Decomposition of vector wavefield data /
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| Other Authors: | , , , |
| Format: | Thesis Book |
| Language: | English |
| Published: |
1991.
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| Subjects: | |
| Online Access: | ProQuest, Abstract Link to OAKTrust copy |
| Abstract: | A new algorithm is developed for estimating the moveout velocities and polarization states in mixed wavefields recorded on multi-component array data in the presence of random noise. The method, which is referred to as the eigendata analysis method, is applicable to a spatial and temporal data window in which more than two events are present. Three fundamental wavefield attributes of the interfering waves are determined: polarization angle, apparent slowness and the change in amplitude between adjacent detectors. Application of a least squares criterion reduces the mathematics to an eigendata problem. The eigenvalues are complex. The magnitude determines the amplitude change factor. The phase is a linear function of frequency with slope which determines the vertical slowness. The eigenvectors are the polarizations. The input data consists of the cross-power spectra between subarrays which contain the same numbers of elements and are shifted by zero or one geophone separation. Examples illustrate the application of the algorithm to synthetic data. Numerical test results show that the performance of the method is not sensitive either to the time overlap between events or to the degree of similarity between waveforms. As an extended application of the eigendata analysis method, an integrated wavefield separation algorithm (IWSA) was developed and tested using real and synthetic seismograms. IWSA utilizes simultaneously the three wavefield attributes of interfering waves in order to maximize the separation ability of the algorithm. The results of the theoretical analysis and the practical applications show that IWSA circumvents the most challenging problem in existing multicomponent data processing techniques: the number-of-events limitation in the single-geophone polarization filtering and the finite spatial aperture problem in the two-dimensional transformation + filtering techniques. As another application of the eigendata analysis method, a complex polarization inversion method was developed for estimating fracture orientation and splitting time. The method utilizes two component shear data from a conventional SH survey or shear vertical seismic profiling. Initially, the polarization inversion method determines a frequency dependent complex polarization vector for the shear wave propagating vertically through a layer of vertically aligned fractures. By minimizing the square error between the estimated and modeled polarizations we can uniquely determine the fracture orientation and the splitting time produced by a fractured reservoir. Numerical test results show that the algorithm is capable of determining with considerable precision the two parameters. |
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| Item Description: | Typescript (photocopy). Vita. "Major subject: Geophysics." |
| Physical Description: | x, 112 leaves : illustrations ; 29 cm |
| Bibliography: | Includes bibliographical references. |