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Point process modelling of reservoir-induced seismicity

Part of: Stochastic processes Geophysics (general) Geophysics

Published online by Cambridge University Press:  14 July 2016

Masajiro Imoto
Masajiro Imoto*
Affiliation:
National Research Institute for Earth Science and Disaster Prevention, Japan
*
1Postal address: National Research Institute for Earth Science and Disaster Prevention, 3–1 Ten'nodai, Tsukuba-shi, Ibaraki-ken, 305–0006, Japan. Email: [email protected]
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Abstract

A point process procedure can be used to study reservoir-induced seismicity (RIS), in which the intensity function representing earthquake hazard is a combination of three terms: a constant background term, an ETAS (epidemic-type aftershock sequence) term for aftershocks, and a time function derived from observation of water levels of a reservoir. This paper presents the results of such a study of the seismicity in the vicinity of the Tarbela reservoir in Pakistan. Making allowance for changes in detection capability and the background seismicity related to tectonic activity, earthquakes of magnitude ≥ 2.0, occurring between May 1978 and January 1982 and whose epicentres were within 100 km of the reservoir, were used in this analysis. Several different intensities were compared via their Akaike information criterion (AIC) values relative to those of a Poisson process. The results demonstrate that the seismicity within 20 km of the reservoir correlates with water levels of the reservoir, namely, active periods occur about 250 days after the appearance of low water levels. This suggests that unloading the reservoir activates the seismicity beneath it. Seasonal variations of the seismicity in an area up to 100 km from the reservoir were also found, but these could not be adequately interpreted by an appropriate RIS mechanism.

Keywords

Induced seismicitypoint processETAS modelRISTarbela reservoir

MSC classification

Primary: 86A15: Seismology
Secondary: 60G55: Point processes
Type
Models and statistics in seismology
Information
Journal of Applied Probability , Volume 38 , Issue A: Probability, Statistics and Seismology , 2001 , pp. 232 - 242
Copyright
Copyright © Applied Probability Trust 2001 

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References

Akaike, H. (1974). A new look at the statistical model identification. IEEE Trans. Automatic Control AC19, 716–723.Google Scholar
Aki, K. (1989). Ideal probabilistic earthquake prediction. Tectonophysics 169, 197–198.Google Scholar
Bell, M. L. and Nur, A. (1978). Strength changes due to reservoir-induced pore pressure and stresses and application to Lake Oroville. J. Geophys. Res. 83, 4469–4483.CrossRefGoogle Scholar
Gough, D. I. and Gough, W. I. (1970a). Stress and deflection in the lithosphere near Lake Kariba, 1. Geophys. J. Roy. Astronom. Soc. 21, 65–78.Google Scholar
Gough, D. I. and Gough, W. I. (1970b). Load-induced earthquakes at Lake Kariba, 2. Geophys. J. Roy. Astronom. Soc. 21, 79–101.Google Scholar
Gupta, H. K. (1992). Reservoir-induced earthquakes (Developments in Geotechnical Engineering 64). Elsevier, Amsterdam.Google Scholar
Ibenbrahim, A., Ni, J., Salyards, S. and Ali, I. M. (1989). Induced seismicity of the Tarbela reservoir, Pakistan. Seismol. Res. Lett. 60, 185–197.Google Scholar
Imoto, M. (2000). A quality factor of earthquake probability models in terms of mean information gain. Zisin 2 , 53, 79–81.Google Scholar
Imoto, M. (2001). Application of the stress release model to the Nankai earthquake sequence, southwest Japan. Tectonophysics , 338, 287–295.Google Scholar
Jacob, K. H., Pennington, W. D., Armbruster, J., Seeber, L. and Farhatulla, S. (1979). Tarbela Reservoir, Pakistan: a region of compressional tectonic with reduced seismicity upon initial reservoir filling. Bull. Seismol. Soc. Amer. 69, 1175–1192.Google Scholar
Kebeasy, R. M., Maamoun, M., Ibrahim, E., Meagahed, A., Simpson, D. W. and Leith, W. S. (1987). Earthquake studies at Aswan reservoir. J. Geodynamics 7, 173–193.CrossRefGoogle Scholar
Love, A. E. H. (1927). A Treatise on the Mathematical Theory of Elasticity , 4th edn. Cambridge University Press. (Reprinted 1944, Dover Publications.) Google Scholar
Matthews, M. V. (1999). A Brownian passage time model for recurrent earthquakes. Unpublished manuscript.Google Scholar
Nadeem, U. H. (1996). Induced seismicity due to large water reservoir. Individual Studies by Participants IISEE, BRI, Japan , 32, 77–90.Google Scholar
Ogata, Y. (1988). Statistical models for earthquake occurrence and residual analysis for point processes. J. Amer. Statist. Assoc. 83, 9–27.Google Scholar
Reasenberg, P. A. (1985). Second-order moment of central California seismicity, 1969-1982. J. Geophys. Res. 90, 5479–5495.Google Scholar
Shimazaki, K. and Nakata, T. (1980). Time-predictable recurrence model for large earthquakes. Geophys. Res. Lett. 7, 279–282.Google Scholar
Simpson, D. W., Leith, W. S. and Scholz, C. H. (1988). Two types of reservoir-induced seismicity. Bull. Seismol. Soc. Amer. 78, 2025–2040.Google Scholar
Utsu, T. (1961). A statistical study on the occurrence of aftershocks. Geophys. Mag. 30, 521–605.Google Scholar
Vere-Jones, D. (1978). Earthquake prediction–a statistician's view. J. Physics Earth 26, 129–146.Google Scholar
Working Group On California Earthquake Probabilities (1990). Probabilities of large earthquakes in the San Francisco bay region, California. U. S. Geol. Surv. Circ. 1053, 51pp.Google Scholar
Zheng, X. and Vere-Jones, D. (1994). Further applications of the stress release model to historical earthquake data. Tectonophysics 229, 101–121.Google Scholar