%0 Conference Paper
%A Leptokaropoulos, Konstantinos Michail
%A Adamaki, Aggeliki K.
%A Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland,
%A Department of Earth Sciences, Uppsala University, Sweden,
%B 7 th EAGE Workshop on Passive Seismic,
%C Kraków, Poland
%D 2018
%F epos:2064
%T Uncertainty of b-value Estimation in Connection with Magnitude Distribution Properties of Small Data Sets
%U https://episodesplatform.eu/eprints/2064/
%X 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.