Manik Singh

Manik Singh

Houston, Texas, United States
3K followers 500+ connections

About

I like to work in the common ground between physics based and data driven models…

Activity

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Experience

  • Ensign Natural Resources  Graphic

    Ensign Natural Resources

    Houston, Texas, United States

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    Houston, Texas, United States

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    Bakersfield, California, United States

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    Dallas, Texas, United States

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    State College, Pennsylvania Area

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    Dallas/Fort Worth Area

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    Houston

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    Gurgaon, India

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    Gurgaon, India

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    Brunei Darussalam

Education

  • Penn State University Graphic

    Penn State University

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    Activities and Societies: Society of Petroleum Engineers

    I modeled a hydraulic propagation model coupled to a seismic wave propagation mdoel under a Bayesian model selection framework for quick delineation of fracture properties and reservoir characterization.

    Selected coursework:
    Numerical solution of PDE of flow in porous media
    Natural gas engineering
    Sampling and monitoring of geo-environment
    Reservoir Characterization
    Data Inversion in Geosciences

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    Activities and Societies: Joint Secretary - SPE ISM Student Chapter, Student Representative, Cairn Industry Institute Interaction Program, Ex- Treasurer Toastmaster's Club

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Licenses & Certifications

Publications

  • Unconventional Reservoir Management Modeling Coupling Diffusive Zone/Phase Field Fracture Modeling and Fracture Probability Maps

    Society of Petroleum Engineers

    The novelty of this work lies in the efficient integration of the phase-field fracture propagation models to diffusive natural fracture networks with a stochastic representation of uncertainty associated with the prediction of natural fractures in a reservoir. The presented method enables practicing engineers to design hydraulic fracturing treatment accounting for the uncertainty associated with the location and spatial variations in natural fractures. Together with efficient parallel…

    The novelty of this work lies in the efficient integration of the phase-field fracture propagation models to diffusive natural fracture networks with a stochastic representation of uncertainty associated with the prediction of natural fractures in a reservoir. The presented method enables practicing engineers to design hydraulic fracturing treatment accounting for the uncertainty associated with the location and spatial variations in natural fractures. Together with efficient parallel implementation, our approach allows for cost-efficient approach to optimizing production processes in the field.

    Other authors
    • Mary F. Wheeler
    • Sanjay Srinivasan
    • Sanghyun Lee
    See publication

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