DSDE: In Practice

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

The complete paper presents a discussion of the use of intelligent well completion in Santos Basin Presalt Cluster wells.

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.

A real-time deep-learning model is proposed to classify the volume of cuttings from a shale shaker on an offshore drilling rig by analyzing the real-time monitoring video stream.

AltaML has announced a partnership with engineering and design firm Kleinfelder in which the two companies will pair 3D reality scans of facilities with artificial intelligence to look for potential problems and risks.

Researchers with the National Center for Airborne Laser Mapping at the University of Houston are creating a set of algorithms that would allow users to more-precisely align data sets collected at different times and reliably estimate changes between images captured at different times.

An estimate says data centers, including edge sites, will soon use four times the energy all data centers used in 2018. Can it be true?

In this paper, the authors introduce a new technology installed permanently on the well completion and addressed to real-time reservoir fluid mapping through time-lapse electromagnetic tomography during production or injection.

The industry increasingly relies on forecasts from reservoir models for reservoir management and decision making. However, because forecasts from reservoir models carry large uncertainties, calibrating them as soon as data come in is crucial.

A group of people who really care how drillers code the memos added to the daily drilling report is the data scientists—who find that the coded tags do not match the activity. A program that helps drillers code is one of three technologies featured in a JPT series on drilling measurement innovation.