Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2701-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-2701-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A novel approach to assessing nuisance risk from seismicity induced by UK shale gas development, with implications for future policy design
Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK
Maximilian J. Werner
School of Earth Sciences, University of Bristol, Bristol, UK
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Flood risk is expected to increase in many regions worldwide due to rapid urbanization and climate change. The benefits of risk-mitigation measures remain inadequately quantified for potential future events in some multi-hazard-prone areas such as Kathmandu Valley (KV), Nepal, which this paper addresses. The analysis involves modeling two flood occurrence scenarios and using four residential exposure inventories representing current urban system or near-future development trajectories for KV.
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Flood risk is expected to increase in many regions worldwide due to rapid urbanization and climate change. The benefits of risk-mitigation measures remain inadequately quantified for potential future events in some multi-hazard-prone areas such as Kathmandu Valley (KV), Nepal, which this paper addresses. The analysis involves modeling two flood occurrence scenarios and using four residential exposure inventories representing current urban system or near-future development trajectories for KV.
Jack N. Williams, Luke N. J. Wedmore, Åke Fagereng, Maximilian J. Werner, Hassan Mdala, Donna J. Shillington, Christopher A. Scholz, Folarin Kolawole, Lachlan J. M. Wright, Juliet Biggs, Zuze Dulanya, Felix Mphepo, and Patrick Chindandali
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We use geologic and GPS data to constrain the magnitude and frequency of earthquakes that occur along active faults in Malawi. These faults slip in earthquakes as the tectonic plates on either side of the East African Rift in Malawi diverge. Low divergence rates (0.5–1.5 mm yr) and long faults (5–200 km) imply that earthquakes along these faults are rare (once every 1000–10 000 years) but could have high magnitudes (M 7–8). These data can be used to assess seismic risk in Malawi.
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Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-59, https://doi.org/10.5194/nhess-2022-59, 2022
Publication in NHESS not foreseen
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This study develops a novel framework of time-dependent (TD) probabilistic tsunami hazard analysis (PTHA) combining a total of ≥ 100,000 spatiotemporal earthquakes (EQ) rupture models and 6,300 probabilistic tsunami simulations to evaluate the tsunami hazards and compare them with the time-independent (TI) PTHA results. The proposed model can capture the uncertainty of future TD tsunami hazards and produces slightly higher hazard estimates than the TI model for short-term periods (< 30 years).
Cited articles
Assatourians, K. and Atkinson, G. M.:
EqHaz: An open-source probabilistic seismic-hazard code based on the Monte Carlo simulation approach,
Seismol. Res. Lett.,
84, 516–524, 2013. a
Athanasopoulos, G. and Pelekis, P.:
Ground vibrations from sheetpile driving in urban environment: measurements, analysis and effects on buildings and occupants,
Soil Dynam. Earthq. Eng.,
19, 371–387, 2000. a
Atkinson, G. M., Eaton, D. W., Ghofrani, H., Walker, D., Cheadle, B., Schultz, R., Shcherbakov, R., Tiampo, K., Gu, J., Harrington, R. M., Liu, Y., van der Baan, M., and Kao, H.:
Hydraulic fracturing and seismicity in the western Canada sedimentary basin,
Seismol. Res. Lett.,
87, 631–647, 2016. a
Atkinson, G. M., Eaton, D. W., and Igonin, N.:
Developments in understanding seismicity triggered by hydraulic fracturing,
Nat. Rev. Earth Environ.,
1, 264–277, 2020. a
Bachmann, C. E., Wiemer, S., Woessner, J., and Hainzl, S.:
Statistical analysis of the induced Basel 2006 earthquake sequence: introducing a probability-based monitoring approach for Enhanced Geothermal Systems,
Geophys. J. Int.,
186, 793–807, 2011. a
