Impact of Geological Heterogeneity on Early-Stage CO2Plume MigrationM. Ashraf1 K.A. Lie1 H.M. Nilsen1 A. Skorstad2

1Department of Applied Mathematics, SINTEF ICT, Oslo, Norway2Norwegian Computing Center, Norway. Present address: Roxar Software Solutions AS, Oslo, Norway

Summary

Academic studies of CO2 injection frequently employ simplified or conceptualized reservoirdescriptions in which the medium is considered nearly homogeneous. However, geologicalknowledge show that the medium can be expected to be heterogeneous on the relevant physicalscales, regardless of whether the target formation is an abandoned petroleum reservoir or apristine aquifer.

The main objectives of CO2 storage studies are to maximize the injection volume/rate and tominimize the risk of leakage [1, 2]. The motivation of this work is mainly to address twoquestions related to CO2 storage:I How sensitive is the injection and early-stage migration to uncertainty and variability in

the geological description?I What simplifying assumptions are allowed in averaging the geological attributes over

scales?

We use a subset of the synthetic models from the SAIGUP study to perform a preliminarysensitivity analysis for CO2 sequestration in aquifers.

SAIGUP Study

Within oil industry, the impact of geologicaluncertainty on production forecast has beenthoroughly investigated in the SAIGUP project[3, 4, 5] focusing on shallow-marine reservoirs. Tostudy different factors, synthetic realistic models weremade and several thousand cases were run fordifferent production scenarios. The results showedthat realistic heterogeneity in the structural andsedimentological description had a strong influenceon the production responses.

Geological Description

Lobosity

Lobosity is defined by the plan-view shape of the shore-line.In this study, we considered three variations for lobosity: flat,one-lobe and two-lobe shoreline shapes.

Geological space is characterized by fiveparameters:I Lobosity – flat, one-lobe, two-lobeI Barriers – low, medium, highI Aggradation – low, medium, and highI Progradation – up and downI Faults — open and closed

Faults

almost open almost closed

The upper plot shows the fault intensity and fault directions.Faults are modelled as either almost open or almost closed us-ing transmissibility multipliers. The corresponding flow pathsare shown in the two lower plots; with open faults, the flowpaths are predominantly in the up-dip direction, whereas forclosed faults, they spread out more laterally.

Barriers

Periodic floods result in mud-draped surfaces which are po-tential significant barriers to both horizontal and verticalflow. We consider three levels: low, medium, and high.

Progradation

Progradation is the depositional-dip direction, or the direc-tion of flow from the river into the sea. Two types are con-sidered here: up and down the dominant structural dip.

Aggradation

The angle at which the transitional deposits are stackedon each-other, is called aggradation angle. Three levels ofaggradation are modelled here: low, medium and high.

Injection Scenario

We are using an injector down in the flank and hydrostaticboundary conditions on the sides, except the faulted sideon the crest. No-flow boundary conditions are imposed on the topand bottom surfaces of the model. The well is completed only inthe lowermost three layers. About 40MM m3 of supercritical CO2

is injected for thirty years, which amounts to 20% of the models’pore volumes. After the injection period, seventy years of early plume migration is simulated.

Important Responses

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54

10

20

30

40

50

60

70

Cases

End O

f S

imula

tion

Total Number Of CO2 Plumes,

Reservoir pressure: The pressure responsein general shows a sharp jump at the start ofinjection and a declining trend during theinjection and plume migration.

Boundary fluxes: The flux through theopen boundaries is a measure of the sweepefficiency of the CO2 plume.

Total mobile/residual CO2: Less mobileCO2 means less risk of leakage and moreresidual volumes (with saturations less thanthe critical). This is related to the efficiencyof the volume sweep.

Connected CO2 volumes: We looked atthe largest plume size, the number of plumes,and other statistical parameters.

