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Acid Fracturing: An Alternative Stimulation Approach in Carbonates Ding Zhu, Texas A&M University

Acid Fracturing: An Alternative Stimulation Approach in ... · Fiction: Hydraulic fracture with proppant is always better Formation mechanical properties, rock mineralogy and

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  • Acid Fracturing: An Alternative Stimulation Approach in Carbonates

    Ding Zhu, Texas A&M University

  • Background

    Propped fracturing

    Slide 2

    Acid fracturing Matrix acidizing

  • Acid Fracturing

    Pro• Easy to pump• Screenout free• Network building in natural fractured formation• Smaller scale compared with propped fracturing

    Con• Depends on formation heterogeneity more critically • Only works for carbonate/carbonate rick formation• Conductivity declines fast as closure stress

    increases

    Slide 3

  • Main Issues in Acid Fracturing

    • Candidate selection• Optimization design (rate, volume)• Multi-stage/zonal isolation/diversion• Modeling of acid fracturing, fully numerical

    models and empirical correlations• Conductivity testing procedures• Productivity predictions

    Slide 4

  • ModelingEmpirical Correlations for Fracture Conductivity• Nierode-Kruk (1973)• Gangi (1978)• Walsh (1981)• Gong (1993)• Mou-Deng (2013)

    Numerical Modeling for Transport Simulation• Settari (1993)• Oeth (2013)

    Slide 5

  • Acid fracture scale Experimental scale

    Intermediate scale

    Scaling ProblemSlide 6

  • Nierode and Kruk (1973) – Exponential function

    Gangi (1978) – Power function

    Walsh (1981) – Logarithmic function

    Conductivity Correlations

    32131 C

    cf CCwk

    cf CCwk ln2131

    cf CCwk 21 exp

    Slide 7

  • Empirical Correlations by Mou-Deng

    expf cwk

    0.520.42.8

    , ,00.22 0.01 1f D x D D z Dwk

    414.9 3.78ln 6.81ln 10D E

    9 3 1 2 , 3 4 5 , 601 2 3 4 5 6

    4.48 10 1 ( ( )) ( ( )) ( 1)

    1.82, 3.25, 0.12, 1.31, 6.71, 0.03

    Df D x D zwk w a erf a a a erf a a e

    a a a a a a

    Slide 8

  • Empirical Correlations for Conductivity

    0.1

    1

    10

    100

    1000

    10000

    100000

    0 1000 2000 3000 4000 5000 6000 7000

    c

    (psi

    )

    wkf (md-ft)

    Nierode-Kruk model

    Mou-Deng model

    Slide 9

  • Numerical Model: Etching Width Prediction

    2D Solutions– Type curves to predict penetration

    (Roberts and Guin, 1974)

    – Early simulators based on finite difference

    – Typically some average integrated across channel (Settari, 1993)

    Settari (1993)

    2

    2

    y

    CD

    y

    Cv

    x

    Cu eff

    1 'nbeff kCy

    CD

    Slide 10

  • Settari (2001) modified 2D approach– No height dependence

    – Analytical velocity solution applied

    Romero (1998) 3D approach– Analytical velocity solution applied

    Settari et al. (2001)

    2

    2

    y

    CD

    z

    Cw

    y

    Cv

    x

    Cu

    t

    Ceff

    Numerical Model: Etching Width PredictionSlide 11

  • 3D Acid Transport Model (Oeth, 2013)

    vLeakoff

    Qinj

    wid

    th

    dire

    ctio

    n

    • Velocity profile for non-Newtonian fluid• Acid concentration in y-direction• Leakoff from fracture to formation

    y

    CD

    yz

    Cw

    y

    Cv

    x

    Cu

    t

    Ceff

    Slide 12

  • Mass Balance: Reaction of acid vs. volume of rock removed f = fraction of leakoff acid to react with the fracture surfaces

    before entering the formation

    Acid-Etched Width with Leakoff

    y

    CDCfv

    MW

    t

    tzxyeffL

    acid

    1

    ),,(w

    idth

    di

    rect

    ion

    Slide 13

  • Simulation Results

    • Straight acid

    • Gelled acid

    Slide 14

    (Al Jawad, 2016)

