CO and brine flows in heterogeneous geologic …CO 2 and brine flows in heterogeneous geologic systems ANNA HERRING ARC DECRA POSTDOCTORAL FELLOW DEPT. APPLIED MATHEMATICS, RSPE AUSTRALIAN

CO2 and brine flows in heterogeneous geologic systemsANNA HERRING

ARC DECRA POSTDOCTORAL FELLOW

DEPT. APPL IED MATHEMATICS , RSPE

AUSTRAL IAN NATIONAL UNIVERS ITY

Geologic CO2 sequestration

Goals of this project● Understand & predict CO2 transport &

trapping ○ on short time scales (months – decades of

years)○ under varying injection parameters ○ in heterogeneous & anisotropic rocks

Image from Ruben Juanes, MIT

Use understanding of microscale physics to inform reservoir‐scale operations

X‐ray microCTmultiphase flow studies

High Pressure Flow Cell

Reservoir conditions• Pore pressure 1350 PSI• Temperature 50oC

Fluids• scCO2• KI‐doped water (“brine”)

Imaging Parameters• 120 kV, 60 mA• voxel size approx. 4 µm• Region of Interest acquisition• 12‐20 hrs acquisition time

Experimental Process1. Install dry rock core2. Saturate core with X‐ray attenuating brine3. scCO2 injection (25 pore volumes) 4. Chase brine injection (25 pore volumes)

video courtesy of Mohammad Saadatfar, ANU

36 mm

Ø = 12 mm

Reservoir sandstoneCoarse grained, layered

Reservoir sandstoneFine grained, layered

Quarry sandstonehomogenous




Dynamic Flow Patterns – scCO2 injectionReservoir sandstone

Coarse grained, layered





Trapped CO2 Distributions

X‐ray microCTmultiphase flow studies inform:Dynamic flow processes◦ Pressure and flow rate signals◦ 2D (radiograph) flow patterns over time◦ Fluid volume to achieve breakthrough, steady state

Quasi‐static (equilibrium) states◦ 3D Distribution, amount of CO2 after after CO2 injection◦ Stability of CO2 (how much CO2 remains trapped after forced injection of water?)◦ Microscopic information◦ interfacial area between water and CO2◦ contact angle (wettability)◦ fluid connectivity

Integration of CT experiments and pore network modeling

SimulationRockWaterCO2‐analogue

Øren, P. E., L. C. Ruspini, M. Saadatfar, R. M. Sok, M. Knackstedt, and A. Herring (2019), In‐situ pore‐scale imaging and image‐based modelling of capillary trapping for geological storage of CO2, Int. J. Greenh. Gas Control, 87, 34–43, doi:10.1016/J.IJGGC.2019.04.017.

ExperimentRockWaterCO2‐analogue



Expe

rimen

tSimulation


Pore network model


Allows for characterization of flow properties beyond experimental conditions:

• Capillary trapping curve• Relative permeability curves• Capillary pressure – saturation curves• Sensitivity to contact angle

Forecast

Continue integration of multiphase flow experiments and modelling◦ identify critical heterogeneous transition zones/layers◦ Investigate interplay between injection parameters (e.g. flow rate) and layers

Map these features throughout depth of core, incl. via larger scale imaging ‐ ANUCTLab‐Whole Core Scanner◦ 62mm core, 120 mm long, 28 μm voxels @ 140 kV

◦ compare to 12 mm core, 36 mm long, 4 μm voxels @ 120 kV microCT

Incorporate multi‐scale heterogeneity into large (reservoir scale) models and simulators

ANU CTLab‐Whole Core Scanner

Voxel = 28μmMedical CTVoxel = 195μm

Acknowledgements

Questions?

Co‐authors:M. Saadatfar, R.M. Sok, M. Knackstedt (ANU)P.E. Øren, L.C. Ruspini (Petricore Norway)

ARC Discovery Early Career Fellowship DE180100082

The authors wish to acknowledge financial assistance provided through Australian National Low Emissions Coal Research and Development (ANLEC R&D). ANLEC R&D is supported by COAL21 Ltd and the Australian Government through the Clean Energy Initiative.

Visualizations created with Drishti https://github.com/nci/drishti


ctlab.anu.edu.au

Documents

CO and brine flows in heterogeneous geologic …CO 2 and brine flows in heterogeneous geologic systems ANNA HERRING ARC DECRA POSTDOCTORAL FELLOW DEPT. APPLIED MATHEMATICS, RSPE AUSTRALIAN