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INFLUENCE OF CAPILLARY PRESSURE ON CO 2 STORAGE AND MONITORING Juan E. Santos Work in collaboration with: G. B. Savioli (IGPUBA), L. A. Macias (IGPUBA),

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Presentation on theme: "INFLUENCE OF CAPILLARY PRESSURE ON CO 2 STORAGE AND MONITORING Juan E. Santos Work in collaboration with: G. B. Savioli (IGPUBA), L. A. Macias (IGPUBA),"— Presentation transcript:

1 INFLUENCE OF CAPILLARY PRESSURE ON CO 2 STORAGE AND MONITORING Juan E. Santos Work in collaboration with: G. B. Savioli (IGPUBA), L. A. Macias (IGPUBA), J. M. Carcione and D.Gei ((OGS) Trieste, Italy) Purdue University and Instituto del Gas y del Petróleo de la Univ. de Buenos Aires (IGPUBA), Argentina and Univ. Nac. de La Plata

2 Introduction. I  CO 2 sequestration in suitable geological formations is one of the solutions to mitigate the greenhouse effect.  Saline aquifers are suitable as storage sites due to their large volume and their common occurrence in nature.  Numerical modeling of CO 2 injection and seismic monitoring are important tools to understand the long term behavior after injection and to test the effectiveness of CO 2 sequestration.

3 Introduction. II The first industrial CO 2 injection project started in 1996 is at the Sleipner gas field in Norway. The CO 2 separated from natural gas is being injected in a saline aquifer, the Utsira formation a high permeable sandstone with several mudstone layers that limit the vertical motion of the CO 2 From:

4 Introduction. III  We introduce a numerical procedure combining simulations of: CO 2 injection and storage in saline aquifers. Seismic monitoring of CO 2 migration in the subsurface.  The multiphase flow functions (relative permeability and capillary pressure relations) are determined from on-site resistivity measurements.  In particular we analyze the sensitivity of the spatial distribution of CO 2 and their seismic images due to capillary pressure variations.

5 1. Black-Oil simulator to model CO 2 injection and storage. 2. Seismic monitoring using a viscoelastic model formulated in the space-frequency domain that includes mesoscopic-scale attenuation and dispersion effects. Multiphase Flow Functions A model to update the petrophysical properties Methodology

6 Mass conservation equation The Black-Oil formulation Darcy’s Empirical Law

7 The numerical solution was obtained employing the public domain software BOAST. BOAST solves the flow differential equations using IMPES (IMplicit Pressure Explicit Saturation), a finite difference technique. The basic idea of IMPES is to obtain a single equation for the brine pressure by a combination of the flow equations. The system is linearized evaluating k r and P C at the saturations of the previous time step. Once pressure is implicitly computed for the new time step, saturation is updated explicitly. The Black-Oil formulation - BOAST

8 Multiphase Flow Functions – Resistivity Index Using the log data and the conductivity relation (Carcione et. al. JPSE, 2012): from logs Then: at Utsira The multiphase flow functions were obtained from the Resistivity Index (RI)

9 Multiphase Flow Functions – Relative Permeability Curves Relative permeability curves are obtained from RI(S b ):

10 Multiphase Flow Functions – Capillary Pressure Curve

11 A Model to update the Petrophysical properties Carcione’s model (Carcione et.al., IJRMMS, 2003)

12 Seismic Modeling – Mesoscopic Attenuation Effects Within the Utsira formation and outside the mudstone layers, we determine the complex and frequency dependent P-wave modulus at the mesoscale using White’s theory for patchy saturation.

13 Seismic Modeling – Constitutive Relations

14 Seismic Modeling – Phase Velocities and Attenuation coefficients

15 Seismic Modeling – A Viscoelastic Model for Wave Propagation

16 Finite Element Method

17 0,4 km depth 1,2 km length 10 km thickness Fractal Initial Porosity Fractal Initial Permeability Low Permeability Mudstones 2,5D model Aquifer Model Utsira formation From:

18 Initial Vertical Permeability Distribution [mD] Aquifer Model – Initial Vertical Permeability Within the formation there are several mudstone layers which act as barriers to the vertical motion of the CO 2.

19 Sensitivity analysis - saturation maps after 3 years of injection Pce=5kPaPce=200kPa

20 Pce=5kPaPce=200kPa QpQp vpvp Sensitivity analysis – Q p and v p after 3 years of injection

21 Pce=5kPaPce=200kPa Distance (m) Time (s) Distance (m) Time (s) Sensitivity analysis – synthetic seismograms after 3 years of injection

22 Saturation maps up to 7 years of injection Pce=200kPa

23 Synthetic seismogram after 7 years of injection Pce=200kPa Real seismogram Distance (m) Time (s) 50ms 0 50 Time-lag (ms) Chadwick et. al., BGS, (2004)

24 Conclusions The fluid-flow simulator yields CO 2 accumulations below the mudstone layers and the corresponding synthetic seismograms resemble the real data, where the pushdown effect is clearly observed. Capillary forces affect the migration and dispersal of the CO 2 plume; higher values of the threshold capillary pressure Pce cause slower CO 2 upward migration and thicker zones of CO 2 accumulations. Variations in capillary forces induce noticeable changes in the seismic images of the Utsira formation, clearly seen in the synthetic seismograms.

25 THANKS FOR YOUR ATTENTION


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