Digital Oil Field
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents a competency-centered, data-driven approach implemented to strengthen control-room emergency-response capability through a cloud-hosted, scenario-based virtual plant simulator.
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
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As the drilling industry improves its efforts to capture drilling operation activities in real time, it has generated a significant amount of data that drilling engineers cannot process on their own. -
A real-time method is presented to predict impending stuck pipe with sufficient warning to prevent it. The new method uses automated analysis of real-time modeling coupled with real-time-data analysis.
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Over the last couple of decades, we have seen a steady stream of “intelligent” innovations go from ideas to infancy to catalog solutions.
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Permanent downhole gauges (PDGs) can provide a continuous record of flow rate and pressure, which provides extensive information about the reservoir. In this work, a machine-learning framework based on PDG data was extended to two applications: multiwell testing and flow-rate reconstruction.
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This paper describes an “active” monitoring technique that uses a direct search method to optimize the sequence of interval-control-valve (ICV) positions during a routine multirate test in an I-well.
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This paper presents information regarding the installation of intelligent-well completions (IWCs) in the Lula and Sapinhoá fields of the Santos basin presalt cluster (SBPSC).
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The case for focusing on boosting recovery from older fields in a depressed drilling climate is compelling. At a breakfast session during IHS CERAWeek on squeezing more oil from brownfields in a low oil price environment, panelists discussed today’s improved field recovery capabilities.
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The Samarang oil field, offshore Sabah, Malaysia, is undergoing a redevelopment project with integrated operations. Several work flows were designed and deployed in order to achieve an early milestone of providing real-time well-performance monitoring, surveillance, and optimization.
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In the past decade, fiber-optic -based sensing has opened up opportunities for in-well reservoir surveillance in the oil and gas industry. In this paper, the authors present a recent example of single-phase-flow profiling with distributed acoustic sensing.
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Despite the recent market conditions during the last year, our industry continued to demonstrate further advances in the monitoring and surveillance field and to attest to the added value provided.