  • From Conductivity to Productivity

    0

    20000

    40000

    60000

    80000

    100000

    120000

    140000

    160000

    180000

    0 0.1 0.2 0.3 0.4 0.5 0.6

    Cu

    mu

    lati

    ve

    Pro

    du

    ctio

    n (

    ST

    B)

    permeability (md)

    Straight Acid

    Gelled Acid

    Emulsified Acid

    Slide 15

  • Experimental Conductivity Evaluation

    • Valuable tool for individual field treatment design

    • Evaluate fluid/rock system• Identify etching pattern• Resultant conductivity

    Slide 16

  • Acid Fracturing ProcedureSlide 17

  • Surface Characterization for

    Dissolved Volume and Pattern

    Slide 18

  • Fracture Conductivity Apparatus

    Side Piston

    Load Frame

    Side Piston

    Force

    N2

    Load Frame

    Core Sample

    Mass Flow Controller Back Pressure Regulator

    Pressure Transducers

    Slide 19

  • Etching Pattern: Channeling (Texas Chalk)

    Les

    s co

    nta

    ct t

    ime

    Les

    s et

    chin

    g

    Slide 20

  • Fractured Samples for Conductivity

    21

    (Newmann, et al., 2012)

    Slide 22

  • Candidate Selection

    Fact:Most wells that can be acid fractured are also candidates for propped fracture

    Fiction:Hydraulic fracture with proppant is always better

    Formation mechanical properties, rock mineralogy and reservoir parameters determine the appropriate stimulation method.

    Slide 22

  • Experimental Conditions

    Acid Etching Test Acid Type 20% Gelled HCl AcidInjection rate 1 Liter /minContact Time 10 minutesTemperature 125°F, 150°F

    Well Sample Proppant Type

    Proppant Concentration, lb/ft2

    1 A 30/50 mesh ceramic 0.12 B

    C

    30/50 mesh ceramic

    30/50 mesh ceramic

    0.1

    0.13 D

    E

    20/40 mesh sand

    20/40 mesh sand

    0.2

    0.2

    Propped Fracture Conductivity Test

    Slide 25

  • Acid Etching Results

    0.145 in3 0.241 in3

    0.224 in3 0.414 in3

    Sample A (Well 1) Sample B (Well 2)

    Sample C (Well 2)Sample D (Well 3)

    Slide 26

  • Conductivity ComparisonSlide 28

  • Observations

    • Low unpropped fracture conductivity indicates that a stimulation treatment is required to improve well performance in the studied reservoir.

    • Conductivity of propped fractures was higher than acid fracture conductivity under the closure stress of 7000 psi.

    • For lower reservoir permeability, acid fracturing could be sufficient for well performance stimulation.

    Slide 29

  • Background: Eagle Ford ShaleSlide 27

    Eagle Ford Outcrop with Zone Specification (Gardener et al., 2013)

    • Eagle Ford shale is a potential acid fracturing candidate due to high carbonate content-Zone B averages 70 wt.%-Zone C averages 75 wt.%-Zone D average 83 wt.%

  • Zone B Conductivity ResultsSlide 28

    1

    10

    100

    1000

    0 1000 2000 3000 4000

    Fra

    ctu

    re C

    on

    du

    ctiv

    ity

    (md

    -ft)

    Closure Stress (psi)

    B_1; 28 wt.% HCl 20 minB_2; 28 wt.% HCl 20 minB_3; 15 wt.% HCl 20 min

  • Combined Acid and Proppant

    (Thripathi and Pournik, 2015)

  • Conclusions1. Better models, both empirical and numerical, have been developed

    with geostatistical consideration. These models can help tounderstand the outcomes of acid fracture.

    2. Identifying etching pattern and acid/rock compatibility in labexperimental investigation is recommended for each field/area.

    3. The outcomes of acid fracturing depend on combination of formationrock properties, reservoir flow properties, field operation designparameters. Integrated study with production prediction helps toselect/design the simulation treatments.

    4. Acid fracturing has potential in low perm, high carbonate contentreservoirs.

    Slide 30

  • Thank You!

    Questions?

    Slide 31