Simultaneous estimation of shape factor and depth of subsurface cavities from residual gravity anomalies using feed-forward back-propagation neural networks

Hajian, Alireza; Zomorrodian, Hossein; Styles, Peter

doi:10.2478/s11600-012-0049-1

Cited by 12 publications

(2 citation statements)

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“…Neural network application has gained popularity in geophysics during the past decades (Hajian et al 2012;Baan and Jutten 2000). In reflection seismology, however, except for the cases relating to the interpretation and classification of seismic attributes, it seems that soft computations and artificial intelligence are not widely used in processing of seismic data.…”

Section: Introductionmentioning

confidence: 99%

“…Real stacked data recorded in Australia, b result of AWF, and c result of ANN filtering performance will differ even with the same inputs, outputs, and network architecture Hajian et al (2012). used mean squared error between outputs and targets as the performance indicator of the trained network and averaged these performance values over 10 iterations for each quantity of nodes in the hidden layer.…”

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confidence: 99%

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Seismic random noise attenuation using artificial neural network and wavelet packet analysis

et al. 2016

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In this paper, we present a method for attenuating background random noise and enhancing resolution of seismic data, which takes advantage of semi-automatic training of feed forward back propagation (FFBP) artificial neural network (ANN) in a multiscale domain obtained from wavelet packet analysis (WPA). The images of approximations and details of the input seismic sections are calculated and utilized to train neural network to model coherent events by an automatic algorithm. After the modeling of coherent events, the remainder data are assumed to be related to background random noise. The proposed method is applied on both synthetic and real seismic data. The results are compared with that of the adaptive Wiener filter (AWF) in synthetic shot gather and real common midpoint gather and also with that of band-pass filtering on real common offset gather. The comparison indicates substantially higher efficiency of the proposed method in attenuating random noise and enhancing seismic signals.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%