1 code implementation • 7 Feb 2017 • Lijun Zhu, Lindsay Chuang, James H. McClellan, Entao Liu, Zhigang Peng
In the presence of background noise, arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location estimation.
no code implementations • 6 Dec 2016 • Entao Liu, Lijun Zhu, Anupama Govinda Raj, James H. McClellan, Abdullatif Al-Shuhail, SanLinn I. Kaka, Naveed Iqbal
Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery.
no code implementations • 16 Nov 2015 • Lingchen Zhu, Entao Liu, James H. McClellan
It has been attacked successfully with the Gauss-Newton method and sparsity promoting regularization based on fixed multiscale transforms that permit significant subsampling of the seismic data when the model perturbation at each FWI data-fitting iteration can be represented with sparse coefficients.