Data & Analytics
This article is the third in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Zikri Bayraktar, a senior machine learning engineer with SLB’s Software Technology and Innovation Center, discusses the expanding use of artificial intelligence in the upstream sector.
This article presents a results-driven case study from an ongoing collaboration between a midstream oil and gas company and Neuralix Inc.
As carbon capture scales up worldwide, the real challenge lies deep underground—where smart reservoir management determines whether CO₂ stays put for good.
-
SponsoredAs operators strive to increase production under tighter budgets, traditional downhole diagnostics are falling short—too costly, complex, and time-consuming. Seismos Acoustic Friction Analysis (SAFA) offers a smarter, surface-based alternative. This white paper explores how SAFA enables real-time treatment optimization, better fracture performance, and substantial cos… -
The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.
-
Over decades of exploration and production, the oil and gas sector has accumulated vast amounts of legacy data in various formats. Artificial intelligence and machine learning present an opportunity to transform how this unstructured data is processed and used, enabling significant improvements in operational efficiency and decision-making.
-
Terra Drone will support Aramco's operations and Saudi Arabia's technological and economic progress.
-
Organic data governance emphasizes flexibility, stakeholder engagement, and a culture that values data integrity.
-
SLB will use artificial intelligence-based software to help ensure the delivery of 18 ultradeepwater wells.
-
A robotic arm, camera system, and virtual reality helped EniProgetti and University of Naples researchers overcome the major challenges of direct-contact nondestructive testing using a drone.
-
Shell’s combination of digital worker technologies enables collaborative troubleshooting and inspections while reducing travel and boosting efficiency.
-
In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
-
This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
