Quantifying location uncertainties in seismicity catalogues: application to the Pyrenees
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Abstract
Linearised least-square inversions are commonly used to locate small-magnitude earthquakes, as they are fast and simple to implement. These methods are based on minimising the root-mean-square (RMS) of travel time residuals to find the best-fitting location coordinates and origin time. There are two well-known problems that affect location estimates: (1) the linearisation of the inverse problem causes dependence on the initial guess; (2) regularisation produces solutions that depend on the chosen damping coefficient and biased uncertainty estimates. In this work, we propose a method to quantify unbiased uncertainties with a series of synthetic tests. We first generate travel times for events from all possible coordinates on a 3D grid and then locate each synthetic event by using HYPOCENTER software (this can be applied to any location method). We show that the uncertainties estimated from the standard linearised inversion are strongly underestimated, and we propose another method to compute uncertainties. We produce a 3D error map, where at each grid point we plot the location error, defined as the distance between the event at the given grid point and its inverted location. Moreover, we show how this error map varies with the quantity and quality of the data, and with user-defined parameters such as maximum event–station distance or station corrections. We also provide a methodology to tune the seismic location parameters and calculate the corresponding uncertainties for users who are using similar earthquake location software. Finally, we present an application to the Pyrenean region.
Keywords
Earthquake location Seismicity catalog Uncertainty quantification Velocity modelNotes
Acknowledgements
The authors thank the editor and the reviewers for their precious comments to make the article more reader friendly. The authors would like to thank, for the fruitful discussions, Renaud Toussaint and Franois Renard. Furthermore, the authors would like to thank Thomas Theunissen for providing the seismicity dataset of the Pyrenean Region and his remarks on the project. We also thank Cedric Twardzik from Geoazur (Nice, France), Stephane Rondenay from University of Bergen, Knut Jorgen Maloy from PoreLab (Oslo, Norway), Sophie Lambotte from IPG (Strasbourg, France) and Francois Renard from ISTerre (Grenoble, France) for providing the opportunity for laboratory visits and discussions with their teams during the preparation of this manuscript.
Funding information
This project is financed by Electricity of France (EDF) via the project SINAPS@.
Supplementary material
References
- Abrahamson NA, Bommer JJ (2005) Probability and uncertainty in seismic hazard analysis. Earthquake Spectra 21(2):603–607. https://doi.org/10.1193/1.1899158 CrossRefGoogle Scholar
- Billings SD, Sambridge MS, Kennett BLN (1994) Errors in hypocenter location: picking, model, and magnitude dependence. Bullet Seismol Soc Amer 84(6):1978Google Scholar
- De Natale G, Zollo A, Del Gaudio C, Ricciardi G, Martini M (1984) Error analysis in hypocentral locations at Phlegraean Fields. Bull Volcanol 47(2):209–218CrossRefGoogle Scholar
- Flanagan MP, Myers SC, Koper KD (2007) Regional travel-time uncertainty and seismic location improvement using a three-dimensional a priori velocity model. Bull Seismol Soc Am 97(3):804–825CrossRefGoogle Scholar
- Font Y, Kao H, Lallemand S, Liu CS, Chiao LY (2004) Hypocentre determination offshore of eastern Taiwan using the maximum intersection method. Geophys J Int 158(2):655–675CrossRefGoogle Scholar
- Husen S, Kissling E, Clinton JF (2011) Local and regional minimum 1d models for earthquake location and data quality assessment in complex tectonic regions: application to Switzerland. Swiss J Geosci 104(3):455–469CrossRefGoogle Scholar
- Jordan TH, Sverdrup KA (1981) Teleseismic location techniques and their application to earthquake clusters in the south-central Pacific. Bull Seismol Soc Am 71(4):1105–1130Google Scholar
- Kissling E, Kradolfer U, Maurer H (1995) Program velest user’s guide-short introduction. Institute of Geophysics, ETH ZurichGoogle Scholar
- Lahr J, Chouet B, Stephens C, Power J, Page R (1994) Earthquake classification, location, and error analysis in a volcanic environment: implications for the magmatic system of the 1989–1990 eruptions at Redoubt Volcano, Alaska. J Volcanol Geotherm Res 62(1-4):137–151CrossRefGoogle Scholar
