Digital oilfield
The authors propose a hybrid virtual flow and pressure metering algorithm that merges physics-based and machine-learning models for enhanced data collection.
This paper discusses the concept, applications, and continual evolution of a new 3D temperature and spectral-acoustics modeling and logging approach.
This paper presents various functionalities and benefits of a monitoring tool developed for and used with all critical flowmeters in the operator’s production system.
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Guest Editorial: 2025 Perspective: Digital Transformation in Oil and Gas—From Evolution to ShockwaveThe path forward is not just about automation—it is about augmentation. AI is not replacing human expertise; it is amplifying it. Those who master this balance will define the future of oil and gas in a rapidly evolving energy landscape. -
The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.
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These papers provided insights and advances into field-operations automation, machine-learning-assisted petrophysical characterization, and fluid-distribution analysis in unconventional assets.
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This paper presents a complete digital workflow applied to several greenfields in the Asia Pacific region that leads to successful deep-transient-testing operations initiated from intelligent planning that positively affected field-development decisions.
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This study introduces a cleanup- and flowback-testing approach incorporating advanced solids-separation technology, a portable solution, equipment automation, improved metallurgy, and enhanced safety standards.
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Located 230 km south of Abu Dhabi, the onshore Shah field produces around 70,000 B/D of crude.
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A new report from GlobalData provides an overview of the digitalization efforts within the industry and their potential to transform operations.
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The authors of this paper discuss how intelligent completions in the Gulf of Mexico have allowed for increased production, reduction in operating expenses, enhanced overall reservoir recovery, and improved safety and environmental performance.
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AI can transform our work, but it demands the highest accuracy. Anything less than perfect in oil and gas and other heavy-asset industries is unacceptable.
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Digitalization and automation of the drilling process drive the need for an interoperability platform in a drilling operation, where a shared definition and method of calculation of the drilling process state is a fundamental element of an infrastructure to enable interoperability at the rigsite.
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