New prognostic technology for analysis of low-frequency seismic noise variations (on the example of the Russian Far East)

Abstract

A new technology for predicting strong earthquakes with a magnitude range of Mw about 7 and more is considered, based on the use of continuous recordings of seismic noise on a network of 21 broadband stations of the GS RAS in the region of the Kamchatka Peninsula, the Commander Islands and the Paramushir Island. The article is described a forecasting algorithm created by A.A. Lyubushin, IPE RAS, and the state of its implementation in the Kamchatka Division GS RAS for the purpose of an advance (months - first years) assessment of the strong earthquakes preparation sites. The data processing algorithm includes the calculation of four noise statistics time series for each station and the construction of their spatial distribution maps for different time intervals. We used four noise statistics, including the minimal entropy of the orthogonal wavelet coefficients squares and three characteristics of the multifractal spectrum of singularity – the generalized Hurst exponent, the carrier width, and the spectral wavelet exponent. Based on previous research, characteristic features of the four seismic noise statistics behavior at preparation stages of the local earthquakes 2013-2016 with Мw=6.6-8.3 were revealed, corresponding to similar changes before the two earthquakes with Мw=8.3 and 9.0 in Japan. It was found that an increase in the danger of a strong earthquake is accompanied by an increase in minimal entropy and a decrease in the carrier width and other parameters of the singularity spectrum. Since 2020, the processing of current data from the network of broadband stations of the GS RAS in the Far East region has been carried out in accordance with the seismic forecasting algorithm for drawing up quarterly forecast conclusions, which are sent to the Russian Expert Council on Earthquake Forecasting, Seismic Hazard and Risk Assessment (REC) and to Kamchatka Branch of REC