TY - GEN

T1 - Uncertainty of B-value estimation in connection with magnitude distribution properties of small data sets

AU - Leptokaropoulos, K.

AU - Adamaki, A.

PY - 2018

Y1 - 2018

N2 - We evaluate the efficiency of the maximum likelihood estimator introduced by Aki (1965), using synthetic datasets exhibiting diverse but well defined properties. The deviation of the b-value estimation from its real value is quantified by Monte Carlo simulations as a function of catalogue features and data properties such as the sample size, the magnitude uncertainties distribution, the round-off interval of reported magnitude values and the magnitude range. Within the objective of this study, algorithms have been compiled for the determination of such observational-theoretical deviations and to facilitate the construction of nomograms corresponding to diverse cases of input parameters. In this way, a more accurate estimation of the uncertainty level for the b-value and MC determination can be achieved, contributing to a more robust seismic hazard assessment, especially at low activity areas and induced seismicity sites. Our results indicate that b-value analysis, especially for small datasets should be carried out together with Magnitude range analysis. Nomograms should be constructed and adjusted to each particular case study in order to achieve a more accurate estimation of the b-value and the corresponding uncertainty.

AB - We evaluate the efficiency of the maximum likelihood estimator introduced by Aki (1965), using synthetic datasets exhibiting diverse but well defined properties. The deviation of the b-value estimation from its real value is quantified by Monte Carlo simulations as a function of catalogue features and data properties such as the sample size, the magnitude uncertainties distribution, the round-off interval of reported magnitude values and the magnitude range. Within the objective of this study, algorithms have been compiled for the determination of such observational-theoretical deviations and to facilitate the construction of nomograms corresponding to diverse cases of input parameters. In this way, a more accurate estimation of the uncertainty level for the b-value and MC determination can be achieved, contributing to a more robust seismic hazard assessment, especially at low activity areas and induced seismicity sites. Our results indicate that b-value analysis, especially for small datasets should be carried out together with Magnitude range analysis. Nomograms should be constructed and adjusted to each particular case study in order to achieve a more accurate estimation of the b-value and the corresponding uncertainty.

UR - http://www.scopus.com/inward/record.url?scp=85049202221&partnerID=8YFLogxK

M3 - Paper in conference proceeding

AN - SCOPUS:85049202221

T3 - 7th EAGE Workshop on Passive Seismic 2018

BT - 7th EAGE Workshop on Passive Seismic 2018

PB - European Association of Geoscientists and Engineers

T2 - 7th EAGE Workshop on Passive Seismic 2018

Y2 - 26 March 2018 through 29 March 2018

ER -