Bao, X. and Eaton, D. W.:
Fault activation by hydraulic fracturing in western Canada,
Science,
354, 1406–1409, 2016. a
Barneich, J.: Vehicle induced ground motion, in: Vibration Problems in Geotechnical Engineering, edited by: Gazetas, G. and Selig, E., Proceedings of Symposium Held by the Geotechnical Engineering Division in conjunction with the ASCE Convention, 22 October 1985, Detroit, MI, USA, 187–202, 1985. a
Bazzurro, P. and Allin Cornell, C.:
Disaggregation of seismic hazard,
B. Seismol. Soc. Am.,
89, 501–520, 1999. a
Beyer, K. and Bommer, J. J.:
Relationships between median values and between aleatory variabilities for different definitions of the horizontal component of motion,
B. Seismol. Soc. Am.,
96, 1512–1522, 2006. a
Bommer, J. J. and Alarcon, J. E.:
The prediction and use of peak ground velocity,
J. Earthq. Eng.,
10, 1–31, 2006. a
Bommer, J. J., Stafford, P. J., Alarcón, J. E., and Akkar, S.:
The influence of magnitude range on empirical ground-motion prediction,
B. Seismol. Soc. Am.,
97, 2152–2170, 2007. a
Boore, D. M., Gibbs, J. F., Joyner, W. B., Tinsley, J. C., and Ponti, D. J.:
Estimated ground motion from the 1994 Northridge, California, earthquake at the site of the Interstate 10 and La Cienega Boulevard bridge collapse, West Los Angeles, California,
B. Seismol. Soc. Am.,
93, 2737–2751, 2003. a
British Geological Survey:
Statement on seismic activity at Preston New Road, Lancashire on 28/8/19,
available at: https://www.bgs.ac.uk/news/docs/BGS Statement on seismic_activity_28_8_19.pdf (last access: March 2020), 2019a. a
British Geological Survey: BGS earthquake database search, available at:
http://www.earthquakes.bgs.ac.uk/earthquakes/dataSearch.html (last access: December 2019), 2019b. a
British Geological Survey: BGS ftp site, available at:
ftp://seiswav.bgs.ac.uk/, last access: September 2020. a
Broccardo, M., Mignan, A., Wiemer, S., Stojadinovic, B., and Giardini, D.:
Hierarchical Bayesian Modeling of Fluid-Induced Seismicity,
Geophys. Res. Lett.,
44, 11–357, 2017. a
Butcher, A., Luckett, R., Kendall, J.-M., and Baptie, B.: Seismic Magnitudes, Corner Frequencies, and Microseismicity: Using Ambient Noise to Correct for High‐Frequency Attenuation, B. Seismol. Soc. Am., 110, 1260–1275, https://doi.org/10.1785/0120190032, 2019. a
Chen, H., Meng, X., Niu, F., Tang, Y., Yin, C., and Wu, F.:
Microseismic monitoring of stimulating shale gas reservoir in SW China: 2. Spatial clustering controlled by the preexisting faults and fractures,
J. Geophys. Res.-Solid,
123, 1659–1672, 2018. a
Cornell, C. A.:
Engineering seismic risk analysis,
B. Seismol. Soc. Am.,
58, 1583–1606, 1968. a
Cotton, M., Rattle, I., and Van Alstine, J.:
Shale gas policy in the United Kingdom: An argumentative discourse analysis,
Energ. Policy,
73, 427–438, 2014. a
Crowley, H., Pinho, R., van Elk, J., and Uilenreef, J.:
Probabilistic damage assessment of buildings due to induced seismicity,
B. Earthq. Eng.,
17, 4495–4516, 2018. a
Davies, R., Foulger, G., Bindley, A., and Styles, P.:
Induced seismicity and hydraulic fracturing for the recovery of hydrocarbons,
Mar. Petrol. Geol.,
45, 171–185, 2013. a
De Pater, C. and Baisch, S.:
Geomechanical study of Bowland Shale seismicity, Synthesis report,
Cuadrilla Resources Ltd., Lichfield, Staffordshire, UK, 57 pp., 2011. a
Douglas, J. and Aochi, H.:
Using estimated risk to develop stimulation strategies for enhanced geothermal systems,
Pure Appl. Geophys.,
171, 1847–1858, 2014. a
Eaton, D. W., Davidsen, J., Pedersen, P. K., and Boroumand, N.:
Breakdown of the Gutenberg-Richter relation for microearthquakes induced by hydraulic fracturing: Influence of stratabound fractures,
Geophys. Prospect.,
62, 806–818, 2014. a
Ellsworth, W. L.:
Injection-induced earthquakes,
Science,
341, 1225942, https://doi.org/10.1126/science.1225942, 2013. a
Gallegos, T. J., Varela, B. A., Haines, S. S., and Engle, M. A.:
Hydraulic fracturing water use variability in the United States and potential environmental implications,
Water Resour. Res.,
51, 5839–5845, 2015. a
Ghofrani, H. and Atkinson, G. M.:
Site condition evaluation using horizontal-to-vertical response spectral ratios of earthquakes in the NGA-West 2 and Japanese databases,
