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Optimization of Hydraulic Fracture Stages and Sequencing in Unconventional Formations

List Price: $68.99
SKU:
9780367781064
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  • Product Details

    Author:
    Ahmed Alzahabi, Mohamed Y. Soliman
    Format:
    Paperback
    Pages:
    278
    Publisher:
    CRC Press (March 31, 2021)
    Language:
    English
    ISBN-13:
    9780367781064
    Weight:
    16oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260331043202538-20260331.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $68.99
    Case Pack:
    1
    As low as:
    $65.54
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    CRC Press
  • Overview

    Shale gas and/or oil play identification is subject to many screening processes for characteristics such as porosity, permeability, and brittleness. Evaluating shale gas and/or oil reservoirs and identifying potential sweet spots (portions of the reservoir rock that have high-quality kerogen content and brittle rock) requires taking into consideration multiple rock, reservoir, and geological parameters that govern production. The early determination of sweet spots for well site selection and fracturing in shale reservoirs is a challenge for many operators. With this limitation in mind, Optimization of Hydraulic Fracture Stages and Sequencing in Unconventional Formations develops an approach to improve the industry’s ability to evaluate shale gas and oil plays and is structured to lead the reader from general shale oil and gas characteristics to detailed sweet-spot classifications. The approach uses a new candidate selection and evaluation algorithm and screening criteria based on key geomechanical, petrophysical, and geochemical parameters and indices to obtain results consistent with existing shale plays and gain insights on the best development strategies going forward. The work introduces new criteria that accurately guide the development process in unconventional reservoirs in addition to reducing uncertainty and cost.