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Flow Properties of Marcellus Shale and Gas09122-04Presenter Name: Roland N. Horne and Maytham Al IsmailOrganization Name: Stanford University

Meeting Name: Review WorkshopMeeting Date: 29 May 2013Meeting Location: Pittsburgh

rpsea.org

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Contacts

PI: Roland N. HorneStanford Universityhorne@stanford.edu(650)723-9595

RPSEA PM: NameEmail AddressPhone Number

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Outline

o Objectiveso Backgroundo Core analysis

• Computerized tomography (CT) scans• Water imbibition test• Permeability

o PVT analysis of natural gaso Sandstone core flooding with binary gas o Sandstone core flooding with Marcellus gaso Shale core flooding with Marcellus gaso Conclusions

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Objective

o Characterize Marcellus shale core sampleso Conduct core flooding experiments to demonstrate how gas-

condensate composition varies during depletiono Gain better understanding of how condensate blocking affects shale

gas wells productivity

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Background

(Fan et al. 2005)

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Background

(Shi 2009)

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Background

(Shi 2009)

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Background

(Vo 2010)

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Core samples

Sample # 1

Sample # 2

Sample # 3

Sample # 4

Berea sandstone

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CT scans

o X-ray attenuation for core sample 1, 2 and 3

o Variation in CT number is caused by variation in densities (rock heterogeneity)

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CT scans

o Type of heterogeneity is inclusionso Inclusions are nonplanar zones that have higher bulk densities

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CT scans

o Sample 4 heterogeneity is further exacerbated by microfractureso CT number fluctuates

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Water imbibition test

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Water imbibition test

o Sample 3 was used: Vb = 498 cco Imbibed water: Mwater = 11.68 g Vwater = 11.68 cco > 2.34%

0

20

40

60

80

100

0 200 400 600 800 1000 1200 1400

Wat

er im

bibe

d, g

Time, hour

Before calibration

After calibration

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Permeability

Measurement techniques

o Darcy flow technique• Berea sandstone core

o Pressure pulse decay technique• Marcellus shale core (sample # 4)

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Permeability

Berea sandstoneo Darcy flow technique

o N2 gas

o

o k vs. 1/pmean

o Absolute permeability = 105 md

This image cannot currently be displayed.

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Permeability

Marcellus shale

o Pressure pulse decay technique:• Permeability• Effective stress law

o 1-in diameter core obtained from sample # 4

o Helium gas(Vermylen, 2011)

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Permeability

Marcellus shale

o Example:• Ppore = 1,010 psi• Ppulse = 25 psi• Peffective = 1,000 psi

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Permeability

Marcellus shaleo Braceetal. 1968 :

∆ ∆

ln∆∆

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Permeability

Marcellus shaleo Observations:

• Permeability = 63 nD• Permeability reduction at

increased effective stress Example (Pp = 1,000 psi):

k (σeff = 1,000 psi) = 63 ndk (σeff = 5,000 psi) = 25 nd

Note: some data points were collected from Heller and Zoback (2012)

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Permeability

Marcellus shaleo Effective stress law (kwon et al., 2001):

log

log 0.42

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Permeability

1 1 1

(Kwon et al. 2001)

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Permeability

Summary

o Berea sandstone:• Darcy flow technique• k = 105 md

o Marcellus shale:• Pressure pulse decay technique• k = 63 nd• = 0.42

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PVT Analysis

o Fluid components: 10 well-defined components and one pseudocomponent (C7+)

o pres = 3,481 psio Tres = 138 oFo pdew = 3,085 psi

ComponentSeparator Gas

Mol%Separator Liquid

Mol%Well Stream

Mol%

N2 0.473 0.112 0.437

CO2 0.09 0.014 0.082

H2S 0 0 0

C1 71.386 6.604 64.914

C2 17.346 8.192 16.431

C3 6.983 10.517 7.336

iC4 0.71 2.242 0.863

nC4 1.919 8.841 2.611

iC5 0.329 3.654 0.661

nC5 0.447 7.902 1.192

C6 0.211 10.183 1.207

C7+ 0.106 41.739 4.266Total 100 100 100

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PVT Analysis

Pupstream = 3,050 psi

Temp = 138 oF

Critical PointExperimental pressure range

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PVT Analysis

o Constant volume depletion (CVD) experiment

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

1000 1500 2000 2500 3000 3500

Cond

ensate Saturation, %

Pressure, psi

Observed

Calculated

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PVT Analysis

o Constant composition expansion (CCE) experiment

0

0.5

1

1.5

2

2.5

3

3.5

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Relativ

e Vo

lume, V/V

sat

Pressure, psi

Observed

Calculated

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PVT Analysis

o Flash to separator conditions calculations

0

10

20

30

40

50

60

70

80

N2 CO2 C1 C2 C3 IC4 NC4 IC5 NC5 C6 C7+

Mole %

Separator Gas

Observed

Calculated

0

5

10

15

20

25

30

35

40

45

N2 CO2 C1 C2 C3 IC4 NC4 IC5 NC5 C6 C7+

Mole %

Separator Liquid

Observed

Calculated

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Sandstone with binary gas

gas

(Shi 2009)

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o Apparatus was tested on Berea sandstoneo C1-nC4 gas mixture was usedo Samples were analyzed by gas chromatography

Sandstone with binary gas

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Sandstone with binary gas

o Noncapture experiment: samples were collected while fluid was flowing

o With increasing pressure drop, condensate dropped and the mixture became lighter (less nC4 conc)

