DSDE: Emerging Technology

Organic data governance emphasizes flexibility, stakeholder engagement, and a culture that values data integrity.

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.

This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.

The agreement aims to bring the efforts of both companies together to advance digital-enabled carbon-free floating power generation.

This paper presents the application of a new automatic geosteering method that combines probabilistic interpretation with artificial intelligence for look-ahead decision-making, representing an innovative advancement in automated geosteering frameworks.

The massive system brings advanced capabilities for simulation, AI, and data analysis to drive breakthroughs in cancer research, materials discovery, energy technologies, and many other fields.

This paper proposes a methodology for preventing drillstring fatigue and failure in deep wells with large shallow doglegs.

In this paper, the authors propose a regression machine-learning model to predict stick/slip severity index using sequences of surface measurements.

This paper presents a novel workflow for using electromagnetic resistivity-based reservoir mapping logging-while-drilling technologies for successful well placement and multilayer mapping in low-resistivity, low-contrast, thinly laminated clastic reservoirs.

A recent study highlights the major challenges the technology faces as operators consider the pros and cons of using additive manufactured parts in a corrosion-prone environment.