| Title | Seismicity-scanning based on navigated automatic phase-picking |
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| Author | Tan, F; Kao, H ;
Nissen, E; Eaton, D |
| Source | Journal of Geophysical Research, Solid Earth vol. 124, issue 4, 2019 p. 3802-3818, https://doi.org/10.1029/2018JB017050 |
| Image |  |
| Year | 2019 |
| Alt Series | Natural Resources Canada, Contribution Series 20190071 |
| Publisher | American Geophysical Union (AGU) |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf (Adobe® Reader®); html |
| Subjects | geophysics; Science and Technology; seismology; seismicity; array seismology; earthquakes; earthquake catalogues; earthquake magnitudes; epicentres; hydraulic fracturing; Methodology;
Automation |
| Illustrations | flow diagrams; location maps; tables; geoscientific sketch maps; profiles; spectra; time series; histograms; graphs |
| Program | Environmental Geoscience Shale Gas - induced seismicity |
| Released | 2019 03 31 |
| Abstract | We propose a new method, named Seismicity-Scanning based on Navigated Automatic Phase-picking (S-SNAP), that is capable of delineating complex spatiotemporal distributions of seismicity. This novel
algorithm takes a cocktail approach that combines source scanning, kurtosis-based phase picking, and the maximum intersection location technique into a single integrated workflow. This method is automated, detecting and locating earthquakes
efficiently, comprehensively, and accurately. We apply S-SNAP to a data set recorded by a dense local seismic array during a hydraulic fracturing operation to test this novel approach and to demonstrate its effectiveness in relation to existing
methods. Overall, S-SNAP found about 3.5 times as many high-quality events as a template matching-based catalogue. All events in the previous catalogue are identified with similar epicenters, depths, and magnitudes, while no false detections are
found by visual inspection. |
| Summary | (Plain Language Summary, not published)
We propose a new method capable of delineating complex distributions of earthquakes that occurred in close time and space. This novel algorithm takes a
cocktail approach that combines the merits of several previously existing methods into a single integrated workflow. This method is automatic, efficiently providing earthquake locations with high comprehensiveness and accuracy. A test example using
data recorded by a dense local seismic array during a hydraulic fracturing operation is presented to demonstrate the advantage of our proposed method. |
| GEOSCAN ID | 314699 |
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