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5 6

nC4, %

Sample Points

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Sandstone with binary gas

o Capture experiment: samples were collected twice, while:o Gas is flowing through the coreo Gas is captured in the core

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 6 7 8

nC4, %

Sample Points

Flowing

Noflow

Cylinder Discharge

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Sandstone with Marcellus gas

o Apparatus was modified to allow for temperature control

o Actual gas mixture was usedo Samples were analyzed by gas

chromatography

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Sandstone with Marcellus gas

o Samples were collected while fluid was flowingo With increasing pressure drop, condensate dropped and the mixture

became lighter (less C3 conc)

0

0.5

1

1.5

2

2.5

3

3.5

0 1 2 3 4 5 6 7

Prop

ane

Mol

e %

Ports

Flowing Experiment Initial

`

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Shale with Marcellus gas

o A 2-in diameter core has been cut to be loaded into the core holder

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Shale with Marcellus gas

DS sample 1 DS sample 2

US sample 1 US valve closed

Ports sample 1

Ports sample 2

Ports sample 3

US sample 2

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Shale with Marcellus gas

o C3, iC4 and nC4 concentrations were monitored o Similar to sandstone core, with increasing pressure drop, condensate

dropped and the mixture became lighter

1 2 3 4

Tempsensor

Discharge fromDS

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Shale with Marcellus gas

1 2 4

Upstream p = 1,520 psi

Upstream p = 755 psi

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Conclusions

o The Marcellus core used in this experiment showed low porosity and low permeability (nanodarcy scale)

o Condensate dropout was observed in the sandstone flooding with binary (C1-nC4) gas mixture

o Condensate dropout was observed in the sandstone and shale flooding with Marcellus gas mixture

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Backup Slides

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Thermodynamics and Phase Behavior

Pore size implicationso Shift of fluid thermodynamic properties due to confinement:

• Critical properties • Capillary pressure• Density• Viscosity

o Hence, the fluid phase behavior changes, specifically, the dew point pressure and the bubble point pressure

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Thermodynamics and Phase Behavior

Critical properties

o Based on Van der Waals model:• Zarragoicoechea and Kuz (2004):

0.9409 0.2415

2 2

(Zarragoicoechea and Kuz, 1997)

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Thermodynamics and Phase Behavior

Methane-butane phase behavior

o ⇒ rp = 4 nmo Tcp and Pcp are calculated

based on Singh et al. (2009)

Component Bulk Tc, K Pore Tcp, K Bulk Pc, atm Pore Pcp, atmC1 190.6 182.3 45.4 50.7

nC4 425.2 400.2 37.5 46.00

500

1000

1500

2000

2500

‐300 ‐200 ‐100 0 100 200

Pressure, p

si

Temperature, oF

Phase diagram of binary mixture

Bulk Mixture

Pore Mixture

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Thermodynamics and Phase Behavior

Methane-butane mixture/Marcellus shale

o Coreflooding experiment• PUS = 2,000 psi• PDS = 1,400 psi

o Preliminary results: condensate saturation is overestimated for bulk properties

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Thermodynamics and Phase Behavior

Capillary pressureo For bulk fluids, pv = pL, therefore, pc = 0

o For confined fluids, pv ≠ pL

• Young-Laplace equation:

2

• Macleod and Sugden correlation: ∑

• Literature review indicated a shift in the phase diagram. However, this wasn’t coupled with the investigations of critical properties

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Molecular Simulation

Grand canonical Monte Carlo (GCMC)o Monte Carlo: computational algorithm that rely on repeated random

samplingo It will be used to compute the equilibrium and adsorption properties

of vapor-liquid multicomponent hydrocarbonso GCMC:

• Temperature, volume and chemical potential are fixed• Number of particles is allowed to fluctuate • Useful for:

1. EOS for Lennard-Jones fluid2. Adsorption isotherms investigations

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Molecular Simulation

Grand canonical Monte Carlo (GCMC)

o MUSIC software will be utilized:• Multipurpose Simulation Code

o Investigate the effect of pore size on phase behavior and adsorption isotherms

o 3D snapshots at 298 K in a 2-nm pore (Mosher et al., 2012):• Red: surface carbon atoms• Blue: methane molecules

o Able to estimate density; difficult experimentally

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Approach:• Field scale discrete fracture network modeling of hydraulic stimulation gas shale.• Includes propagation of new fractures and opening and slip of preexisting fractures.• Fluid flow, stresses induced by fracture opening and sliding, transmissivity coupling

Applications:• Investigation of fundamental mechanisms• Stimulation design and optimization• Formation evaluation

Simulation of Fracturing - McClure

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GC Calibration

o The GC was calibrated with a natural gas mixtureo The GC is able to identify peaks up to nC4o A good match is achieved between GC readings and calibration gas

composition

0

10

20

30

40

50

60

70

80

N2 CO2 C1 C2 C3 iC4 nC4

Calibration Gas

GC Results

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Simulations of shale withMarcellus gas

o Gas injection into the coreo pinj = 210 atm = 3,085 psio Requires more than 70 hours to saturate the 6.5 in shale core

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Simulations of shale withMarcellus gas

o Gas discharge from the core (scenario 1)o pinj = 210 atm = 3,085 psio pprod = 135 atm = 2,000 psi

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Simulations of shale withMarcellus gas

o Gas discharge from the core (scenario 2)o No injector (upstream valve is closed)o pprod = 135 atm = 2,000 psi