Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities
[4]
- National Energy Technology Lab. (NETL) and Oak Ridge Inst. for Science and Education (ORISE), Pittsburgh, PA, (United States)
- National Energy Technology Lab. (NETL) and Oak Ridge Inst. for Science and Education (ORISE), Pittsburgh, PA, (United States); Univ. of Pittsburgh, PA (United States). Dept. of Geology and Environmental Science
- National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Time-lapse surface seismic surveys have been widely used at carbon sequestration sites for site characterization, monitoring subsurface CO2 plume migration, and detecting potential CO2 leakage from a storage reservoir. Monitoring in the first permeable unit directly above the primary seal is important for early detection of CO2 leakage. Forward modeling of time-lapse seismic data can be used to assess the utility of the seismic method for CO2 leakage detection. We develop a workflow for forward modeling of time-lapse seismic data, including constructing seismic velocity models using flow simulation outputs, modeling of pre-stack and post-stack synthetic seismic data following seismic data processing sequence and analysis of processed synthetic time-lapse seismic data. We apply the forward modeling and analysis workflow to assessing the detectability and the earliest detection time of seismic monitoring using the hypothetical CO2 leakage scenarios for a model geologic storage site with realistic geology. We then derive the detection thresholds using the simulated normalized root-mean-square (NRMS) differences for the no-leakage case at a range of signal-to-noise ratios, representing the background noise levels in seismic data. We then compare NRMS differences triggered by the CO2 leakage to the detection thresholds at each time step to quantify the detectability and the earliest detection time of seismic monitoring. We analyze the effects of the acquisition parameters and elastic parameters on the produced synthetic seismic data and earliest detection time. Our modeling results indicate that high signal-to-noise ratio is needed to detect the CO2 leakage at the model site. Minimizing the background noise in seismic data is crucial for improving the detectability of the seismic method. Increasing the shot density or increasing the dominant frequency of the source wavelet is likely to increase the possibility of the leakage detection and reduce the time needed for the detection. The elastic parameters used in the rock physics modeling have significant effects on the resultant seismic velocity models and synthetic seismic data, highlighting their critical roles in understanding and interpreting time-lapse seismic reflection data associated with CO2monitoring, verification and accounting activities.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States); National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States); Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE)
- Grant/Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1473811
- Alternate ID(s):
- OSTI ID: 1496441
- Report Number(s):
- LA-UR-18-20332
- Journal Information:
- International Journal of Greenhouse Gas Control, Vol. 76, Issue C; ISSN 1750-5836
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Kimberlina 1.2 Velocity Models and Seismic Data
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dataset | January 2021 |
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