MACHINE LEARNING ASSISTED COMPLETION DESIGN FOR NEW WELLS

    公开(公告)号:US20230205948A1

    公开(公告)日:2023-06-29

    申请号:US17560982

    申请日:2021-12-23

    摘要: Systems and methods for completion design are disclosed. Wellsite data is acquired for one or more existing production wells. The wellsite data is transformed into model data sets for training a first machine learning (ML) model to predict well logs. A first well model uses the well logs to estimate production of the existing well(s). Parameters of the first well model are tuned based on a comparison between the estimated and actual production of the existing well(s). A second ML model is trained to predict parameters of a second well model for a new well, based on the tuned parameters of the first well model. The new well's production is forecasted using the second ML model. Completion costs for the new well are estimated based on the well's completion design parameters and the forecasted production. Completion design parameters are adjusted, based on the estimated completion costs and the forecasted production.

    EVENT MODEL TRAINING USING IN SITU DATA
    38.
    发明公开

    公开(公告)号:US20230169369A1

    公开(公告)日:2023-06-01

    申请号:US18159658

    申请日:2023-01-25

    申请人: Lytt Limited

    IPC分类号: G06N5/04 E21B47/00 G06N20/00

    摘要: A method of identifying events within a wellbore comprises obtaining a first set of measurements of a first signal within a wellbore, identifying one or more events within the wellbore using the first set of measurements, obtaining a second set of measurements of a second signal within the wellbore, wherein the first signal and the second signal represent different physical measurements, training one or more event models using the second set of measurements and the identification of the one or more events as inputs, and using the one or more event models to identify at least one additional event within the wellbore.