Fugro Wins Contest With Machine-Learning Model for Pile-Driving Prediction
Using the supplied data set of cone penetration test results, competing teams had to predict the number of hammer blows required to drive the pile a given unit of depth in the North Sea.
Engineering Diagram Processing Featured in Worley and Arundo Global Hub for Advanced Analytics
Using deep-learning and computer-vision techniques, the software recognizes all instances of specific instruments, valves, lines, and other features in a P&I diagram in seconds.
ADNOC, Honeywell Team on Large-Scale Predictive Maintenance Project
ADNOC will utilize Honeywell’s asset monitoring and predictive analytics platform to improve asset efficiency and integrity across the operator’s upstream and downstream businesses.
Corrosion Will Occur, Whether You Like It or Not
Just like Houston’s summer heat, corrosion of metal surfaces will occur—whether you like it or not. To help you better understand corrosion, these papers describe using water surveys in a production/injection plant, testing the effectiveness of mitigation, and data evaluation using machine learning.
Machine Learning Enhances Evaluation of Oil and Gas Assets
Using machine learning (ML), image recognition, and object detection, the use of ML on algorithms to recognize objects and describe their condition were investigated—offering new possibilities for performing inspection and data gathering to evaluate the technical condition of oil and gas assets.
Data-Driven Methods Present Potential for Success
Data-driven methods offer significant advantages in the industry, under certain conditions, over conventional methods. But reservations still exist about their use. The paper serves to bridge the gap between unclear understanding of these methods and their successful acceptance and implementation.
Machine Learning and AI Streamline Automated Maintenance Reviews
Machine learning and artificial intelligence technology offer offshore operators the chance to automate high-cost, error-prone tasks to avoid the effects of inconsistency and errors in analysis, improving efficiencies and safety.
SwRI Develops Autonomous Leak Detection System for Chemical Spills
Southwest Research Institute has developed a leak detection system to autonomously monitor pipelines for hazardous chemical spills. R&D Magazine recently recognized the system as one of the 100 most significant innovations of 2017.
Artificial Intelligence Poised To Change Industry Operations
A consultant examines the ways in which artificial intelligence and machine learning solutions may have a significant impact on industry operations.
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