Abstract
The arrival time of a microseismic event is an important piece of information for microseismic monitoring. The accuracy and efficiency of arrival time identification is affected by many factors, such as the low signal-to-noise ratio (SNR) of the records, the vast amount of real-time monitoring records, and the abnormal situations of monitoring equipment. In order to eliminate the interference of these factors, we propose a method based on phase-only correlation (POC) to estimate the relative arrival times of microseismic events. The proposed method includes three main steps: (1) The SNR of the records is improved via time-frequency transform, which is used to obtain the time-frequency representation of each trace of a microseismic event. (2) The POC functions of all pairs of time-frequency representations are calculated. The peak value of the POC function indicates the similarity of the traces, and the peak position in the time lag axis indicates the relative arrival times between the traces. (3) Using the peak values as weighting coefficients of the linear equations, consistency processing is used to exclude any abnormal situations and obtain the optimal relative arrival times. We used synthetic data and field data to validate the proposed method. Comparing with Akaike information criterion (AIC) and cross-correlation, the proposed method is more robust at estimating the relative arrival time and excluding the influence of abnormal situations.
Highlights
IntroductionMicroseismic monitoring is widely used to predict rockbursts in coal mining, minimize the risks of CO2 leakage, characterize geothermal energy reservoir, and evaluate hydraulic fracturing [1,2,3,4,5,6,7,8]
Microseismic monitoring is widely used to predict rockbursts in coal mining, minimize the risks of CO2 leakage, characterize geothermal energy reservoir, and evaluate hydraulic fracturing [1,2,3,4,5,6,7,8].The arrival time of microseismic event is an important piece of information of microseismic monitoring for phase identification, source location, source mechanism analysis, and microseismic interpretation [9,10,11,12,13]
The peak values of the phase-only correlation (POC) functions are added into Equation (7) (shown as Equation (8))
Summary
Microseismic monitoring is widely used to predict rockbursts in coal mining, minimize the risks of CO2 leakage, characterize geothermal energy reservoir, and evaluate hydraulic fracturing [1,2,3,4,5,6,7,8]. The ratio of the short-term average over long-time average (STA/LTA) is the most commonly used algorithm for identifying arrival times [15] This method is sensitive to background noise and the length of the window [16]. We propose a new method based on phase-only correlation (POC) to estimate the relative arrival times of downhole microseismic data. Coherence-based methods can be used to pick the relative arrival times with the information of multi-trace records [40,41,42]. The proposed method applies POC to estimate the relative arrival time. POC evaluates the similarity level by calculating the peak value of the cross-phase spectrum of two two-dimensional (2D) images. We used synthetic data and a high signal-to-noise ratio (SNR) microseismic event to validate the proposed method. The phase-only correlation (POC) function between f (n, w) and g(n, w) the peak value of the POC function rf g (n, ω )
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