Method for estimation of near-surface sedimentary rock state based on the results of observations of geoacoustic emission dynamic characteristics

The technology of observations of the near-surface sedimentary rock state is developed and realized in IKIR FEB RAS since 2003. It is based on the results of geoacoustic emission signal processing and analysis. The relation between the degree of stress-strain state of sedimentary rocks and pulse flux intensity in geoacoustic emission signal has been discovered before. Continuous measurements of geoacoustic emission pulse flux intensity, pulse form and their distributions are carried out. The final aim of the investigations is the development of methods for analysis of the observed anomalies of geoacoutic emission signal characteristics to detect their relation with the probability of earthquake occurrences. At the current stage of the research, a probabilistic model of GAE signal formation in the near-surface sedimentary rocks at the reception site is presented. The model makes it possible to describe the changes in the nearsurface sedimentary rocks state based on the results of estimations of the changeability of pulse duration distribution pattern and that of their amplitudes taking into account the update of the model for signal formation at the receiving device input. The results of computational experiments with natural signals of geoacoustic emission, confirming the changes made in the model of GAE signal formation. Implementation of the research results into the observation practice makes it possible to improve the quality of real-time observations of the changes in the near-surface sedimentary rock state without expensive and laborious methods of direct measurements. Time changes in the following characteristics of GAE are considered: changes in pulse duration and diversity of their amplitude-phase modulation in a moving time window of different duration. The result is achieved by visual representation of GAE signal characteristics in the form of three-dimensional images of statistical distributions of pulse duration and amplitudes mapped on a graph at defined time intervals. Such a representation allows one to see the occurring anomalies in GAE signal characteristics parameters and to classify the observed anomalies. In the future, that will allow to connect the detected anomalies with certain seismic events and to distinguish them from the anomalies occurring under climatic and seasonal factors impact.