New dynamic stochastic source encoding combined with a minmax-concave total variation regularization strategy for full waveform inversion
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Release time:2020-08-07 Impact Factor:5.63 DOI number:10.1109/TGRS.2020.2983720 Affiliation of Author(s):School of Geosciences and Info-Physics, Central South University, Changsha 410083, China Teaching and Research Group:Applied Geophysics Journal:IEEE Geoscience and Remote Sensing Letters Place of Publication:United States Funded by:41574116； 41774132； 2018zzts688 Key Words:Dynamic stochastic source encoding；full waveform inversion (FWI)；total variation (TV) regularization model constraint；variable-density acoustic equation Abstract:To address problems, such as the computationally intensive inversion requirements, low inversion efficiency, and inadequate inversion accuracy caused by multiparameter cross-talk in a synchronous inversion, a new dynamic stochastic source encoding strategy combined with minmax-concave total variation (MCTV) regularization model constraints was proposed. This strategy avoids crosstalk noise between shots caused by the algorithm and greatly improves the inversion efficiency without affecting the inversion accuracy. By comparing a "cross"-shaped model with the multiparameter inversion results, we found that the MCTV regularization strategy boasts the best inversion effect. We further showed that dynamic stochastic source encoding can increase the inversion efficiency threefold by applying the 1994 British Petroleum (BP) migration international standard topography model and establishing a function to evaluate the most efficient inversion strategy from among seven options. Compared with the traditional stochastic source encoding strategies, dynamic stochastic source encoding was shown to better suppress crosstalk noise. The proposed strategy also presented a higher acceleration ratio; additionally, combining this strategy with MCTV regularization model constraints provided the clearest reconstructed image with the highest inversion precision and obtained the best evaluation score among the considered inversion strategies, albeit with a slight reduction in the total elapsed time-acceleration ratio. Index Terms-Dynamic stochastic source encoding, full wave-form inversion (FWI), total variation (TV) regularization model constraint, variable-density acoustic equation. Co-author:王向宇 First Author:冯德山 Indexed by:Applied Research Correspondence Author:王珣 Document Code:DOI：10.1109/TGRS.2020.2983720 Discipline:地质资源与地质工程 Document Type:J Page Number:1~19 ISSN No.:1545-598X Translation or Not:no Date of Publication:2020-04-13 Included Journals:SCI -
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