A technique of noise suppression used f-x deconvolution and the wavelet transform allows reducing jump edges in the phase noise of distributed acoustic sensing. The DAS system has been already tested and demonstrated great results of high performance in terms of increasing the quality level of seismic waves. Distributed acoustic sensing provides relatively stable phase sensitivity as well as better the signal-to-noise ratio, leading to more remarkable features of seismic wave signals.
To be more precise, distributed fiber optic sensing based on Rayleigh scattering is not new and used in various applications to control current assets and employ new resources. It is possible to apply such DAS systems to provide efficient and comparatively inexpensive development of perimeter security systems and produce defensive redundancy.
Different methods have been used to apply Rayleigh scattering in the development of distributed fiber optic sensors. For instance, a distributed sensing technology of optical time-domain reflectometry (OTDR) was used for the first time over three decades ago. Nowadays a noise suppression technique based on f-x deconvolution and the wavelet transform is considered to be the most efficient for distributed acoustic sensors.
The thing is that f-x deconvolution is regarded as a traditional technique of seismic data processing. The application includes the treatment of seismic signals by fiber optic sensors as a two-dimensional (2D) image in terms of time and channel. The DAS system enables us to extract the signal characteristics of each channel with a comparatively stable noise distribution between channels.
Usually, such techniques as deconvolution or the wavelet transform are applied separately in traditional seismic noise processing but here these techniques are combined in distributed sensing technology to minimize the number of wavelet transform layers and reach effective low-frequency noise suppression. The DAS system offers such benefits as comparatively stable phase sensitivity over the whole sensing range, the reduction of jump edges in phase noise, and more evident features of seismic wave signals.
The operating principle of distributed acoustic sensing used f-x deconvolution is based on “the assumption that desired signals are continuous and predictable whereas random noise is incoherent and unpredictable.” DAS sensors are actively used for oil and gas exploration. Thus, the noise compression technique improves the phase noise performance of the DAS system. Moreover, the jump edges from the noise of fiber optic sensors are reduced with the same peaks and valleys compared to the original signals which play a crucial role in calculating the time delay of peaks and valleys between various channels.
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