Data & Analytics
Working with Dell Technologies and NVIDIA, the French supermajor is targeting improved seismic processing and artificial intelligence applications.
A discussion at the inaugural executive breakfast convened by the SPE Data Science and Engineering Analytics Technical Section, held alongside CERAWeek by S&P Global and powered by Black & Veatch, tackled the challenge of value creation from artificial intelligence in the energy industry.
AI‑driven data center growth is straining US power grids and accelerating interest in enhanced geothermal systems as a scalable, low‑carbon solution.
-
This paper focuses on developing a model that can be used in an automated, end-to-end flare-smoke detection, alert, and distribution-control solution that leverages existing flare closed-circuit television cameras at manufacturing facilities. -
This paper describes an experimentation trial deploying and operating a computer-vision system on a deepwater rig to measure drilled cuttings in real time using a remotely monitored camera system.
-
Real-time wellhead monitoring aims to help Romania meet new EU methane emission regulations.
-
The supermajor’s Energy Outlook 2025 suggests geopolitical fragmentation could tilt the balance of the energy trilemma toward energy security and away from sustainability.
-
The companies said they plan to start deploying digital twin technologies in Oman this year.
-
Intelligent completions could improve many of the world’s oil and gas wells, but not all are suited to the technology. There is another option.
-
Oil and gas experts encourage human/AI partnerships that can “supercharge” capabilities to create competitive advantages.
-
The paper describes the deployment of fiber-optic monitoring of CO₂ injection and containment in a carbonate saline aquifer onshore Abu Dhabi.
-
This paper presents a novel workflow with multiobjective optimization techniques to assess the integration of pressure-management methodologies for permanent geological carbon dioxide storage in saline aquifers.
-
This paper reviews the motivation and development of response-based forecasting from the perspective of the authors, reviewing examples and processes that have served as validation and led to modeling refinement.
![JPT_2025-09_GuestEd1_SS_382853197[4].jpg](https://assets.spe.org/dims4/default/860913d/2147483647/strip/true/crop/850x475+0+46/resize/365x204!/quality/90/?url=http%3A%2F%2Fspe-brightspot.s3.us-east-2.amazonaws.com%2F8a%2F95%2Fe4e82cb54fd597d497a5b1267f8a%2Fjpt-2025-09-guested1-ss-3828531974.jpg)
