Automation is a key component to reducing the carbon footprint of operations and increasing drilling efficiency. Using A.I.-driven power management systems optimizes power usage while minimizing fuel consumption and carbon emissions.
Vision AI solutions for the upstream industry combine the latest AI, 5G, and Edge technologies for rapid visual data curation, proactive remote monitoring, continuous tracking, and automated alerting for solutions scaled across E&P sites and facilities.
May 11, 2023
The state-of-the-art subsea platform, an unmanned underwater vehicle ("UUV") with advanced artificial intelligence, sensing capabilities, and more can perform a growing number of jobs without hazarding human divers.
May 04, 2023
In a session titled “Artificial intelligence, real-time monitoring, automation and big data,” Shell’s Gulf of Mexico Safety Manager, Neisha Kydd, and Oxy’s Director of Enterprise Architecture & Emerging Technologies, Mansoor Nazar, discussed the ways their companies utilize artificial intelligence, automation and robotics in safety spaces, the limitations of these technologies, and the future of AI in their respective companies and the offshore industry as a whole.
April 14, 2023
Following commissioning, Nauticus expects to send the initial Aquanaut MK2 units to the North Sea and the Gulf of Mexico in the coming months to support customer initiatives in those regions.
April 05, 2023
The deployment provides scalability, flexibility, integration, and third-party collaboration and accelerates the adoption of machine learning and artificial intelligence across the drilling and wells organization.
Drilling technology: New ML-based drilling system recommender app demonstrates AI’s inherent value to well construction
As ML applications become easier to access and use, they are setting the stage for rapid scaling across the E&P industry to assist the human decision-making process. A new ML-based drilling system recommender illustrates how this scaling is improving drilling performance and reducing energy extraction costs.
February 24, 2023
The Envana™ digital emissions management solution provides a smarter and more accurate picture of emissions, which gives companies actionable information to manage and reduce their total carbon footprint.
December 23, 2022
By forging this new relationship with DataRobot, Weatherford will accelerate the development of machine learning and AI-enabled offerings within its digital solutions portfolio to deliver disruptive and innovative technologies to the oil and gas industry.
November 23, 2022
Bumi Armada, international offshore energy facilities and services provider, has partnered with OPEX (an ERM Group Company) to drive down carbon emissions on its Armada Kraken FPSO facility, which serves the EnQuest-operated Kraken Field located in the northern North Sea.
A New Era for Managing Enclosed Spaces - Powered by IIoT and Connected Worker Technology
September 12, 2022
Geolog and Petro.ai partner to deliver Data Science products and services to the global energy industry
September 06, 2022
Geolog International BV and Petro.ai have today announced a new strategic partnership to deliver Machine Learning and AI-based data science and predictive products and services to the global Energy Industry.
SOL-X unlocks valuable data and leading indicators through IIoT to drive operational decision-making
September 06, 2022
SOL-X's solution, SAFEVUE.ai, addresses industrial safety through smart wearables and AI. It enables efficient and compliant Control Of Work and raises worker situational awareness and improves their well-being.
May 24, 2022
Seismicity reviews are conducted by the Underground Injection Control Department for injection/disposal well permits in areas susceptible to earthquakes and in certain geologic zones.
A domain-centric approach when applying AI technologies is being used to solve issues in challenging wells.
April 29, 2022
Schlumberger announced it has expanded its global INNOVATION FACTORI network with the inauguration of a new center in Oslo, Norway.
An integrated platform, incorporating data from multiple systems that are accessible to a real-time operations center and field personnel, produces a comprehensive model of a company’s ecosystem. The innovative combination results in safer, more reliable operations with less downtime.
How to Achieve Enterprise-Scale Innovation in Energy: A real-world study on the impact of digitalization
April 28, 2022
Rapid advances towards achieving our decarbonization responsibility in energy, while delivering the enormous productivity gains required to keep up with substantial growth in the world economy this decade, face the innovation dilemma—how do you achieve meaningful innovation at enterprise-scale? Join Schlumberger, Director, Corporate Strategy & Marketing, Amit Singh, as he presents real-world solutions to the energy dual challenge, with examples of highly-successful deployments of digital technology that harness data and AI to deliver automation for customers around the globe. Amit will show how Schlumberger is leveraging industry-wide collaboration and partnership to deliver low carbon operations while driving a sustainable future.
March 10, 2022
Schlumberger expanded its INNOVATION FACTORI network with the opening of a new center in Houston, Texas.
Learn How Using ConnectedProduction Lift Surveillance’s Real Time AI Response Prioritization Technology Reduces Downtime and Deferred Production
March 24, 2022
Sensia Automation and Rockwell
Automatically prioritize wells by the criticality of their real-time operational condition with ConnectedProduction Lift Surveillance’s state-of-the-art artificial intelligence software. It’s easy to deploy and available in both cloud (SaaS) and on-prem architectures to fit into your organization today, regardless of size, scale, or level of digitalization. Created by combining technologies from trusted industry leaders Schlumberger Technology and Rockwell Automation, you can rest assured the software will continue to grow and adapt for years to come.
The New Era of Surface Logging: Digital, Automated and Sustainable
March 03, 2022
Mud gas and cuttings analysis remains at today the only direct measurement of, respectively, the reservoir fluid and rock, until a PVT sample and a core are available for laboratory analysis. Surface logging data is an attractive solution for the client to take real-time decisions as they are available while drilling, on a continuous basis and at relatively low cost. Nowadays the accuracy and quality of the surface logging data has reached a level comparable to more sophisticated downhole tools thanks to the technological evolution, processes automation and innovative digital workflows. In this presentation we will describe how Artificial Intelligence and Machine Learning models and ground-breaking algorithms permit a more quantitative and objective approach to determine lithology classification, enhance the accuracy of the mud gas data even in extreme drilling conditions and enable predicting fluid properties while drilling.