- Lahr JC (1999) HYPOELLIPSE: A computer program for determining local earthquake hypocentral parameters, magnitude and first motion pattern. US Department of the Interior, US Geological SurveyGoogle Scholar
- Lee WHK, Lahr JC (1972) Hypo71: a computer program for determining hypocenter, magnitude and first motion pattern of local earthquakes. Technical report, US Geological SurveyGoogle Scholar
- Lee Y, Taylor C, Hu Z, Graf WP, Huyck CK (2014) Uncertainty estimates for earthquake hazard analysis through robust simulation. In: Tenth US National Conference on Earthquake Engineering Frontiers of Earthquake Engineering, pp 21–25Google Scholar
- Lienert BR, Berg E, Frazer LN (1986) Hypocenter: an earthquake location method using centered, scaled, and adaptively damped least squares. Bull Seismol Soc Am 76(3):771–783Google Scholar
- Lienert BR, Havskov J (1995) A computer program for locating earthquakes both locally and globally. Seismol Res Lett 66(5):26–36CrossRefGoogle Scholar
- Lomax A, Virieux J, Volant P, Berge-Thierry C (2000) Probabilistic earthquake location in 3d and layered models. In: Advances in seismic event location. Springer, pp 101–134Google Scholar
- Lomax A, Michelini A, Curtis A (2009) Earthquake location, direct, global-searchglobal-search methods. In: Encyclopedia of complexity and systems science. Springer, pp 2449–2473Google Scholar
- Pavlis GL (1986) Appraising earthquake hypocenter location errors: a complete, practical approach for single-event locations. Bullet Seismol Soc Amer 76(6):1699Google Scholar
- Pavlis GL (1992) Appraising relative earthquake location errors. Bullet Seismol Soc Amer 82(2):836Google Scholar
- Peters DC, Crosson RS (1972) Application of prediction analysis to hypocenter determination using a local array. Bull Seismol Soc Am 62(3):775–788Google Scholar
- Rawlinson N, Sambridge M (2005) The fast marching method: an effective tool for tomographic imaging and tracking multiple phases in complex layered media. Explor Geophys 36(4):341–350CrossRefGoogle Scholar
- Richards PG, Waldhauser F, Schaff D, Kim WY (2006) The applicability of modern methods of earthquake location. Pure Appl Geophys 163(2):351–372. https://doi.org/10.1007/s00024-005-0019-5 CrossRefGoogle Scholar
- Simmons NA, Myers SC, Johannesson G, Matzel E (2012) Llnl-g3dv3: Global p wave tomography model for improved regional and teleseismic travel time prediction. Journal of Geophysical Research: Solid Earth 117(B10). https://doi.org/10.1029/2012JB009525
- Tarantola A, Valette B (1982) Generalized nonlinear inverse problems solved using the least squares criterion. Rev Geophys 20(2):219–232CrossRefGoogle Scholar
- Theunissen T, Lallemand S, Font Y, Gautier S, Lee CS, Liang WT, Wu F, Berthet T (2012) Crustal deformation at the southernmost part of the Ryukyu subduction (East Taiwan) as revealed by new marine seismic experiments. Tectonophysics 578:10–30CrossRefGoogle Scholar
- Theunissen T, Chevrot S, Sylvander M, Monteiller V, Calvet M, Villaseñor A, Benahmed S, Pauchet H, Grimaud F (2017) Absolute earthquake locations using 3-d versus 1-d velocity models below a local seismic network: example from the pyrenees. Geophys J Int 212(3):1806– 1828CrossRefGoogle Scholar
- Thurber CH (1986) Analysis methods for kinematic data from local earthquakes. Rev Geophys 24 (4):793–805. https://doi.org/10.1029/RG024i004p00793 CrossRefGoogle Scholar
- Thurber CH (1992) Hypocenter-velocity structure coupling in local earthquake tomography. Phys Earth Planet Inter 75(1-3):55–62CrossRefGoogle Scholar
- Tramelli A, Troise C, De Natale G, Orazi M (2013) A new method for optimization and testing of microseismic networks: an application to Campi Flegrei (southern italy). Bull Seismol Soc Am 103(3):1679–1691CrossRefGoogle Scholar
- Turkaya S, Toussaint R, Eriksen FK, Lengliné O, Daniel G, Flekkøy EG, Måløy KJ (2016) Note: Localization based on estimated source energy homogeneity. Rev Sci Instrum 87(9):096101. https://doi.org/10.1063/1.4962407 CrossRefGoogle Scholar
- Turquet AL, Toussaint R, Eriksen FK, Daniel G, Lengline O, Flekkoy EG, Maloy KJ (2019) Source localization of microseismic emissions during pneumatic fracturing. Geophys Res Lett 46(7):3726–3733. https://doi.org/10.1029/2019GL082198. https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019GL082198 CrossRefGoogle Scholar
- Waldhauser F (2001) hypodd–a program to compute double-difference hypocenter locations (hypodd version 1.0-03/2001). US Geol Surv Open-File Rept 01 113Google Scholar