Estimating observation error covariance matrix of seismic data from a perspective of image denoising

DOI10.1007/s10596-016-9605-0zbMath1381.86022OpenAlexW2558028285MaRDI QIDQ1702361

Tuhin Bhakta, Xiao-Dong Luo

Publication date: 28 February 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-016-9605-0

zbMATH Keywords

image denoisingdata assimilationseismic history matchingobservation error covariance matrix

Mathematics Subject Classification ID

Seismology (including tsunami modeling), earthquakes (86A15) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Geostatistics (86A32)

Related Items (4)

Simultaneous assimilation of production and seismic data: application to the Norne field ⋮ Marginalized iterative ensemble smoothers for data assimilation ⋮ A robust adaptive iterative ensemble smoother scheme for practical history matching applications ⋮ Model Error Estimation Using the Expectation Maximization Algorithm and a Particle Flow Filter

Cites Work

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• Ridgelets: a key to higher-dimensional intermittency?
• A Review of Image Denoising Algorithms, with a New One
• Noise reduction by wavelet thresholding

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