Drilling automation
This study explores the use of autoencoder models with convolutional neural networks to present a framework and prototype for early and accurate kick detection during offshore oilwell drilling.
This paper presents the first global application of autonomous drilling in deepwater and the journey to reach optimal drilling parameters, integrating proprietary tools from the project’s business partners.
Drilling experts recently shared candid views on what will be required for their segment of the upstream business to move to the next stage of development.
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The authors describe challenges that must be overcome to reach the goal of drilling systems automation. -
This paper details the introduction of a drilling automation system to deliver superior well-construction performance in a major gas field.
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MPD was used to successfully drill through a pore pressure ramp and address a well-control event in conjunction with conventional methods.
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Drilling automation and innovation continue as dominant trends despite market downturns and unprecedented challenges in the past year. In many ways, the drive toward new efficiencies and step changes in well-construction performance has taken on an even greater sense of urgency.
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The complete paper presents a solution that integrates a physics-based torque-and-drag (T&D) stiff/soft string model with a real-time drilling analytics system using a custom-built extract, transform, and load translator and digital-transformation applications to automate the T&D modeling work flow.
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The service companies plan to co-market an emerging well control system that can integrate with established managed-pressure-drilling components to enhance well construction safety and efficiency.
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Brazil’s national oil company details the results of 6 years of real-time drilling monitoring. The next step is to move toward optimization, then automation.
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An intelligent drilling optimization application performs as an adaptive autodriller. In the Marcellus Shale, ROP improved 61% and 39% and drilling performance, measured as hours on bottom, improved 25%.
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A real-time deep-learning model is proposed to classify the volume of cuttings from a shale shaker on an offshore drilling rig by analyzing the real-time monitoring video stream.
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The best way to know how drilling affects drill bits is to visualize the bits. A device that creates high-resolution images for precise measurements is one of three technologies being featured in a JPT series on drilling measurement innovations.