Soil Dynam. Earthq. Eng.,
67, 30–43, 2014. a
Gischig, V. S.:
Rupture propagation behavior and the largest possible earthquake induced by fluid injection into deep reservoirs,
Geophys. Res. Lett.,
42, 7420–7428, 2015. a
Gischig, V. S. and Wiemer, S.:
A stochastic model for induced seismicity based on non-linear pressure diffusion and irreversible permeability enhancement,
Geophys. J. Int.,
194, 1229–1249, 2013. a
Ground Water Protection Council:
Modern shale gas development in the United States: A primer,
US Department of Energy, Office of Fossil Energy, Washington, D.C., USA, 2009. a
Grünthal, G.:
European macroseismic scale 1998, Tech. rep.,
European Seismological Commission (ESC), Luxembourg, 1998. a
Gupta, A. and Baker, J. W.:
A framework for time-varying induced seismicity risk assessment, with application in Oklahoma,
B. Earthq. Eng.,
17, 4475–4493, 2019. a
Hainzl, S. and Ogata, Y.:
Detecting fluid signals in seismicity data through statistical earthquake modeling,
J. Geophys. Res.-Sol. Ea.,
110, B05S07, https://doi.org/10.1029/2004JB003247, 2005. a
Häring, M. O., Schanz, U., Ladner, F., and Dyer, B. C.:
Characterisation of the Basel 1 enhanced geothermal system,
Geothermics,
37, 469–495, 2008. a
Haylock, D.:
Numeracy for teaching,
Sage, London, UK, 2001. a
Jayaram, N. and Baker, J. W.:
Statistical tests of the joint distribution of spectral acceleration values,
B. Seismol. Soc. Am.,
98, 2231–2243, 2008. a
Johnson, E. G. and Johnson, L. A.:
Hydraulic fracture water usage in northeast British Columbia: locations, volumes and trends, in: Geoscience Reports 2012, British Columbia Ministry of Energy and Mines, Victoria, British Columbia, Canada, 41–63, 2012. a
Kettlety, T., Verdon, J., Werner, M., and Kendall, J.:
Stress transfer from opening hydraulic fractures controls the distribution of induced seismicity,
J. Geophys. Res.-Solid,
125, e2019JB018794, https://doi.org/10.1029/2019JB018794, 2020. a
Kraft, T., Mai, P. M., Wiemer, S., Deichmann, N., Ripperger, J., Kästli, P., Bachmann, C., Fäh, D., Wössner, J., and Giardini, D.:
Enhanced geothermal systems: Mitigating risk in urban areas,
Eos T. Am. Geophys. Un.,
90, 273–274, 2009. a
Kwiatek, G., Saarno, T., Ader, T., Bluemle, F., Bohnhoff, M., Chendorain, M., Dresen, G., Heikkinen, P., Kukkonen, I., Leary, P., Leonhardt, M., Malin, P., Martínez-Garzón, P., Passmore, K., Passmore, P., Valenzuela, S., and Wollin, C.: Controlling fluid-induced seismicity during a 6.1-km-deep geothermal stimulation in Finland, Sci. Adv., 5, eaav7224, https://doi.org/10.1126/sciadv.aav7224, 2019. a
Langenbruch, C. and Shapiro, S. A.:
Decay rate of fluid-induced seismicity after termination of reservoir stimulations,
Geophysics,
75, MA53–MA62, 2010. a
MacRae, G. A.:
Decision making tools for seismic risk,
in: vol. 28, Proceedings of the New Zealand Society of Earthquake Engineering Annual Conference Paper, March 2006, Napier, New Zealand, 2006. a
Mancini, S., Segou, M., Werner, M. J., and Baptie, B. J.:
Statistical modelling of the Preston New Road seismicity: Towards probabilistic forecasting tools,
Report No. CR/19/068 Commissioned by the Oil and Gas Authority,
available at: https://www.ogauthority.co.uk/media/6147/bgs-innovations-in-forecasting.pdf (last access: September 2020), 2019. a, b
McGarr, A.:
Maximum magnitude earthquakes induced by fluid injection,
J. Geophys. Res.-Solid,
119, 1008–1019, 2014. a
Mena, B., Wiemer, S., and Bachmann, C.:
Building robust models to forecast the induced seismicity related to geothermal reservoir enhancement,
B. Seismol. Soc. Am.,
103, 383–393, 2013. a
Mignan, A., Broccardo, M., Wiemer, S., and Giardini, D.:
Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections,
Sci. Rep.-UK,
7, 13607, https://doi.org/10.1038/s41598-017-13585-9, 2017. a, b
Mignan, A., Karvounis, D., Broccardo, M., Wiemer, S., and Giardini, D.:
Including seismic risk mitigation measures into the Levelized Cost of Electricity in enhanced geothermal systems for optimal siting,
Appl. Energ.,
238, 831–850, 2019. a
Morris, B., Medyckyj-Scott, D., and Burnhill, P.:
EDINA Digimap: new developments in the Internet Mapping and Data Service for the UK Higher Education community,
