Radial jet drilling and heat transfer modelling in fractured reservoirs

L. Torres, S. Salimzadeh, Maiya Medetbekova, Hamid Nick

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    Abstract

    In this study, the application of the Radial Jet Drilling (RJD), a novel stimulating technique for enhancing productivity in the existing wells in deformable naturally fractured reservoirs was investigated using a robust three-dimensional finite element DFM (discrete fracture-matrix) model. Results showed that the RJD laterals were more effective in enhancing injectivity/productivity in cases with lower fracture density, i.e. lower equivalent permeability, while they had no significant effect on the heat production in these cases. In higher fracture density cases, the RJD laterals improved the heat production while had no significant effect on the injectivity/productivity. Results also showed that in reservoirs with very low permeability matrix, the RJD laterals can be used to connect the wells to the fracture network and hence enhance the well performance. The sensitivity analysis on the average net energy production rate with respect to the length of the RJD laterals showed that in the situations where the wells were not connected directly to the fractures, the length of RJD laterals played a crucial role in enhancing the average net energy rate. However, the 100 m laterals almost removed the dependency of the average net energy production rate on the well placement for low, medium and high fracture density cases.
    Original languageEnglish
    Publication date2019
    Publication statusPublished - 2019
    EventDanish Hydrocarbon Research and Technology Centre
    Technology Conference 2019
    - Comwell Kolding, Kolding, Denmark
    Duration: 5 Nov 20196 Nov 2019
    https://dhrtc.easysignup.com/16/

    Conference

    ConferenceDanish Hydrocarbon Research and Technology Centre
    Technology Conference 2019
    LocationComwell Kolding
    Country/TerritoryDenmark
    CityKolding
    Period05/11/201906/11/2019
    Internet address

    Keywords

    • Stimulation methods
    • DFN

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