Time-lapse crosswell seismic monitoring of CO2 injection at the Nagaoka CCS site using elastic full-waveform inversion

Nakata, Rie; Nakata, Nori; Girard, Aaron; Ichikawa, Masaru; Kato, Akira; Lumley, David; Xue, Ziqian

doi:10.1190/image2022-3744414.1

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…Seismic velocity is a measure of rocks' elastic properties, which is sensitive to perturbations in fluid content, the stress field, and micro‐structures. Temporal changes in seismic velocity have been measured to study a variety of geological and environmental processes related to tectonic stress build up or release (Poupinet et al., 1984), magma storage changes at volcanos (Brenguier, Shapiro, et al., 2008; Koulakov et al., 2013; Mordret et al., 2010; Rivet et al., 2015), dynamic shaking or static stress changes caused by earthquakes (Brenguier et al., 2014; Froment et al., 2013; Peng & Ben‐Zion, 2006; Rubinstein & Beroza, 2004, 2005; Zaccarelli et al., 2011), seasonal changes in near‐surface saturation or groundwater level (Clements & Denolle, 2018; Clymer & McEvilly, 1981; Lecocq et al., 2017; Mao et al., 2022; Mordret et al., 2020; Qin et al., 2022; Sens‐Schönfelder & Wegler, 2006; Voisin et al., 2017), tidally induced strain (Mao et al., 2019; Takano et al., 2019; Wang et al., 2008; Yamamura et al., 2003), geothermal exploitation (Boitnott & Boyd, 1996; Sanchez‐Pastor et al., 2019; Taira et al., 2018; Zhang et al., 2022), CO 2 injection (Nakata et al., 2022), and freeze‐thaw cycles (James et al., 2019; Lindner et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Adaptive Coda‐Wave Imaging With Voronoi Tessellation

2023

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Reconstructions of Green’s functions by ambient noise interferometry enable the imaging of the Earth’s subsurface. Coda waves from reconstructed Green’s functions can be utilized to perform time‐dependent imaging of processes that vary substantially at daily to monthly time scales in the shallow crust. Time‐dependent Coda‐Wave Imaging (CWI) can detect tiny changes in seismic velocity with high temporal resolution. Challenges for the interpretation of coda waves, however, result from complexities in the travel paths of multiply scattered coda waves. In this paper we develop a pragmatic approach to improving coda‐wave imaging using Voronoi tessellation with mesh cells adapted to coda‐wave sensitivity kernels. Using seismic stations in Central California, we present both synthetic and real data imaging to demonstrate that this approach stabilizes the inversion, is computationally efficient, and provides spatially adaptive resolution. We further propose a heuristic approach for a quantitative assessment of spatial resolution based on multi‐scale checkerboard tests.

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Section: Introductionmentioning

confidence: 99%

Adaptive Coda‐Wave Imaging With Voronoi Tessellation

2023

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“…In time-lapse cross-well seismic surveys, travel time tomography and travel time difference tomography were widely used to detect velocity changes in reservoirs caused by CO 2 injection [7,8,14,[18][19][20][21]. Moreover, full waveform inversion (FWI) can also be applied for monitoring CO 2 sequestration and providing a possible way to quantify the amount of injected CO 2 [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Time-Lapse Cross-Well Monitoring of CO2 Sequestration Using Coda Wave Interferometry

Zhang

Juhlin

et al. 2022

Remote Sensing

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In this study, we explored the capability of coda wave interferometry (CWI) for monitoring CO2 storage by estimating the seismic velocity changes caused by CO2 injection. Given that the CWI method is highly efficient, the primary aim of this study was to provide a quick detection tool for the long-term monitoring of CO2 storage safety. In particular, we looked at monitoring with a cross-well geometry. We also expected that CWI could help to reduce the inversion errors of existing methods. Time-lapse upgoing waves and downgoing waves from two-component datasets were utilized to efficiently monitor the area between the wells and provide a quick indication of possible CO2 leakage. The resulting mean velocity changes versus the depth indicated the depth where velocity changes occurred. Combining the upgoing and downgoing wavefields provided a more specific indication of the depth range for changes. The calculated velocity changes were determined using the time shift between the time-lapse wavefields caused by CO2 injection/leakage. Hence, the resulting velocity changes were closely related to the ratio of propagation path length through the CO2 injection/leakage layer over the length of the entire travel path. The results indicated that the noise level and repeatability of the time-lapse datasets significantly influenced the results generated using CWI. Therefore, denoising and time-lapse processing were very important for improving the detectability of any change. Applying CWI to time-lapse cross-well surveys can be an effective tool for monitoring CO2 in the subsurface at a relatively low computational cost. As a highly efficient monitoring method, it is sensitive to changes in the seismic response caused by velocity changes in the subsurface and provides additional constraints on the inversion results from conventional travel time tomography and full waveform inversion.

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Enigmatic doubly scattered tube waves at a crosswell seismic survey

Nakata

Kato

et al. 2022

Geophysical Journal International

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Summary Enigmatically strong tube waves continue to exist long after the direct wave during repeat crosswell-monitoring surveys at the Nagaoka CO2 injection site in Japan. The tube waves, which have linear moveouts with velocities of 1.29 and 1.41 km/s at plastic and steel casings, respectively, are generated by double scattering on the shallow side of the wells. We characterize wavefields to confirm that these late coda waves are tube waves that are excited at the source well, propagate upward, then travel to a receiver well as a body wave, and finally propagate downward along the receiver well. Even though these tube waves result from second-order scattering, they have large amplitudes because of the relatively short distance between source and receiver wells. Because these waves propagate along both wells many times, we can extract detailed information of wave propagation by averaging them to increase the signal-to-noise ratio. We first use the tube waves to relocate sources and receivers between multiple monitoring surveys, demonstrating our ability to correct the severe noise caused by location errors that frequently degrades the repeatability of time-lapse surveys. Then we apply an inversion based on the physics of tube waves to estimate the location and strength of the scatterers and find that they are predominantly located in the shallow segment of the wells, above the sources, and infer that they are related to local fractures and/or wellbore conditions because their locations do not correspond to the well geometry. Lastly, we use the tube waves to accurately estimate subsurface velocities along the wells. The estimation is stable and robust, and the velocities follow the general trend of subsurface structure seen in the well log data. Due to the receiver spacing, tube-wave analysis cannot resolve a thin, high-velocity layer at the CO2 reservoir. By combining tube waves observed during different stages of the monitoring survey, we can estimate the time-lapse changes of the subsurface velocities.

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Time-lapse crosswell seismic monitoring of CO2 injection at the Nagaoka CCS site using elastic full-waveform inversion

Cited by 6 publications

References 7 publications

Adaptive Coda‐Wave Imaging With Voronoi Tessellation

Adaptive Coda‐Wave Imaging With Voronoi Tessellation

Time-Lapse Cross-Well Monitoring of CO2 Sequestration Using Coda Wave Interferometry

Enigmatic doubly scattered tube waves at a crosswell seismic survey

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