WELLBORE PLANNING SYSTEMS AND METHODS

    公开(公告)号:US20220397027A1

    公开(公告)日:2022-12-15

    申请号:US17661943

    申请日:2022-05-04

    Abstract: Planning a wellbore includes determining drillability values from surface drilling parameters for an offset wellbore. The drillability values are used to prepare a protein code sequence of protein codes assigned to a range of drillability values. The protein code sequence from the offset wellbore is used to develop a protein code sequence for a planned wellbore. A machine learning model analyzes the offset surface drilling parameters and protein code sequence, and provides target surface drilling parameters for the planned wellbore.

    HYBRID NEURAL NETWORK FOR DRILLING ANOMALY DETECTION

    公开(公告)号:US20230082520A1

    公开(公告)日:2023-03-16

    申请号:US17929412

    申请日:2022-09-02

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for detecting a washout or other anomaly event in a wellbore. In particular, in one or more embodiments, the disclosed systems receive a plurality of measurements including a measured flow rate into the wellbore, a measured weight on a drill bit in the wellbore, a measured depth of the drill bit in the wellbore, and a measured pressure at a standpipe of the wellbore. In one or more embodiments, the disclosed systems estimate one or more parameters of a physical model for determining a theoretical estimate of the standpipe pressure. In one or more embodiments, the disclosed systems determine a probability that the washout or other anomaly event is occurring in the wellbore based at least partially upon the measurements and the theoretical estimate of the standpipe pressure.

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