1
FOR MORE INFORMATION, CONTACT US AT FRACTUREID.COM WHAT WE FOUND HOW THIS IMPROVES COMPLETIONS MECHANICAL FACIES MODEL IS A PREDICTION WIZARD Fracture ID and Hawkwood Energy joined forces to predict pressure treatment responses by using a Mechanical Facies model. We utilized Young’s Modulus (YM) and Minimum Horizontal Stress (ShMIN) along with bedding and fracturing measured along the well to derive unique rock types and their impact to completion responses. The reason rock types were chosen rather than single rock mechanical measurements is explained in the plot to the right. While some trends can become evident (e.g. PR), the rock characteristics are more complicated than any one single measurement and need to be studied using a multivariate approach.By training each facie to a rock type’s specific treatment response, the model predicted hydraulic treatment responses on the next well’s completion. Results from post-frac analysis indicate that the predicted frac gradient from the mechanical facies model correlated extremely well with the actual post- frac gradient (an R2 value of 0.64), while plotting stress vs. gamma ray alone showed no statistical correlation. The model incorporates varying mechanical properties along the wellbore that are used to improve cluster treatment efficiency along with the ability to treat additional clusters per well. Fracture ID can predict how changing stages will affect perf cluster treatment efficiency with credible accuracy. These predictions improve operational efficiency and optimize stimulations for specific rock types not otherwise identified using single or sparse measurements to determine lithology. 78.0 76.0 74.0 72.0 70.0 68.0 66.0 64.0 62.0 60.0 58.0 56.0 54.0 52.0 50.0 48.0 46.0 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35 r2=0.03 GAMMA VS. FRAC GRADIENT GAMMA RAY FRAC GRADIENT (PSI/FT) POISSON’S RATIO VS. FRAC GRADIENT POISSON’S RATIO FRAC GRADIENT (PSI/FT) 0.34 0.33 0.32 0.31 0.30 0.29 0.28 0.27 0.26 0.25 0.24 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35 r2=0.19 HISTORY MATCHED WELL UNCOMPLETED WELL FACIES % BY STAGE (0–8) ACTUAL FRAG GRADIENT (1.5–0/88) CALIBRATED FRAC GRADIENT (1.5–0.88) 1.45 1.25 1.05 0.85 0.65 0.65 0.85 1.05 1.25 1.45 PREDICTED FRAC GRADIENT RECORDED FRAC GRADIENT y=0.955x + 0.0488 R2=0.6375

FRACTUREID · 2018. 7. 17. · Minimum Horizontal Stress (ShMIN) along with bedding and fracturing measured along the well to derive unique rock types and their impact to completion

  • Upload
    others

  • View
    3

  • Download
    0

Embed Size (px)

Citation preview

  • FOR MORE INFORMATION, CONTACT US AT

    FRACTUREID.COM

    WHAT WE FOUND

    HOW THIS IMPROVES COMPLETIONS

    MECHANICAL FACIES MODEL IS A PREDICTION WIZARDFracture ID and Hawkwood Energy joined forces to predict pressure treatment responses by using a Mechanical Facies model.

    We utilized Young’s Modulus (YM) and Minimum Horizontal Stress (ShMIN) along with bedding and fracturing measured along the well to derive unique rock types and their impact to completion responses. The reason rock types were chosen rather than single rock mechanical measurements is explained in the plot to the right. While some trends can become evident (e.g. PR), the rock characteristics are more complicated than any one single measurement and need to be studied using a multivariate approach.By training each facie to a rock type’s specific treatment response, the model predicted hydraulic treatment responses on the next well’s completion.

    Results from post-frac analysis indicate that the predicted frac gradient from the mechanical facies model correlated extremely well with the actual post-frac gradient (an R2 value of 0.64), while plotting stress vs. gamma ray alone showed no statistical correlation. The model incorporates varying mechanical properties along the wellbore that are used to improve cluster treatment efficiency along with the ability to treat additional clusters per well.

    Fracture ID can predict how changing stages will affect perf cluster treatment efficiency with credible accuracy. These predictions improve operational efficiency and optimize stimulations for specific rock types not otherwise identified using single or sparse measurements to determine lithology.

    78.076.074.072.070.068.066.064.062.060.058.056.054.052.050.048.046.0

    0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35

    r2=0.03

    GAMMA VS. FRAC GRADIENT

    GA

    MM

    A R

    AY

    FRAC GRADIENT (PSI/FT)

    POISSON’S RATIO VS. FRAC GRADIENT

    PO

    ISSO

    N’S

    RA

    TIO

    FRAC GRADIENT (PSI/FT)

    0.34

    0.33

    0.32

    0.31

    0.30

    0.29

    0.28

    0.27

    0.26

    0.25

    0.24

    0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35

    r2=0.19

    HISTORY MATCHED WELL

    UNCOMPLETED WELL

    FACIES % BY STAGE (0–8) ACTUAL FRAG GRADIENT (1.5–0/88)

    CALIBRATED FRAC GRADIENT (1.5–0.88)

    1.45

    1.25

    1.05

    0.85

    0.650.65 0.85 1.05 1.25 1.45

    PR

    EDIC

    TED

    FR

    AC

    GR

    AD

    IEN

    T

    RECORDED FRAC GRADIENT

    y=0.955x + 0.0488R2=0.6375