Digital Transformation
Discover how AI and machine learning are transforming oil and gas field development by reducing subsurface uncertainty, optimizing development decisions, and maximizing long-term reservoir value from concept selection through production.
As upstream operators move beyond isolated experiments, the hardest part of the AI journey is not building a model, it is making it stick.
How 7 decades of AI research, including the emergence of agentic AI, are reshaping oil, gas, renewables, and the grid.
-
Statoil's Acting head of Digital Centre of Excellence shares the company's digital road map. -
The data science, machine learning, and artificial intelligence fields do have a great deal of overlap, but they are not interchangeable.
-
BHGE shared its plans for the integration of its services, products, and digital platforms for upstream to downstream applications.
-
R&D may be the key to the survival of companies as the new economics of the industry take hold.
-
One tech company is using a unique approach to building custom apps for the oil and gas business.
-
MIT News Office, 7 September. IBM and Massachusetts Institute of Technology (MIT) recently announced that IBM plans to make a 10-year, $240 million investment to create the MIT-IBM Artificial Intelligence (AI) Lab in partnership with MIT.
-
No longer considered a buzz phrase, cloud computing has made converts of the largest oil companies, and now the smaller ones are next.
-
The BP Statistical Review of World Energy is an institution in the energy world. Who's behind assembling and managing the mountain of data that goes into it?
-
A quick look at the term "Fourth Industrial Revolution" and links to related articles.
-
Data-driven reservoir modeling is an alternative or a complement to numerical simulation and uses machine learning and data mining to develop full-field reservoir models.
