.png){kind=icon}
.png){kind=icon}
Return
Probabilistic imaging location method for microseismic source based on variable gaussian distribution function
.png){kind=icon}
PRE
AI
DOI：10.6038/cjg2025t0254.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
High-precision source localization is essential for microseismic monitoring. While picking-based localization methods are widely used across different scales, their performance is often compromised by errors in first-arrival time picking. Localization based on station-pair-derived Equal Differential Time (EDT) surfaces offers an effective means to mitigate such errors. However, conventional EDT approaches typically adopt fixed widths or predefined probability distribution functions, limiting the ability of probabilistic imaging methods to simultaneously achieve high resolution and accuracy. This paper introduces a novel adaptive probabilistic imaging localization method based on a variable Gaussian distribution function, which incorporates the correlation between first-arrival picking errors and the signal-to-noise ratio (SNR) of microseismic signals. Specifically, the SNR of seismic waveforms is first estimated. Then, the variance of the Gaussian distribution is adaptively adjusted according to the SNR: For station pairs with high-SNR differential arrival-time data, the variance is reduced so that the EDT-distribution function converges more rapidly, thereby reducing probability values assigned to non-potential source locations; For station pairs with low SNR differential arrival-time data, a larger variance is applied to yield a heavier tail, preserving higher probability values near the true source location. The final localization is obtained using the product-form probabilistic imaging function. Both theoretical analysis and synthetic tests demonstrate that the proposed variable Gaussian distribution significantly enhances localization resolution and accuracy. Application to real microseismic data from a mining site further validates the method's effectiveness, indicating its strong potential for improving the reliability and precision of microseismic event localization.
Keywords:
Source localization
Equal Differential Time (EDT) surface
Variable Gaussian distribution function
Probabilistic imaging
Signal-to-noise ratio (SNR)
Journal
C
IF:
1.4
Papers:
205
Citations:
0
View more organizations