Liber Quart.,
10, 445–453, 2000. a
Musson, R.:
Determination of design earthquakes in seismic hazard analysis through Monte Carlo simulation,
J. Earthq. Eng.,
3, 463–474, 1999. a
Park, J., Bazzurro, P., and Baker, J. W.: Modeling spatial correlation of ground motion intensity measures for regional seismic hazard and portfolio loss estimation, in: 10th International Conference on Application of Statistic and Probability in Civil Engineering (ICASP10), Tokyo, Japan, 8 pp., 2007. a
Precht, P. and Dempster, D.:
Jurisdictional review of hydraulic fracturing regulation, Final report for Nova Scotia Hydraulic Fracturing Review Committee,
Nova Scotia Department of Energy and Nova Scotia Environment,
available at: https://novascotia.ca/nse/pollutionprevention/docs/Consultation.Hydraulic.Fracturing-Jurisdictional.Review.pdf (last access: September 2020), 2012. a
Scasserra, G., Stewart, J. P., Bazzurro, P., Lanzo, G., and Mollaioli, F.:
A comparison of NGA ground-motion prediction equations to Italian data,
B. Seismol. Soc. Am.,
99, 2961–2978, 2009. a
Shapiro, S. A., Dinske, C., Langenbruch, C., and Wenzel, F.:
Seismogenic index and magnitude probability of earthquakes induced during reservoir fluid stimulations,
Leading Edge,
29, 304–309, 2010. a
Third Energy:
Hydraulic Fracture Plan for well KM-8,
Third Energy UK Gas Ltd., Malton, North Yorkshire, UK, 2017. a
UK Oil & Gas Authority: Preston New Road – PNR 1Z – Hydraulic Fracturing Operations Data, available at: https://www.ogauthority.co.uk/exploration-production/onshore/onshore-reports-and-data/preston-new-road-pnr-1z-hydraulic-fracturing-operations-data/, last access: September 2020. a
Van Eck, T., Goutbeek, F., Haak, H., and Dost, B.:
Seismic hazard due to small-magnitude, shallow-source, induced earthquakes in The Netherlands,
Eng. Geol.,
87, 105–121, 2006. a
Verdon, J. P., Baptie, B. J., and Bommer, J. J.:
An improved framework for discriminating seismicity induced by industrial activities from natural earthquakes, Seismol. Res. Lett., 90, 1592–1611, https://doi.org/10.1785/0220190030, 2019. a
Wang, M. and Takada, T.:
Macrospatial correlation model of seismic ground motions,
Earthq. Spectra,
21, 1137–1156, 2005. a
Weatherill, G., Silva, V., Crowley, H., and Bazzurro, P.:
Exploring the impact of spatial correlations and uncertainties for portfolio analysis in probabilistic seismic loss estimation,
B. Earthq. Eng.,
13, 957–981, 2015. a
Westaway, R.:
The importance of characterizing uncertainty in controversial geoscience applications: induced seismicity associated with hydraulic fracturing for shale gas in northwest England,
P. Geologist. Assoc.,
127, 1–17, 2016. a
Whitmarsh, L., Nash, N., Upham, P., Lloyd, A., Verdon, J. P., and Kendall, J.-M.:
UK public perceptions of shale gas hydraulic fracturing: The role of audience, message and contextual factors on risk perceptions and policy support,
Appl. Energ.,
160, 419–430, 2015. a
Williams, L., Macnaghten, P., Davies, R., and Curtis, S.:
Framing `fracking': Exploring public perceptions of hydraulic fracturing in the United Kingdom,
Publ.Underst. Sci.,
26, 89–104, 2017. a
Woessner, J., Laurentiu, D., Giardini, D., Crowley, H., Cotton, F., Grünthal, G., Valensise, G., Arvidsson, R., Basili, R., Demircioglu, M. B., Hiemer, S., Meletti, C., Musson, R. W., Rovida, A. N., Sesetyan, K., Stucchi, M., and The SHARE Consortium:
The 2013 European seismic hazard model: key components and results,
B. Earthq. Eng.,
13, 3553–3596, 2015. a
Short summary
We develop a framework that links the volume of hydraulic fracturing fluid injected during shale gas exploration with the likelihood that resulting seismicity causes a nuisance to nearby populations. We apply the framework to a shale gas site in England and find that the potential of a given injected volume to produce nuisance ground motions is especially sensitive to assumptions about the amount of seismic energy released during operations. The work can inform policy on shale gas exploration.
We develop a framework that links the volume of hydraulic fracturing fluid injected during shale...
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