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Liquid-Rich Shale Well Modelling and Optimisation (RES30)


    This course deals with the quantitative reservoir and well modelling of liquid-rich shale resources, providing the necessary skills and toolkit to produce reliable production forecasts of existing wells with production performance, and new wells where many uncertainties lead to a range of forecasted performance. The topics also include determination of in-place volumes of gas and oil, and expected recoveries. Emphasis on optimized production is given in terms of total value, properly translating gas and oil rate profiles to revenue profiles. Likewise, an approach is given to optimize well completion strategy with proper treatment of the cost model.
    Engineering methods range from rigorous 2D and 3D finite-difference finely-gridded well models, both black-oil and EOS, to simpler methods such as Fetkovich decline curve analysis (DCA) that properly treat long-time infinite-acting behaviour transitioning into longer-term pseudosteady state performance (Arps).
    A rigorous treatment of PVT in liquid-rich shales is one of the key contributions of this course, where it is shown clearly (in our 2012 SPE paper 155499 “PVT in Liquid-Rich Shale Reservoirs”) that PVT and fluid flow are strongly coupled, and must be treated accordingly.

    Course Level: Advanced
    Instructor: Curtis H. Whitson

    Designed for you, if you are...

    Reservoir engineers, production engineers, engineering managers (not familiar with shale resource development), and geological engineers - with one thing in common, wanting to know how better to quantitatively forecast shale oil and gas resources reliably.

    The benefits from attending

    The course emphasizes all first-order (key) factors that affect production performance and reserve estimation - e.g. matrix permeability and porosity, natural fracture contribution to "effective" rock permeability, hydraulic fracture size (area connecting wellbore to reservoir rock), PVT, relative permeability, and geologic considerations (e.g. lamination and stress orientation).
    You will learn what minimum data are required to perform reliable production history matching and production forecasting, including PVT samples and PVT data, historical rates of gas, oil, and water, flowing pressures, and key reservoir / well completion data (well dimensions, depths, etc.). How to QC these data and best use them in history matching.
    Numerical well modelling is used in exercises, and compared with simpler models such as Fetkovich-based transient/PSS decline curve analysis and other relevant pressure-rate transient models.
    PVT modelling will be covered in detail, including development of EOS models and in-situ fluid estimation for liquid-rich shale reservoirs, generation of consistent black-oil PVT tables, and using the PVT models for optimized (value-based) daily drawdown well control.
    All of the main cause-and-effects in production performance forecasting, modelling, history matching, optimal well spacing, and optimal well design-and-control will be covered.


    • Dry-gas shale well performance - basics
    • Liquid-rich shale well performance - basics
    • PVT in liquid-rich shale reservoirs
    • Modelling shale wells using finely-gridded numerical models
    • Plausible geological models - what and how to use in modelling
    • History matching LRS wells
    • Daily (value-based) well optimized drawdown control
    • Optimizing new-well design with production forecasting and cost model
    • Uncertainty analysis

    Morning sessions are mostly lectures and theory. Afternoon sessions are mostly hands-on problem solving with advanced Excel-based DCA methods, numerical well modelling, and EOS-based PVT software.




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    HOT Engineering Vienna Office

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