machine learning

Phase 1 covers the modeling and monitoring of assets for six ADNOC Group companies. The four phases of the project are expected to be completed by 2022.

A new study confirms the success of a natural-gas leak-detection tool pioneered by Los Alamos National Laboratory scientists that uses sensors and machine learning to locate leak points at oil and gas fields, promising new automatic, affordable sampling across a vast natural gas infrastructure.

The complete paper discusses the successful application of a data-driven approach to analyze production data and identify root causes of slugging in a subsea production system on the Norwegian Continental Shelf.

To drive progress in the field of data science, the authors propose 10 challenge areas for the research community to pursue. Because data science is broad, with methods drawing from computer science, statistics, and other disciplines, these challenge areas speak to the breadth of issues.

Automated image-processing algorithms can improve the quality and speed in classifying the morphology of heterogeneous carbonate rock. Several commercial products have produced petrophysical properties from 2D images and, to a lesser extent, from 3D images.

Deep learning is routinely used in products and services that affect hundreds of millions of lives, despite the fact that no one quite understands how it works. Now, the Office of Naval Research has awarded a $7.5 million grant to a group of researchers who think they can unravel the mystery.

Lloyd’s Register has partnered with STC Global to create an artificial intelligence tool expected to provide insight from incident data captured by HSE functions but left untapped.

Advanced machine-learning methods combined with aspects of game theory are helping operators understand the drivers of water production and improve forecasting and economics in unconventional basins.

Forced to tighten their belts financially by the coronavirus pandemic, businesses are increasingly using software that automates back-office tasks. The idea, of course, is for companies to save money by reducing the number of workers they need to handle clerical work.

Recent advances in data technology and machine learning have disrupted many businesses and processes and can lead to a new paradigm in workplace safety as well. This case study demonstrates the application of data science and predictive analytics to aid the health, safety, and environment function.