Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Yifeng Wang, Yongliang Xiong, Louise Criscenti, Tuan Anh Ho, Philippe Weck, Edward Matteo, Jessica Kruichak

Sandia National Laboratories, Albuquerque, New Mexico

Fundamental Understanding of Methane-Carbon Dioxide-Water (CH4-CO2-H2O) Interactions in Shale Nanopores under Reservoir Conditions

Acknowledgments DOE NETL for financial support Bruce Brown, Adam Tew, Joe Renk, Henry Stephen, Jared

Ciferno, (NETL) for management support MSEEL for shale samples Mei Ding (LANL) for neutron scattering experiments

2

Shale gas production: A multi-scale problem

SPE 124253 (2009)

JCPT 46, 55 -61 (2007)

Kerogen

1.0E-13

1.0E-11

1.0E-09

1.0E-07

1.0E-05

1.0E-03

1.0E-01

1 10 100 1000f(

r) (n

m-1

)

Pore radius (r) (nm)

Fractal distribution

Barnett Shale

Nanopore confinement and emergent properties

Bulk phase fluids (Unconfined or pore size >

~100 nm)

EOS = f(P, T, composition)

Nanofluids(Confined in nanopores, pore

size < ~100 nm)

EOS = f(P, T, composition, pore size, surface chemistry)

Nanoconfinement

0

0.1

0.2

0.3

0.4

0.5

0 0.1 0.2 0.3 0.4 0.5(T

c-Tcp

)/T c

σ/rp

Ar

Ar

O2

Xe

CO2

CO2

C2H4

N2

Wang (2014); Zarragoicoechea and Kuz (2004)

Akkutlu, 2013

Overall goal: (1) Obtain a fundamental understanding of CH4-CO2-H2O (or other fluid component) interactions in shale nanopores under high-pressure and high temperature reservoir conditions, and (2) integrate this understanding into reservoir engineering for efficient resource recovery and subsurface carbon sequestration.

Capabilities for Nanogeochemical Studies at Sandia National Laboratories

Gas disposition & release• Gas in place (GIP)• Gas migration from matrix

into fractures• Stimulated volume• Gas for secondary recovery

Material characterization• Pore structures: SANS, BET,

TEM, SEM, etc• Chemistry & mineralogy: XRD,

XRF, etc

Sorption/desorption measurements• Methane sorption/desorption

on model materials• Methane sorption/desorption

under high P & high T• Chemical/physical

stimulations

Field observations• Core/outcrop sample

collection• Quantification of

heterogeneities

Column experiments• Diffusive fluxes• Advective fluxes

Nanoscience• Effects of nanopore

confinement on fluid thermodynamic properties

• Effects of nanoporeconfinement on methane transport (microfluidics in shale)

Molecular dynamic (MD) modeling• Binding energies of methane

sorption• Diffusion rates

Upscaling• Percolation theory• Fractal representation• Lattice Boltzmann modeling

Predictive models• Constitutive relationships• Continuum models• Reactive transport modeling

Synthesis of nanoporousmaterials

Isolation of kerogen from Mancos shale Density functional theory (DFT)

modeling

High pressure/high temperature sorption/desorption measurements

TRAMANTO: Classical Density Functional Theory

http://www.pflotran.org/applications.html

PFLOTRAN: Reactive transport modeling

Pore structure characterization

Pioneering work in nanogeochemistry. Access to DOE Center of Integrated Nanotechnology

Pore structure characterization (FIB)

Material preparation & characterization

About 10 shale core samples obtained Focus on Mancos, Marcellus &

Woodford

Pure kerogen isolated from Mancos, Woodford & Marcellus shale

About 5 model materials synthesized or purchased

Major material characterization completed (BET, SANS, FTIR)

Synthesis of nanoporousmaterials

Gas sorption measurements

Model Substances Temp, oC Gas Mixture, volume percent Pressure, PSI Sorption Capacity (mixture)

mg/g

Sorption Rate,

mg/g min-1

Illite, <75 mm 50 90% CH4 + 10% CO2 300 190 1.5

Kerogen

8

DensitySample 1: 1.172g/cm3

Sample 2: 1.287g/cm3

Average :1.22±0.04 g/cm3

Experiment: 1.28±0.3g/cm3

Stankiewicz A, et al. (2015) Kerogen density revisited –lessons from the Duvernay Shale. In: Paper URTeC2157904 at the Unconventional Resources Technology Conference, San Antonio, Texas, July 2015

Pore size distribution

Pore Diameter (Å)0 2 4 6 8 10 12 14 16

Prop

abili

ty D

ensi

ty0.0

0.2

0.4

0.6

0.8

1.0

1.2

21

Method: Bhattacharya S & Gubbins KE (2006) Langmuir 22:7726-7731 AAPG 96 (2012), 1099-1119

Over-mature kerogen molecules

Ho et al, Scientific Reports 28053

Methane sorption and extraction from kerogen

Time (ps)0 200 400 600 800 1000Ex

trac

tion

rate

(# m

olec

ules

/ps)

0.0

0.2

0.4

0.6

0.8

1.0

Pres

sure

(atm

)

0

50

100

150

200

250

47% 50%Sample 1

Sample 2 30% 35% 35%

Fast Slow Unrecoverable

Pressure (atm)0 50 100 150 200 250 300

Tota

l upt

ake

(mm

ol/g

)

0

1

2

3

4

CO2CH4

10

Gas adsorption Scenario 1: Pure CH4 and pure CO2

Pressure (atm)0 50 100 150 200 250 300

Tota

l upt

ake

(mm

ol/g

)

0

1

2

3

4

5

CO2

CH4

Scenario 2: 1:1 binary mixture CH4 and CO2

Pore specific effects on enhanced gas recovery

11

CH4

CO2

0.814 nm CNTPore is too small for the invasion of CO2

1.085 nm CNTPore is big enough for the invasion of CO2

Pore size effect

Pore specific effects on enhanced gas recovery

12

Water effect

Assume that water thin films block the pore entrance.

