Multiple noise reduction for distributed acoustic sensing data ...

DCRCDNet shows great potential in reconstructing DAS signals from hidden noise, suppressing strong and mixed noise, and extracting hidden signals.

We develop a supervised learning-based densely connected residual convolutional denoising network (DCRCDNet), which leverages both encoding and decoding ...

(PDF) Multiple Noise Reduction for Distributed Acoustic Sensing ...

Multiple Noise Reduction for Distributed Acoustic Sensing Data Processing through Densely Connected Residual Convolutional Networks · Abstract.

Multiple Noise Reduction for Distributed Acoustic Sensing Data ...

noise and extracting hidden signals. 24. Key words: Distributed acoustic sensing, seismic survey, supervised learning, encoding and decoding.

Removing multiple types of noise of distributed acoustic sensing ...

However, the application of attention mechanism in seismic data processing is limited. Inspired by this, we apply ADNet for DAS seismic noise suppression. The ...

A Novel Iterative PA-MRNet: Multiple Noise Suppression and Weak ...

With the goal of obtaining high-quality downhole distributed acoustic sensing (DAS) data from multiple types of complex noise, ...

Multiple Noise Reduction for Distributed Acoustic Sensing Data ...

Abstract Distributed acoustic sensing (DAS), which utilizes the entire optical fiber as the sensing medium, provides distinct advantages of high resolution, ...

Multi-source aliasing suppression for distributed fiber acoustic ...

... sensor noise is neglected for simplification. On the far-field condition [29], the amplitude response of each sensing element is consistent, gi=g. Δri=ri−r ...

Simultaneous denoising and reconstruction of distributed acoustic ...

artificial intelligence, borehole geophysics, distributed acoustic sensors, data reconstruction, noise ... two kinds of special noise ...

Background noise suppression for DAS-VSP data using attention ...

Distributed Acoustic Sensing (DAS) has emerged as a widely used technology in various applications, including borehole.

Noise attenuation in distributed acoustic sensing data using a ...

However, these traditional denoising methods suffer from signal leakage and are not well suited for all the complex noise found in DAS data. Several supervised ...

Multiple noise reduction for distributed acoustic sensing data ... - OUCI

Multiple noise reduction for distributed acoustic sensing data processing through densely connected residual convolutional networks · Tianye Huang · Aopeng Li ...

Multiple noise reduction for distributed acoustic sensing data ...

Multiple noise reduction for distributed acoustic sensing data processing through densely connected residual convolutional networks. Tianye Huang. Aopeng Li.

Removing multiple types of noise of distributed acoustic sensing ...

Therefore, for the purpose of effectively improving the signal-to-noise ratio (SNR) of DAS seismic data, we introduce a denoising network named attention-guided ...

SelfMixed: Self-supervised Mixed Noise Attenuation for Distributed ...

Distributed acoustic sensing (DAS) is an emerging data acquisition technique known for its high sensing density, cost-effectiveness, ...

SelfMixed: Self-supervised mixed noise attenuation for distributed ...

ABSTRACTDistributed acoustic sensing (DAS) is an emerging data acquisition technique known for its high sensing density, cost effectiveness, ...

Removing Instrumental Noise in Distributed Acoustic Sensing Data

We present a comparison between two deep learning approaches to address DAS hardware noise and enhance the quality of DAS data. These approaches have the ...

US10401519B2 - Noise removal for distributed acoustic sensing data

The second coupler 208 may split light from the optical fiber 232 into two paths along interferometer arm 224 and interferometer arm 222. In other words, the ...

Denoising distributed acoustic sensing data using unsupervised ...

Our network uses several encoders and decoders to ... Distributed acoustic sensing coupling noise removal based on sparse optimization.

machine learning distributed acoustic sensing DAS signal denoising ...

However, in many applications, it can be difficult or even impossible to acquire sufficient quantities of noise-free or high signal-to-noise ...