Continuous passive-seismic monitoring of CO2 geologic sequestration projects

Transcription

1 Continuous passive-seismic monitoring of CO2 geologic sequestration projects Biondo Biondi, Stanford University with Sjoerd de Ridder and Jason Chang, Stanford University

2 CCS monitoring 2

3 Volumetric monitoring by 3D seismic Surface receivers Active sources 3

4 Volumetric monitoring by passive 3D seismic Surface receivers 4

5 History of interferometric seismic imaging Invented on Earth Jon Claerbout (1968) Geophysics 5

6 History of interferometric seismic imaging Invented on Earth Apllied on the Sun Jon Claerbout (1968) Geophysics Stanford/NASA soi.stanford.edu/results 6

7 History of interferometric seismic imaging Invented on Earth Applied on the Sun Back to Earth Jon Claerbout (1968) Geophysics Stanford/NASA soi.stanford.edu/results Shapiro et al. (2005) Geophysics 7

8 Seismic interferometry - Step 1 Record data at two receivers Ambient seismic noise Correlations Virtual seismic source 8

9 Seismic interferometry - Step 1 Record data at two receivers at the surface Ambient seismic noise Correlations Virtual seismic source 9

10 Seismic interferometry Step 2 Cross-correlate recorded traces Ambient seismic noise Correlations Virtual seismic source 10

11 Seismic interferometry Step 3 Synthesize virtual events Interface waves Ambient seismic noise Correlations Virtual seismic source Surface waves (transmission) 11

12 Seismic interferometry Step 2 Cross-correlate recorded traces Ambient seismic noise Correlations Virtual seismic source 12

13 Seismic interferometry Step 3 Synthesize virtual events Body waves Ambient seismic noise Correlations Virtual seismic source Body waves (reflections) 13

14 Ambient seismic noise Ambient noise (time slice) Ambient noise (time vs. distance) Distance (km) x real-time 14

15 Ambient seismic noise Ambient noise (time slices) Virtual source (time slices) 2x real-time 15

16 Monitor CO2 reservoir by reflections? Surface waves CO2 reservoir Reflections 16

17 Sleipner - Active seismic monitoring of CCS Andy Chadwick (2009)

18 Sleipner - Monitoring by reflection images Andy Chadwick (2009)

19 Direct detection of CO2 plumes before they reach the surface? Surface waves CO2 plume CO2 reservoir Reflections 19

20 Indirect detection of CO2 plumes deep in the subsurface? CO2 plume Upward migrating CO2 acts as a pressure conduit and changes stress field close to the surface CO2 reservoir 20

21 Salha (Algeria) CCS project Allan Mathieson et al. (2010) Energy Procedia 21

22 Salha (Algeria) CCS project - SAR monitoring Allan Mathieson et al. (2010) Energy Procedia 22

23 ``Moore s law for seismic acquisition Number of channels for one active source credit: David Monke (Apache) &Tim Keho (Aramco) 23

24 Valhall - Life Of Field Seismic array (LOFS) 120 km seismic cables 2500 groups of 4C sensors 50 m receiver spacing 300 m cable spacing 15 Hz geophones, but they record down to.5 Hz signals credit: Olav Barkved (BP) 24

25 Other datasets from (semi)permanent arrays Long Beach 3,000 autonomous MEM sensors Ekofisk 4,000 4C Fiber optic sensors credit: Dan Hollis (Nodal Geophysical) credit: Ali Tura (CP) 25

26 Other datasets from (semi)permanent arrays Long Beach 3,000 autonomous MEM sensors Ekofisk 4,000 4C Fiber optic sensors credit: Dan Hollis (Nodal Geophysical) credit: Ali Tura (CP) 26

27 Other datasets from (semi)permanent arrays Long Beach 3,000 autonomous MEM sensors Ekofisk 4,000 4C Fiber optic sensors.5 TB/day 2.7 TB/day credit: Dan Hollis (Nodal Geophysical) credit: Ali Tura (CP) 27

28 Spectrum of ambient seismic field at Valhall 28

29 Valhall - Virtual seismic source 29

30 Monitor CO2 reservoir by reflections? Surface waves CO2 reservoir Reflections 30

31 Monitor CO2 reservoir by reflections? Not yet Surface waves CO2 reservoir Reflections 31

32 Direct detection of CO2 plumes before they reach the surface? Surface waves CO2 plume CO2 reservoir Reflections 32

33 Identifying velocity anomalies Validation with active-data images at 80 m Ambient seismic noise tomography Hz Full Waveform Inversion on active data m QuickTime and a decompressor are needed to see this picture. QuickTime and a decompressor are needed to see this picture. De Ridder, 2011 Landes et al,

34 Identifying velocity anomalies Validation with active-data images at 170 m Ambient seismic noise tomography Hz Full Waveform Inversion on active data m QuickTime and a decompressor are needed to see this picture. De Ridder, 2011 Landes et al,

35 Direct detection of CO2 plumes before they reach the surface? Most likely! Surface waves CO2 plume CO2 reservoir Reflections 35

36 Indirect detection of CO2 plumes deep in the subsurface? CO2 plume Upward migrating CO2 acts as a pressure conduit and changes stress field close to the surface CO2 reservoir 36

37 Subsidence-related stress changes in subsurface extension contraction extension Gas Pocket Barkved,

38 Detecting changes in stress field Shear wave splitting maps Polarization of fast split shear wave and lag size Production related subsidence Input for geomechanical inversion Can be monitored over time credit: Barkved, BP Norge 38

39 Indirect detection of CO2 plumes deep in the subsurface? Will test on Valhall and Ekofisk CO2 plume Upward migrating CO2 acts as a pressure conduit and changes stress field close to the surface CO2 reservoir 39

40 What about land data? Preliminary results from Long Beach data Long Beach 3,000 autonomous MEM sensors Ambient noise (time slices) 40

41 What about land data? Preliminary results from Long Beach data Virtual source (time slices) Ambient noise (time slices) 41

42 Ongoing and future investigations Analyze Long Beach for time-lapse effects Analyze Ekofisk and Valhall data for anisotropy Look for reflections in all three datasets by performing longer correlations to improve SNR at high frequencies Record data on an actual CCS project 42

43 Ongoing and future investigations Analyze Long Beach for time-lapse effects Analyze Ekofisk and Valhall data for anisotropy Look for reflections in all three datasets by performing longer correlations to improve SNR at high frequencies Record data on an actual CCS project 43

44 Ackowedgements GCEP for financial support SEP affiliate companies for financial support Joe Dellinger and Olav Barkved at BP for data, ideas, and help Dan Hollis at Nodal Geophysical and Signal Petroleum for Long Beach data Ali Tura at ConocoPhillips for Ekofisk data 44

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