Abstract
Coal seam hydraulic fracturing (CSHF) has recently been applied to mitigate frequent regional rockburst risk in deep mines before mining practice, as an effective substitute for conventional labor-intensive and time-consuming rockburst prevention measures. Due to the complex nature of CSHF microseismic signals—e.g., nonstationary, transient, and low signal-to-noise ratio—conventional denoising methods tend to yield undesirable results that may preclude reliable evaluation of hydraulic fracturing performance using microseismic data. We propose an advanced denoising method MWPT-IHHT to achieve twice denoising in a fine and adaptive manner. This method combines a multithreshold wavelet packet transform (MWPT) and an improved Hilbert-Huang transform (IHHT), with each being improved compared to their conventional counterparts. A quantitative comparison using synthetic signals suggests the outperformance of the proposed method over the commonly used denoising methods in suppressing noises in terms of signal-to-noise ratio, signal similarity, and energy percentage. The desirable denoising results of two typical real CSHF signals in a CSHF test at Huafeng Coal Mine further demonstrate the applicability and effectiveness of the proposed MWPT-IHHT method.
Highlights
With coal resources being continuously extracted for decades, a great number of coal mines in China have entered into deep mining, and as a result, rockbursts have become one of the most dangerous dynamic hazards, causing tremendous economic losses and casualties [1,2,3,4,5]
This paper aims to extend and further develop the denoising method for Coal seam hydraulic fracturing (CSHF) signals by combining a multithreshold wavelet packet transform (MWPT) and an improved Hilbert-Huang transform (IHHT), with each being improved compared to the conventional methods and combined for twice denoising
MWPT-IHHT denoising method employs a multithreshold wavelet packet transform to implement preliminary denoising and an improved Hilbert-Huang transform for a second denoising. e combination of MWPT and IHHT, with each being improved compared to their conventional counterparts, can significantly enhance the time-frequency localization and allow complex signals (CSHF signal) to be processed in a fine and adaptive manner
Summary
With coal resources being continuously extracted for decades, a great number of coal mines in China have entered into deep mining, and as a result, rockbursts have become one of the most dangerous dynamic hazards, causing tremendous economic losses and casualties [1,2,3,4,5]. Conventional rockburst prevention measures that involve a small volume, e.g., destress drilling and destress blasting, have long been applied and can effectively control local rockbursts in highly stressed zones These measures are both laborintensive and time-consuming, which renders them less suitable for deep mines subjected to frequent rockburst hazards. Erefore, a cost-effective technique for regional rockburst prevention is urgently needed To this end, hydraulic fracturing, initially used for oil and gas stimulation and in situ stress measurement [7,8,9], has recently been applied to mitigate frequent rockburst risk in deep mines through preconditioning hard roofs and coal seams before mining practice [6, 10,11,12]. Further development of this technique has been restricted due to the absence of a mine-specific method for evaluating the hydraulic fracturing performance using microseismic monitoring data, and guidelines for determining appropriate design parameters for hydraulic fracturing treatment are underdeveloped
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