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    Modeling Lost-Circulation in Fractured Media Using Physics-Based Machine Learning

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    Type
    Conference Paper
    Authors
    Albattat, Rami cc
    He, X.
    AlSinan, M.
    Kwak, H.
    Hoteit, Hussein cc
    KAUST Department
    King Abdullah University of Science and Technology
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Energy Resources and Petroleum Engineering Program
    Ali I. Al-Naimi Petroleum Engineering Research Center (ANPERC)
    Date
    2022
    Permanent link to this record
    http://hdl.handle.net/10754/678305
    
    Metadata
    Show full item record
    Abstract
    This work provides a novel machine learning approach to model lost-circulation in a naturally fractured formation. As input, the modeling tool requires the observed mud rate, mud physical properties, pressure flowing bottom-hole condition, if available. The deep neural network tool is trained using a physics-based model based on full-physics Cauchy momentum equation for non-Newtonian fluid, which can serve an accurate and quick estimate of the effective hydraulic aperture of natural fracture, and predictions for cumulative mud loss volume, and final stopping time leakage behavior. Such information can help take the preventive/corrective decision, such as the optimum drilling additive design for the lost circulation material. To our best knowledge, the proposed machine learning workflow is applied for the first time for modeling lost circulation events in fractured formations.
    Citation
    Albattat, R., He, X., AlSinan, M., Kwak, H., & Hoteit, H. (2022). Modeling Lost-Circulation in Fractured Media Using Physics-Based Machine Learning. 83rd EAGE Annual Conference & Exhibition. https://doi.org/10.3997/2214-4609.202210204
    Publisher
    European Association of Geoscientists & Engineers
    Conference/Event name
    83rd EAGE Annual Conference & Exhibition
    DOI
    10.3997/2214-4609.202210204
    Additional Links
    https://www.earthdoc.org/content/papers/10.3997/2214-4609.202210204
    ae974a485f413a2113503eed53cd6c53
    10.3997/2214-4609.202210204
    Scopus Count
    Collections
    Conference Papers; Energy Resources and Petroleum Engineering Program; Ali I. Al-Naimi Petroleum Engineering Research Center (ANPERC); Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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