The real-time map of stored CO2 plume will provide a deeper understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of possible CO2 leakage hazards.
We are funded by DOE NETL as well as CO2_SMART center (industry consortium):
The objective of the 1st DOE project (2018 – 2022) is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring (CASSM) dataset capable of providing real-time monitoring of CO2 plume during geologic carbon sequestration (GCS).
The 2nd DOE project (2021-24) is developing a new strategy for monitoring seal integrity combining borehole-based Continuous Active Source Seismic Monitoring (CASSM) with next-generation distributed acoustic sensing (DAS) acquisition to improve the resolution and economic viability of such approaches. Prior generations of borehole sources used for CASSM radiate in the kHz range while DAS tends to have problematic optical noise above 500 Hz; this mismatch will be remedied by (a) development of a new borehole source tuned to lower frequencies; and (b) employing a new DAS interrogator design with improved response in the kHz range. These advances in acquisition technology will be paired with research into relevant processing including novel time-lapse full waveform inversion (FWI) approaches and coda wave analysis techniques. Read details here: https://netl.doe.gov/project-information?p=FE0032058
Copyright @ Penn StateThe major research objectives are to
- develop methodologies for fast seismic full waveform inversion of CASSM datasets for simultaneously estimating velocity and attenuation, and with data assimilation;
- develop joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO2 saturation models;
- demonstrate the methods using multiple datasets including (surface and borehole) synthetic, laboratory, and field CASSM datasets.
Our study showed that efficient data assimilation seismic inversion can provide real-time imaging of CO2 plumes in the deep subsurface. Below is the animation of reduced seismic speed (blue) by inversion to indicate CO2 plume migration along the dipping Blue Sand formation (Huang and Zhu, 2020).
Investigators: Tieyuan Zhu (PI, PSU), Eugene Morgan (PSU), Sanjay Srinivasan (PSU), Alex Sun (UT-Austin), Jonathan Ajo-Franklin (LBL-Rice), Tom Daley (LBL)
Postdoc and students supported:
- Penn State: Donggeon Kim (Postdoc 2024- ), Xuejian Liu (Postdoc 2020-2022), Chao Huang (Postdoc, 2018-2020), Guangchi Xing (Ph.D. student 2017-2022), Shams Joon (Ph.D. student, 2017-2022), Ismael Dawuda (Ph.D. student), Zi Xian Leong (Ph.D. student 2018-2023), Jackson Saftner (Ph.D. student 2022 – )
- Rice U.: Tanner Shadoan (Ph.D. student)
Sponsors: US DOE National Energy Technology Laboratory
Media news:
ScienceDaily news: Coda waves reveal carbon dioxide storage plume
NPR news: At Penn State, researchers push for answers on carbon capture: Will it stay where we put it?
Publications:
Liu X., Zhu T., and Ajo-Franklin J. (2023). Understanding subsurface fracture evolution dynamics using time-lapse full waveform inversion of continuous active-source seismic monitoring data. Geophysical Research Letters, 50, e2022GL101739. https://doi.org/10.1029/2022GL101739
Huang C., Zhu T., and Xing G., (2023), Monitoring dynamic evolution of CO2 plumes during geological sequestration using data assimilated visco-acoustic full-waveform inversion, Geophysics., https://doi.org/10.1190/geo2021-0804.1
Xing G., and Zhu T., (2022), Decoupled Fréchet kernels based on a fractional viscoacoustic wave equation, Geophysics 87: T61-T70. https://doi.org/10.1190/geo2021-0248.1
Zi Xian Leong, Tieyuan Zhu, and Alexander Y. Sun, (2022), “Estimating CO2 saturation maps from seismic data using deep convolutional neural networks,” SEG Technical Program Expanded Abstracts: 510-514. https://doi.org/10.1190/image2022-3746727.1
Xing G., and Zhu T., (2021), A viscoelastic model for seismic attenuation using fractal mechanical network, Geophys. J. Int, 224(3),1658–1669. https://doi.org/10.1093/gji/ggaa549
Huang C., and Zhu T., (2020), Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation, Geophys. J. Int, 223 (2), 811-824. DOI link, PDF
Xing G. and Zhu T., (2019), Modeling frequency-independent Q viscoacoustic wave propagation in heterogeneous media, Journal of Geophysical Research: Solid Earth, 124(11), 11568-11584 https://doi.org/10.1029/2019JB017985, PDF
Joon S. and Morgan E., (2019), Real-time monitoring of CO2 plume during GCS with integrated continuous active-source seismic and pressure monitoring data, AGU fall meeting 2019
Huang C. and Zhu T., (2019), Time-lapse full waveform inversion plus extended Kalman filter for high-resolution seismic models and uncertainty estimation, SEG Technical Program Expanded Abstracts ****-****, Antonio, TX (Sep 14-19 2019).
Xing G. and Zhu T., (2019), Fréchet kernels based on a fractional viscoacoustic wave equation, SEG Technical Program Expanded Abstracts 2019 ****-****, Antonio, TX (Sep 14-19 2019).
Zhu T., Ajo-Franklin J., Daley T.M., and Marone C., (2019) Dynamics of geologic CO2 storage and plume motion revealed by seismic coda waves, PNAS, PDF
Xing G. and Zhu T., (2018), Fractal mechanical network based time domain viscoacoustic wave equation“, SEG Technical Program Expanded Abstracts 2018 3994-3998, Anaheim, CA (Oct 14-19 2018). Links
( 2018). Discovering state‐parameter mappings in subsurface models using generative adversarial networks. Geophysical Research Letters, 45, 11,137– 11,146. https://doi.org/10.1029/2018GL080404