Digital oilfield
This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
This paper proposes a novel approach toward drilling maximum-reservoir-contact wells by integrating automated drilling and geosteering software to control the downhole bottomhole assembly, thereby minimizing the need for human intervention.
This paper offers an exploration into the field applications of multiphase flowmeters (MPFMs) across global contexts and the lessons learned from implementation in a smart oil field that uses several types of MPFM.
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This article explores how the pursuit of a "perfect" reservoir model may be hindering progress in an industry increasingly shaped by data, uncertainty, and AI. -
Operators that demand control of their future position in global energy production are forging ahead into new territory by digitally transforming their operations at a time that still feels relatively comfortable. They’ve recognized that, while traditional approaches served the industry well for many decades, the chance to reimagine how they do things is not something…
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Weatherford International announced a strategic agreement with Amazon Web Services (AWS) to advance the company's digital transformation and drive innovation across the energy sector.
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This paper describes the operator’s digital-twin end-to-end production system deployed for model-based surveillance and optimization.
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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.
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This paper presents an immersive platform that enables multidisciplinary teams and management to make decisions, connecting professionals to demonstrate and share findings in a way that capitalizes on artificial intelligence and cognitive capabilities.
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The paper showcases the digital journey of a brownfield where digital solutions are enhancing recoverable volume, production, and process efficiency while minimizing losses and maximizing the return of investment.
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The rapid development of oil and gas intelligent operations depends on artificial intelligence, automation, and data analytics to achieve optimal conditions in oil and gas operations.
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SponsoredAs operators strive to increase production under tighter budgets, traditional downhole diagnostics are falling short—too costly, complex, and time-consuming. Seismos Acoustic Friction Analysis (SAFA) offers a smarter, surface-based alternative. This white paper explores how SAFA enables real-time treatment optimization, better fracture performance, and substantial cos…
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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.
