machine learning

With evolving targets and techniques, the digital landscape is quaking. Are you cyber-ready for the threats?

Research shows how to understand the role of individual neurons in a neural network.

Like biological brains, artificial neural networks may depend on slow-wave sleep for learning.

Machine learning enables fast, cost-effective, and accurate methane emissions detection in remote areas.

Despite streams of data being available on platforms about the condition of topside and drilling equipment, most experts agree that only a small fraction of such data is used. Whether for a fleet or single platform, AI can transform an offshore enterprise.

An AI-based application enabled operators to preempt ESP failures while optimizing production.

Artificial intelligence systems can be trained to recognize visual content in drawings and provide a simplified context. The complete paper highlights the use of AI to process a scanned drawing and redrawing it on a digital platform.

Time-stamped data anomalies can lead to more-accurate identification and faster diagnosis.

This paper describes an automated work flow that uses sensor data and machine-learning (ML) algorithms to predict and identify root causes of impending and unplanned shutdown events and provide actionable insights.

This paper presents a fatigue-prediction methodology designed to extend the life of unbonded flexible risers and improve the accuracy of floating production, storage, and offloading vessel response analysis.