Least-squares joint imaging of primaries and pegleg multiples: 2-D field data test
نویسنده
چکیده
In this paper I present an improved least-squares joint imaging algorithm for primary reflections and pegleg multiples (LSJIMP) which utilizes improved amplitude modeling and imaging operators presented in two companion papers in this report (Brown, 2003b,a). This algorithm is applied to the entire Mississippi Canyon 2-D multiples test dataset and demonstrates a good capability to separate pegleg multiples from the data.
منابع مشابه
Least-squares joint imaging of multiples and primaries
Multiple reflections contain subsurface reflectivity information which often complements that found in primary reflections. Previous attempts to combine the additional information by summing prestack images of the primaries and multiples have generally failed because of crosstalk leakage between the images. We present a general linear least-squares inversion method, Least-Squares Joint Imaging ...
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My Least-squares Joint Imaging of Multiples and Primaries (LSJIMP) algorithm (Brown, 2003b) separates pegleg multiples and primaries. LSJIMP computes separate images of the peglegs and primaries, and then uses the mutual consistency of the images to discriminate against unwanted noise types in each image. The images must be consistent in two respects: kinematics and amplitudes. A companion pape...
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