
UPNet is a novel uncertainty-based picking deep learning network that not only estimates the uncertainty of network output but also can filter the pickings with low confidence, achieving higher accuracy and robustness than deterministic DNN-based models in first break picking tasks.


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upnet-a-robust-first-break-picking-deep-learning-network-with-uncertainty-quantification


UPNet: A Robust First Break Picking Deep Learning Network with Uncertainty Quantification


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This paper introduces and compares several approaches to efficiently compress all matrices within the linear system of multidimensional deconvolution, significantly improving the solution efficiency, including algorithms based on global low-rank and block low-rank approximations.


efficient-compression-techniques-for-multidimensional-deconvolution-in-seismic-exploration


Efficient Compression Techniques for Multidimensional Deconvolution in Seismic Exploration
