Quick Links


Uncertainty Of B-Value Estimation In Connection With Magnitude Distribution Properties Of Small Data SetsNormal access

Authors: K. Leptokaropoulos and A. Adamaki
Event name: Seventh EAGE Workshop on Passive Seismic 2018
Session: PSW Poster Session 2
Publication date: 26 March 2017
DOI: 10.3997/2214-4609.201800052
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 428.92Kb )
Price: € 20

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.

Back to the article list