Abstract

The successful application of high‐resolution seismic methods requires evaluating each element in the seismic system and ensuring that each part of the system contributes optimally to the success of the method. Unfortunately, unlike data processing, seismic signal generation is not carefully optimized. The purpose of our study was to optimize the source signal in order to better coordinate field operations with subsequent data processing to achieve their common objective. We developed an iterative method for a rational frequency distribution of the energy of a seismic source. The method allows the optimum amplitude spectrum of a source signal to be calculated, thus providing the best data quality at the end of the processing. We assume that the source signal is affected by a total transfer function, by the reflectivity function of a target interval, and by ambient noise, whose characteristics, if not known, can be estimated or measured in practice. The transfer function includes data processing other than the correlation stage and the final trace‐optimizing filter. The variance of a reflectivity estimate is considered to be a measure of the data quality and improvement of the characteristic corresponds to a decrease in the variance. For this reason, a constrained Wiener deconvolution filter is used as the final trace‐optimizing filter. It not only minimizes the variance of a reflectivity estimate but also ensures a specific signal‐to‐noise ratio. The method is made feasible by following the Vibroseis technique, primarily because of the versatility of the technique in controlling the signal spectrum. With the optimum amplitude spectrum obtained, the corresponding optimum pilot sweep can be readily calculated. Examples using synthetic data are presented to illustrate the method.

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