Response Correlations

0 1000 2000 3000 4000 5000 60000

1

2

3

4

5

6

7

8x 10

5

Down Boundary CO2 FLux

Tot

al R

esid

ual C

O2 V

olum

e

End Of Injection

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

x 106

0

10

20

30

40

50

60

70

80

Total Residual CO2 Volume

Tot

al N

umbe

r O

f CO

2 Plu

mes

End Of Simulation

We relate the responses by plotting them against each other. This helps in understanding thedegree of correlations between the responses.

Sensitivity Analysis

We define a gradient for each of the five geological features to quantify the sensitivity of flowresponses. (This is done by computing average flow responses for each feature value and thenfitting a line through the averages to define an averaged slope).

Average aquifer pressure

Progradation

Aggradation

Barrier

Lobosity

Fault

End of injection End of simulation

Progradation

Aggradation

Barrier

Lobosity

Fault

During the injection phase, the flow is

dictated by viscous forces imposed by

the injector, and aggredation is the

most influential parameter. After the

injection period, the dominating force

is gravity, and the flow is now most

sensitive to whether the faults are

open or closed.

Number of CO2 plumesEnd of injection

Progradation

Aggradation

Barrier

Lobosity

Fault

End of simulation

Progradation

Aggradation

Barrier

Lobosity

Fault

During injection, barriers enhance the

lateral flow and the plume splits rather

than accumulating in the crest. After

injection, progradation plays a

relatively important role. The open

faults are introducing large number of

plumes, while the unfaulted and closed

faulted cases introduce small number

of plumes, which in average cancels

out to a low gradient.

Conclusion

We have demonstrated that different geological parameters can have a different impact on theCO2 migration during injection and during the later migration. In particular, our results highlighthow variation in aggradation, fault criteria and barriers significantly change the flow directionwithin the medium. Therefore we believe that effort should be put into detailed geologicalmodelling of potential injection sites. This way, one can better balance the influence ofsimplifications made in the models of geology and flow physics.

References[1] J. M. Nordbotten: Sequestration of Carbon in Saline Aquifers: Mathematical and Numerical Analysis, Doctor Scientiarum Thesis, Department of

Mathematics, University of Bergen, (2004).

[2] S. Bachu: CO2 storage in geological media: Role, means, status and barriers to deployment, Progress in Energy and Combustion Science,ELSEVIER, (2008).

[3] J. A. Howell, A. Skorstad, A. MacDonald, A. Fordham, S. Flint, B. Fjellvoll, and T. Manzocchi: Sedimentological parameterization of shallow-marinereservoirs, Petroleum Geoscience, 14 (1), pp. 17-34, (2008).

[4] T. Manzocchi, J. N. Carter, A. Skorstad, B. Fjellvoll, K. D. Stephen, J. A. Howell, J. D. Matthews, J. J. Walsh, M. Nepveu, C. Bos, J. Cole, P.Egberts, S. Flint, C. Hern, L. Holden, H. Hovland, H. Jackson, O. Kolbjørnsen, A. MacDonald, P. A. R. Nell, K. Onyeagoro, J. Strand, A. R.Syversveen, A. Tchistiakov, C. Yang, G. Yielding, and R. W. Zimmerman: Sensitivity of the impact of geological uncertainty on production fromfaulted and unfaulted shallow-marine oil reservoirs: objectives and methods, Petroleum Geoscience, 14 (1), pp. 3-15, (2008).

[5] J. D. Matthews, J. N. Carter, K. D. Stephen, R. W. Zimmerman, A. Skorstad, T. Manzocchi, and J. A. Howell: Assessing the effect of geologicaluncertainty on recovery estimates in shallow-marine reservoirs: the application of reservoir engineering to the SAIGUP project, Petroleum Geoscience,14 (1), pp. 33-44, (2008).

[6] S. E. Gasda, J. M. Nordbotten, and M. A. Celia: Vertical equilibrium with sub-scale analytical methods for geological CO2 sequestration,Computational Geosciences, 13 (4), pp. 469-481, (2009).

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http://www.sintef.no/MatMorA Arne.Skorstad@roxar.com