CO2 invades through water and replaces CH4 in the nanopore.

Model Molecular Structure of kerogen

Ungerer et al. (2015)

Weck et al, Scientific Reports (2017)

Kerogen Models

Comparison of DFT results with measurements

Activated carbon: pH titration, surface functional groups, gas sorption and metal sorption and release

Wang et al. (2007)

New kerogen models?

17

Bousige et al. (2016)

New structural models

Nanoconfinement & emergent transport properties

Slip flow Knudsen diffusion

𝑘𝑘𝑎𝑎𝑎𝑎𝑎𝑎 = 2𝑟𝑟3𝑅𝑅𝑅𝑅

8𝑅𝑅𝑅𝑅𝜋𝜋𝜋𝜋

1/2+ 1 + 8𝜋𝜋𝑅𝑅𝑅𝑅

𝜋𝜋

1/2 𝜇𝜇𝑎𝑎𝑟𝑟

2𝛼𝛼− 1 𝑐𝑐𝑟𝑟2

8𝜇𝜇

SPE 124253 (2009)

Conventional reservoir

Shale formation

M - Molecular weight

Mass dependent transport

Wang (2017)

Nanoconfinement & emergent transport properties: isotope fractionation Chemical species confined in

nanopores behave differently from those in a bulk system.

Interaction of chemical species with pore surfaces is much enhanced due to a high surface/fluid volume ratio.

Nano-confinement also manifests the discrete nature of fluid molecules in transport, therefore enhancing mass-dependent isotope fractionations.

All these effects combined lead to a distinct set of tracer signatures that may not be observed in a conventional hydrocarbon reservoir or highly permeable groundwater aquifer system.

-10.2

-10.0

-9.8

-9.6

-9.4

-9.2

-9.0

-8.8

-8.6

-8.4

0 50 100 150 200

δ18O

(‰)

Total filtrate (ml)

Residual solution

Filtrate

Isot

ope

frac

tiona

tion

Data from Coplen & Hanshaw (1973)

Isotope fractionation of water by ultrafiltration across a compacted clay membrane (Coplen and Hanshaw, 1973)

-70

-65

-60

-55

-50

-45

-40

-35

-30

-25

-20

-10 -9 -8 -7 -6 -5 -4δ

D (

‰)

δ18O (‰)

Waters extracted from Opallinus Clay at Benken (Switzerland) (Mazurek et al., 2009)

Wang (2017)

Chaotic behavior of gas migration in compacted clay

FORGE Report D4.17 (Harrington, 2013)

Bubble migration under a pressure gradient

𝜆𝜆1 =𝑘𝑘𝑢𝑢0𝑃𝑃𝑢𝑢 + 𝑘𝑘𝑑𝑑0𝑃𝑃𝑑𝑑 𝑅𝑅𝑅𝑅

𝑉𝑉 𝜆𝜆2 =𝑘𝑘𝑢𝑢0 + 𝑘𝑘𝑑𝑑0 𝑅𝑅𝑅𝑅

𝑉𝑉𝐾𝐾 =

𝜆𝜆1𝜆𝜆2

𝑑𝑑𝑃𝑃𝑑𝑑𝑑𝑑

= 𝜆𝜆1 1 −𝑃𝑃𝐾𝐾

�−∞

𝑡𝑡𝛼𝛼𝑒𝑒 )−𝛼𝛼(𝑡𝑡−𝑠𝑠 𝑝𝑝 𝑠𝑠 𝑑𝑑𝑠𝑠

𝑑𝑑𝑃𝑃𝑑𝑑𝑑𝑑

= 𝜆𝜆1 1 −𝑃𝑃𝐾𝐾

�−∞

𝑡𝑡𝐺𝐺 𝑑𝑑 − 𝑠𝑠 𝑝𝑝 𝑠𝑠 𝑑𝑑𝑠𝑠

Delay logistic equation

M P V

Dilated zone

𝑘𝑘𝑢𝑢𝑘𝑘𝑑𝑑

𝑃𝑃𝑢𝑢 𝑃𝑃𝑑𝑑

Fracture healingFracture opening

)𝑝𝑝𝑛𝑛+1 = 𝜆𝜆𝑝𝑝𝑛𝑛(1 − 𝑝𝑝𝑛𝑛

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97

P

n

λ = 2.5 3.2 3.6

0.0E+002.0E-094.0E-096.0E-098.0E-091.0E-081.2E-081.4E-081.6E-081.8E-08

66 67 68 69 70 71 72

Out

flow

Day

Logistic map

Chaotic behavior of well production?

22

https://www.shaletec.com/files/Production-below-decline-curve.png

Future work Performing additional high pressure and high temperature sorption

measurements on crushed shale samples. Perform sorption measurements more on multicomponent systems to clarify the

interactions among different components (CH4-CO2-H2O). Develop new structural models for kerogen that correctly account for both atom

correlations and functional group distributions. Understand the effects of surface functional groups on gas sorption and release in

kerogen. Perform MD (or MC) simulations for understanding CH4-CO2-H2O interactions in

nanoporous clay matrix. Extend the research to include other hydrocarbon components. Develop a nanofluidic model for gas transport and isotope fractionation in shale. Based on the existing experimental and modeling results to formulate new gas

disposition and release model for well-borehole production. Collaboration on kerogen study: Schlumberger, MIT

23