts.”

AI applied to E&P at Total

• Total started applying artificial intelligence to characterise oil & gas fields using machine learning algorithms in the 1990s.
• In 2013, Total used machine learning algorithms to implement predictive maintenance for turbines, pumps and compressors at its industrial facilities, thus generating savings of several hundred million dollars.
• Today, Total teams are exploring multiple machine learning and deep learning applications such as production profile forecasting, automated analysis of satellite images or analysis of rock sample images.

Read the article online at: https://www.oilfieldtechnology.com/digital-oilfield/25042018/total-to-develop-ai-solutions-with-google-cloud/