Directional/complex wells
This paper presents the mitigation of drilling challenges encountered in the Niger Delta through a technique that relates shale resistivity to shale porosity and vertical effective stress to predict pore pressure.
This work provides a new modeling tool, validated against a static-wellbore solver and field data, to estimate and manage downhole temperature in higher-temperature oil, gas, and geothermal wells.
The Research Council of Norway’s $118,000 grant will support development of longer fishbone laterals to raise production while lowering carbon footprints.
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This case study presents results achieved in Romania, Mexico, and Kuwait with the use of a series of innovations featuring integrated bottomhole assemblies. A push-the-bit system combines high-performance drilling with precise directional control.
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This paper highlights the potential of machine learning to be used as a tool in assisting the drilling engineer in bit selection through data insights previously overlooked.
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A leaner and wiser Weatherford seeks new Middle East contracts while growing margins and market share on existing business.
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This paper presents a physics-based approach to predict sand production for various reservoir and completion types, explored through a case study of recent production wells in a sandstone reservoir development.
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This paper discusses novel acoustic techniques used to identify productive zones and areas of sand production in a well with a sanding event.
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ADNOC awarded a new round of contracts to international service companies, intending to apply directional drilling and LWD to boost production by getting a better assessment of its reservoirs.
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An automated detection application helped identify stringers early for an operator of a mature field in the North Sea while drilling multilateral wells through reservoir sections containing hard calcite stringers interspersed in sand formations with low unconfined compressive strength. The application guided drilling decisions that minimized invisible lost time and sh…
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The drilling of wells in shale and granite shares a common need—faster drilling is required to make it work.
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The paper describes the experience of using a machine-learning model prepared by the ensemble method to prevent stuck-pipe events during well construction in extended-reach wells.
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Artificial intelligence and machine learning, which can effectively mine deep insight from a large amount of drilling operational data and synthetic forward modeling data, are starting to shape the design and operations of extended-reach and complex wells.