FIG. 2. Left: Impedance inversion result using the measured physical modeling data without frequency extrapolation. Low frequencies are lacking in the measured data, leading to a lack of absolute impedance changes in the result. Right: Impedance inversion using the measured physical modeling data after frequency extrapolation. While significant artifacts and other problems remain, there is significant improvement over the pre-extrapolation result. Interpolation of seismic data using a principal component analysis POCS approach Scott Keating and Kris Innanen ABSTRACT Projection onto convex sets, or POCS, is a simple, straightforward method of interpolation which hinges on a few basic assumptions. In order to better fulfill these assumptions, a type of POCS is proposed in which a projection onto principal components is the transform used. This method is shown to be effective both on simple synthetic data, as well as on real VSP data. The problem of acquiring the relevant principal components is addressed by using nearby intact data, and other methods are proposed if this should prove impractical. Partially incomplete data are shown to provide adequate principal components for interpolation in some cases. FIG. 1. Left: Shot gather for VSP data with 30% of traces removed. Right: Data after PCA POCS interpolation, using principal components of nearby, incomplete shot gathers. Nonstationary L1 adaptive subtraction and application to inverse scattering multiple attenuation Scott Keating*, Jian Sun, Pan Pan, Kris Innanen ABSTRACT A method for adaptive subtraction in conjunction with internal multiple prediction by inverse scattering series is investigated. An L1, nonstationary adaptive subtraction is found to minimize mistaken matching to primaries while still allowing for a large degree of multiple removal. This adaptive subtraction is tested on both synthetic and physical modeling data. The method proves to be effective, and avoids unwanted matching to primaries.
FIG. 2. Left: Impedance inversion result using the measured physical modeling data without frequency extrapolation. Low frequencies are lacking in the measured data, leading to a lack of absolute impedance changes in the result. Right: Impedance inversion using the measured physical modeling data after frequency extrapolation. While significant artifacts and other problems remain, there is significant improvement over the pre-extrapolation result. Interpolation of seismic data using a principal component analysis POCS approach Scott Keating and Kris Innanen Projection onto convex sets, or POCS, is a simple, straightforward method of interpolation which hinges on a few basic assumptions. In order to better fulfill these assumptions, a type of POCS is proposed in which a projection onto principal components is the transform used. This method is shown to be effective both on simple synthetic data, as well as on real VSP data. The problem of acquiring the relevant principal components is addressed by using nearby intact data, and other methods are proposed if this should prove impractical. Partially incomplete data are shown to provide adequate principal components for interpolation in some cases. FIG. 1. Left: Shot gather for VSP data with 30% of traces removed. Right: Data after PCA POCS interpolation, using principal components of nearby, incomplete shot gathers. Nonstationary L1 adaptive subtraction and application to inverse scattering multiple attenuation Scott Keating*, Jian Sun, Pan Pan, Kris Innanen A method for adaptive subtraction in conjunction with internal multiple prediction by inverse scattering series is investigated. An L1, nonstationary adaptive subtraction is found to minimize mistaken matching to primaries while still allowing for a large degree of multiple removal. This adaptive subtraction is tested on both synthetic and physical modeling data. The method proves to be effective, and avoids unwanted matching to primaries. ABSTRACT ABSTRACT
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