Time-Frequency Representation of Microseismic Signals using the Synchrosqueezing Transform
This work addresses the need for improved time-frequency analysis in microseismic monitoring for applications like hydraulic fracturing and CO2 sequestration, but it is incremental as it applies an existing method to a specific domain.
The paper tackled the problem of accurately representing time-frequency information in microseismic signals, which is crucial for interpreting resonance frequencies during fracturing or CO2 management, by applying the synchrosqueezing transform to overcome limitations of existing methods like STFT and wavelet analysis, showing its potential for seismic signal processing.
Resonance frequencies can provide useful information on the deformation occurring during fracturing experiments or $CO_2$ management, complementary to the microseismic event distribution. An accurate time-frequency representation is of crucial importance prior to interpreting the cause of resonance frequencies during microseismic experiments. The popular methods of Short-Time Fourier Transform (STFT) and wavelet analysis have limitations in representing close frequencies and dealing with fast varying instantaneous frequencies and this is often the nature of microseismic signals. The synchrosqueezing transform (SST) is a promising tool to track these resonant frequencies and provide a detailed time-frequency representation. Here we apply the synchrosqueezing transform to microseismic signals and also show its potential to general seismic signal processing applications.