Passive seismic analysis for reservoir monitoring

1. Passive seismic analysis for reservoir monitoring September 24, 2010 Capo Caccia, Sardinia, Italy D. Gei, L. Eisner, P. Suhadolc

2. Outline • Hydraulic stimulation of reservoirs • Passive seismic monitoring • Surface star array data: some examples • Focal mechanism inversion of microseismic events • P-wave traveltime inversion for VTI media

3. Hydraulic stimulation of reservoirs Hydraulic stimulation is a technique to induce fractures in hydrocarbon and geothermal reservoirs. • It is injection of fluids under high pressure in order to overcome minimum stress and open a hydraulic fractures, either by opening existing fractures or producing new ones. • It increases the permeability of the rock from microdarcy to millidarcy range. • The fluid injected into the formation is typically composed of brine (95%), additives, proppant (e.g. resin-coated sand, ceramic materials). • The stimulated volume can extend several hundred meters around the well. The dimensions, extent, and geometry of the induced fractures are controlled by pump rate, pressure, and viscosity of the fracturing fluid. • Reservoir hydraulic stimulations usually induce (significant) microseismic activity.

4. Stage 2 Stage 1 Low permeability, hydrocarbon-rich formation Perforation shots Perforation shots Perforation shots serve to connect wellbore and formation through opening in casing Heel Toe (picture after API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, First Edition, October 2009)

5. Fluid injection Stage 2 Stage 1 Microseismic events Hydraulic stimulation (picture after API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, Fisrt Edition, October 2009)

6. Passive seismic for reservoir monitoring Passive seismic monitoring of reservoirs consists in “listening” to the subsoil during oilfield operations (e.g. production, hydraulic stimulation, CO2 injection). Location of events and clustering Map fracture system Cap rock integrity Fault mapping (reservoir compartmentalization) Focal mechanisms Anisotropy analysis (P and S waves) Fracture characterization Fracture orientation Fracture density and aspect ratio

7. > source depth Depth (kft) Receivers Microseisms Treatment wells Northing (kft) (from Warpinski, 2009) Easting (kft) Microseismic signals can be recorded by downhole sensors or surface star arrays of receivers. Monitoring well Treatment well ~300 m Vertical array of 3C geophones (8-12 receivers) in a monitoring well. Hundreds of receivers disposed in a star shaped array

8. Hmax Treatment well (deviated) (picture from www.microseismic.com)

9. Microseismic event 1 Perforation shot Data example

10. Microseismic event 1 Lines 1 - 10 Processing performed Bandpass freq filter (2,7,60,70) Hz Agc for visualization

11. Polarity flip Polarity flip Polarity flip Polarity flip Microseismic event 1 Lines 1 - 10 Processing performed Bandpass freq filter (2,7,60,70) Hz Agc for visualization

12. Red line: frequency peak of the spectrum for each seismic trace Microseismic event 1: frequency analysis of the seismic signals Data from line 10 (1C) Raw data Time window width: 0.032 s Line 10 Line 10 Polarity flip  source location

13. Perforation shot

14. Well head Receivers Perforation shot Perforation shot Direct arrivals from the perforation shot Direct waves from the well head Surface waves from the well head

15. Focal mechanisms

16. Focal mechanisms: event 1 OK Focal mechanism: oblique dip-slip fault

17. Focal mechanisms: event 6 Focal mechanism: strike slip fault

18. Vertical Transverse Isotropy (polar anisotropy) Anisotropic material: properties (e.g. seismic velocities) depend on direction. Vertical transverse isotropy can be related to fine layering in sedimentary basins or to shales. 5 independent elasticity constants (c11, c33, c44, c66, c13) Thomsen parameters (weak anisotropy)

19. Experimental traveltimes •Computed traveltimes (t0=-0.005 =0.1 =-0.1 ) •Computed traveltimes (t0=0.007 =0.2 =0.3 ) •Computed traveltimes (t0=0 =0.1 =0.22 ) * P-wave traveltime inversion for homogeneous VTI media , , VP0 picked arrival time origin time one-way vertical traveltime P-wave velocity // symmetry axis offset (horizontal projection of source-receiver distance) normal moveout velocity Anellipticity (Alkhalifah and Tsvankin, 1995)

20. Perforation shot P-wave traveltime inversion of perforation shot data P-wave velocity profile

21. P-wave traveltime inversion of perforation shot data Traveltimes from experimental data (layered anisotropic ? medium) Traveltimes from synthetic data (ray tracing - isotropic layered medium) Effective velocity for traveltime inversion ,  , 

22. Picked arrival times Time (s) Time residuals P-wave traveltime inversion from experimental data Experimental data Inversion results: vti t0 = -0.244 s = 0.2734, 0.1172 RMS4.0 ms Experimental and theoretical traveltimes - Line 1

23. P-wave traveltime inversion from synthetic data Picked arrival times Synthetic data Inversion results: VTI t0 = -0.001s = 0.1217, 0.0148 RMS1.1 ms Time (s) Synthetic and theoretical traveltimes - Line 1 Time residuals

24. P-wave traveltime inversion from synthetic data Picked arrival times Synthetic data Inversion results: VTI t0 = -0.001s = 0.1217, 0.0148 RMS1.1 ms Experimental data Inversion results: VTI t0 = -0.244 s = 0.2734, 0.1172 RMS4.0 ms Time (s) Synthetic and theoretical traveltimes - Line 1 Time residuals

25. Conclusions This dataset is characterized by non-unique focal mechanism The reservoir and/or the overburden are affected by polar anisotropy

26. Bibliography Alkhalifah, T., and I. Tsvankin, 1995, Velocity analysis for transversely isotropic media: Geophysics, 60, 1550-1566. API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, First Edition, October 2009 (http://www.gwpc.org/e-library/documents/general/APi%20Hydraulic%20Fracturing%20Guidance%20Document.pdf) Fischer, T., Hainzl, S., Eisner, L., Shapiro, S.A. and Le Calvez, J., 2008a, Microseismic signatures of hydraulic fracture growth in sediment formations: observations and modeling. Jour. Geoph. Res., 113, B02307, doi:10.1029/2007JB005070. Grechka, V., 2009, Applications of seismic anisotropy in the oil and gas industry, EAGE Publications bv. Jupe, A.J., Jones, R.H., Wilson, S.A., and Cowles, J.F., 2003, Microseismic monitoring of geomechanical reservoir processes and fracture-dominated fluid flow, Fracture and In-Situ Stress Characterization of Hydrocarbon Reservoirs, Geological Society, London, Special Publications.2003, Ameed, M.S. (Ed); 209: 77-86. Maver, K.G., Boivineau, A.S., Rinck, U., Barzaghi, L., and Ferulano, F., Real time and continuous reservoir monitoring using microseismicity recorded in a live well, First Break, 27, 57-61. Thomsen, L., 1986, Weak elastic anisotropy, Geophysics, 51, 1954–1966. Warpinski, N., 2009, Microseismic Monitoring: inside and out, JPT, November 2009, 80-85.

27. Acknowledgments We are grateful to Microseismic Inc. for supporting and providing us with the dataset. We thank Vladimir Grechka for providing us with the P-wave traveltime inversion code.