Microseismic Event Localization via Least-squares Full Waveform Inversion with Group Sparsity Constraints

References

1. Beck, A. and Teboulle, M.
   [2009] A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM journal on imaging sciences, 2(1), 183–202.
   [Google Scholar]
2. Fornasier, M. and Rauhut, H.
   [2008] Recovery algorithms for vector-valued data with joint sparsity constraints. SIAM Journal on Numerical Analysis, 46(2), 577–613.
   [Google Scholar]
3. Iamali-Rad, H., Tang, Z., Campman, X., Droujinine, A. and Leus, G.
   [2015] Research Note: Sparsity-Aware Multiple Microseismic Event Localization Blind to the Source Time-Function. Geophysical Prospecting, 63(1), 70–77.
   [Google Scholar]
4. Ii, I.
   [2009] An exact adjoint operation pair in time extrapolation and its application in least-squares reverse-time migration. Geophysics, 74(5), H27–H33.
   [Google Scholar]
5. Leaney, W.S.
   [2008] Inversion of microseismic data by least-squares time reversal and waveform fitting. SEG Technical Program Expanded Abstracts 2008, 1347–1351.
   [Google Scholar]
6. Malioutov, D., Çetin, M. and Willsky, A.S.
   [2005] A sparse signal reconstruction perspective for source localization with sensor arrays. IEEE Transactions on Signal Processing, 53(8), 3010–3022.
   [Google Scholar]
7. Menon, R. and Gerstoft, R
   [2013] High resolution beamforming using sparse recovery from sensor array data. The Journal of the Acoustical Society of America, 133(5), 3579–3579.
   [Google Scholar]
8. Rodriguez, I.V., Sacchi, M.D. and Gu, Y.J.
   [2010] Continuous hypocenter and source mechanism inversion via a Green’s function-based matching pursuit algorithm. The Leading Edge, 29(3), 334–337.
   [Google Scholar]
9. Rodriguez, I.V., Sacchi, M.D. and Gu, Y.J.
   [2012a] A compressive sensing framework for seismic source parameter estimation. Geophysical Journal International, 191(3), 1226–1236.
   [Google Scholar]
10. Rodriguez, I.V., Sacchi, M.D. and Gu, Y.J.
    [2012b] Simultaneous recovery of origin time, hypocentre location and seismic moment tensor using sparse representation theory. Geophysical Journal International, 188(3), 1188–1202.
    [Google Scholar]