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    Statistical Methods to Improve the Quality of Real-Time Drilling Data 

    Source: Journal of Energy Resources Technology:;2022:;volume( 144 ):;issue: 009:;page 93006-1
    Author(s): Al-Gharbi, Salem; Al-Majed, Abdulaziz; Abdulraheem, Abdulazeez; Tariq, Zeeshan; Mahmoud, Mohamed
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The age of easy oil is ending, and the industry started drilling in remote unconventional conditions. To help produce safer, faster, and most effective operations, the utilization of artificial intelligence and machine ...
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    Evaluating the Effectiveness of Machine Learning Technologies in Improving Real-Time Drilling Data Quality 

    Source: Journal of Energy Resources Technology:;2022:;volume( 144 ):;issue: 009:;page 93002-1
    Author(s): Al-Gharbi, Salem; Al-Majed, Abdulaziz; Elkatatny, Salaheldin; Abdulraheem, Abdulazeez
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Due to high demand for energy, oil and gas companies started to drill wells in remote environments conducting unconventional operations. In order to maintain safe, fast, and more cost-effective operations, utilizing machine ...
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