... Seismic data is contaminated by random noise, which decreases the accuracy of subsequent seismic data processing. Therefore, random noise attenuation is an important step to improve the signal-to-noise ratio (SNR) of seismic data. We design a Deep Image Prior (DIP) network architecture based...

... The density-based spatial clustering application with noise (DBSCAN) along with the super-virtual refraction interferometry (SVI) are used to pick the first arrivals’ traveltimes. DBSCAN alone suffers if the signal-to-noise ratio (SNR) of the data is poor. To overcome this drawback, SVI is used...

... ellmauthaler topology snr scenario Distributed Acoustic Sensing of Long Subsea Tie-Backs Glenn A. Wilson*, Halliburton, Brian C. Seabrook, ExxonMobil Upstream Research Company, Sigurd Moe, TechnipFMC, Kwang Suh, Mikko Jaaskelainen, Andreas Ellmauthaler, Jeff Bush, Halliburton, and James Dupree...

... Designing seismic acquisition is a blend of science and art, especially in a desert environment with low signal-to-noise ratios (SNR) of -20 to -60 dB. Basic design driven by the square-root model may be overly simplistic. At the same time, conventional numerical feasibility studies are lengthy...

... Dense spatial sampling (∼1m) and low signal-to-noise ratio (SNR) are typical features of distributed acoustic sensing (DAS) data. We have developed a wavelet stacking method to attenuate DAS noise without compromising data bandwidth. Wavelet stack consists of two steps, adaptive nonlinear...

... artificial intelligence sb array borehole geophone sub array exploration geophysicist 10 reservoir characterization microseismic monitoring superstation array expanded abstract shallow borehole array channel count sensor machine learning upstream oil & gas reference array snr geophone...

... effective capability to attenuate random noise. neural network seismic data machine learning deep learning applied geoscience snr noise-free label reservoir characterization upstream oil & gas deconvolution noisy data denoised deep learning method china noise bandpass zhang...

... and because they are more controllable and efficient than airgun arrays. In this paper we discuss the optimal design of marine vibrator sweeps for ocean-bottom seismic surveys using a sweep generation approach guided by signal-to-noise ratio (SNR). As example, we use the SNR estimated from ocean bottom...

..., and the signal-to-noise ratios (SNR) are significantly improved. Synthetic data and real data experiments prove the effectiveness of our method. reservoir characterization seismic data tsinghua university machine learning upstream oil & gas training set module noisy data neural network...

...) as a coherency We present an approach for quality control (QC) of massive measure. The most critical metric for seismic data quality prestack land seismic datasets, focusing on evaluating data control is the SNR. An SNR is typically defined as the ratio enhancement procedures critical for processing success...

... 20 f=2 f=4 f=6 0 (a) 0 (b) 15 f=8 1 1 SNR (dB) 10 2 2 3 3 5 Time (s) Time (s) 4 0 20O00ffset40(m00) 6000 4 0 20O00ffset40(m00) 6000 0 0 (c) 0 (d) 5 1 1 2 2 p0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 3 3 Figure 3: Signal-to-noise ratio calculated by robust matching Time (s) 4 0 20O00ffset40(m00...

... Presentation Type: Oral artificial intelligence reservoir characterization seismic data iteration synthetic seismic trace anti-noise ability upstream oil & gas seismic inversion exploration geophysicist 10 fixed-point seismic inversion reflection coefficient p-wave impedance snr seg...

... 10 snr das vsp data wavefield separation das data geophone data seg international exposition rms velocity vertical seismic profile reservoir surveillance upstream oil & gas gauge length fbp decimation saudi aramco suppression Influence of gauge length on DAS VSP data...

... Presentation Type: Oral deeply-towed marine seismic vibrator-comparative study msv marine vibratory source vibrator annual international meeting upstream oil & gas seg international exposition snr reservoir characterization survey data multichannel predictive deconvolution airgun array...

... ABSTRACT Microseismic monitoring aims at detecting as weak events as possible by maximizing the signal-to-noise ratio (SNR) of the detection parameters. Whilst the signal depends on a priori unknown source radiation and propagation effects, the noise levels on the receivers can be measured...

... specialized curvelet transform specialized transform reservoir characterization snr time-frequency analysis rotation equation wavelet transform coefficient curvelet coefficient seg international exposition upstream oil & gas curvelet transform information frequency frequency slice seismic...

... ABSTRACT Noise mitigation techniques and preferred practices are presented for surface-based controlled source electromagnetic (CSEM) monitoring of hydraulic fracturing operations. Distinct forms of noise encountered in oilfields that degrade the signal-to-noise ratio (SNR) can be caused...

..., quantitative and efficient method that takes into account the influence of noises. In this paper, the resolution of raw and imaging data is quantified indirectly by the SNR in the frequency domain; the application of this method in the actual data of multiple research fields is introduced; the actual...

...: Poster reservoir characterization real-time quality control geophone array application vibrator digital geophone digital sensor operation acquisition technology upstream oil & gas resolution acquisition point-receiver acquisition annual meeting seg international exposition snr...

... Date: Tuesday, October 16, 2018 Start Time: 9:20:00 AM Location: Poster Station 3 Presentation Type: Poster random noise noise attenuation classification architecture deep learning annual meeting international conference seg international exposition zhang snr wavelet artificial...