با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
---|---|---|
1 |
Subsurface velocity inversion from deep learning-based data assimilation
وارونگی سرعت زیرسطحی از جذب داده های مبتنی بر یادگیری عمیق-2019 Data assimilation haswidespread applications inmeteorology and oceanography. This paper applies data assimilation
for seismic exploration. Comparing with full waveform inversion, the distrust of the prior velocity information
is preserved, to avoid the local minima caused by its inaccuracy. Prior velocity information is scarce in
seismic exploration, but the introduction of deep learningmethods makes it possible, to correct the major defects
in the application of data assimilation in seismic velocity inversion. Finally, we design a simple salt body model,
and we introduce deep learning to obtain prior velocity information and drive data assimilation for highprecision
inversion of subsurface velocity. It is compared with the traditional full waveform inversion, to prove
the effectiveness and advantages of this new process. Keywords: Deep learning | Data assimilation | Full waveform inversion | Prior velocity information |
مقاله انگلیسی |