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Abstract

Summary

Microseismic monitoring can provide important parameters for the evaluation of fracturing, water/gas injection production, and gas storage, etc. in oil and gas energy sector. Due to tiny magnitude and huge number of microseismics, their signals are generally drowned out in the background noise; thus, the traditional seismic location fails, which highlights the large arrived amplitude. Therefore, the methods of probability and statistics have to be used to identify and analyze microseismicity. In the principle and denoise of our vector scanning, we applied the correlation analysis to find the microseismicity, and periodic disturbance from a large number of records. In the real-time automation process of data collation, denoising, and interpretation, we determine the range and/or threshold of characteristic parameters of noise coherent based on data statistics. We also statistically integrate the random spatiotemporal distributions of energy released to suppress the residual and occasional noise coherence, and obtain the space-time geometry of the slit network with high probability connection.

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/content/papers/10.3997/2214-4609.202335015
2023-11-27
2026-01-15

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/content/papers/10.3997/2214-4609.202335015
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Statistics in Vector Scanning for Microseismic
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202335015
/content/papers/10.3997/2214-4609.202335015
/content/papers/10.3997/2214-4609.202335015
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