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This article is the second in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Madhava Syamlal, CEO and founder of QubitSolve, discusses the present and future of quantum computing.
The full potential of data can only be realized when it is viewed not in isolation but as part of the dynamic triad of hydrocarbons, the data, and the people who interpret it and act on it.
Over decades of exploration and production, the oil and gas sector has accumulated vast amounts of legacy data in various formats. Artificial intelligence and machine learning present an opportunity to transform how this unstructured data is processed and used, enabling significant improvements in operational efficiency and decision-making.
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Shell’s combination of digital worker technologies enables collaborative troubleshooting and inspections while reducing travel and boosting efficiency.
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After 5 years of in-depth diagnostic research, the Oklahoma City-based operator shares more insights on fracture behavior.
After a successful trial phase of ENERGYai, AIQ has been tapped to roll out the technology across ADNOC’s upstream operations.
Weatherford and AIQ say they aim to enable the energy sector to unlock efficiencies, boost productivity, and reduce operational costs by combining their strengths.
Terra Drone will support Aramco's operations and Saudi Arabia's technological and economic progress.
The company said that adding Altair technology to its Xcelerator open digital business platform will create the world’s most complete AI-powered portfolio of industrial software.
The Louisiana contractor is buying Kystdesign for an undisclosed sum, expanding its underwater vehicle business.
The technology, which uses Industrial Internet of Things components, aims to reduce the costs and improve the safety of drilling operations.
Although 92% of energy companies say they plan on digital technology investments, only 27% currently retrain and reskill existing employees to meet the upcoming demand, according to a recent survey from Ernst & Young.
The acquisition of the imaging company gives Kraken offices in Colorado and Texas.
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This paper presents a continuous passive magnetic ranging technique that can provide real-time distance and direction to the offset well while drilling without interrupting drilling operations. -
The authors of this paper describe a project to develop a virtual sensor to monitor the cooling effect downstream of a subsea choke to avoid hydrate plugs during cold-start operations. -
In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems. -
This study presents a production-optimization method that uses a deep-learning-based proxy model for the prediction of state variables and well outputs to solve nonlinearly constrained optimization with geological uncertainty.
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This paper describes the operator’s digital-twin end-to-end production system deployed for model-based surveillance and optimization. -
This paper presents a lost-circulation model used during design and job-evaluation phases to accurately predict top of cement and equivalent circulating densities. -
This comprehensive review of stuck pipe prediction methods focuses on data frequency, approach to variable selection, types of predictive models, interpretability, and performance assessment with the aim of providing improved guidelines for prediction that can be extended to other drilling abnormalities, such as lost circulation and drilling dysfunctions. -
This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
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Real-time location systems have emerged as invaluable tools for enhancing safety and efficiency in the operations of oil and gas organizations. This paper investigates the various applications of the technology within the industry, highlighting its transformative effect on safety protocols and operational efficiency.
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New case studies highlight how artificial intelligence, advanced hardware, and innovative business models are enabling success in drilling automation.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
