Least-squares reverse time migration of marine data with frequency-selection encoding
Author(s) -
Wei Dai,
Yunsong Huang,
Gerard T. Schuster
Publication year - 2013
Publication title -
king abdullah university of science and technology repository (king abdullah university of science and technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1190/segam2013-0412.1
Subject(s) - computer science , encoding (memory) , seismic migration , algorithm , selection (genetic algorithm) , frequency domain , limiting , least squares function approximation , artificial intelligence , mathematics , computer vision , geology , engineering , statistics , mechanical engineering , estimator , seismology
The phase-encoding technique can sometimes increase the efficiency of the least-squares reverse time migration (LSRTM) by more than one order of magnitude. However, traditional random encoding functions require all the encoded shots to share the same receiver locations, thus limiting the usage to seismic surveys with a fixed spread geometry. We implement a frequency-selection encoding strategy that accommodates data with a marine streamer geometry. The encoding functions are delta functions in the frequency domain, so that all the en- coded shots have unique non-overlapping frequency content, and the receivers can distinguish the wavefield from each shot with a unique frequency band. Since the encoding functions are orthogonal to each other, there will be no crosstalk between different shots during modeling and migration. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is compara- ble to conventional RTM for both the Marmousi2 model and a marine data set recorded in the Gulf of Mexico. With more iterations, the LSRTM image quality is further improved. We conclude that LSRTM with frequency-selection is an efficient migration method that can sometimes produce more focused images than conventional RTM
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