Abstract
Prof Yuriy Tyapkin, of the Ukrainian State Geological Prospecting Institute, and Enders A. Robinson, Maurice Ewing and J. Lamar Worzel professor emeritus of geophysics, Columbia University, New York City, have been developing a solution to what they believe is a longstanding omission in the effectiveness of the pilot sweep of vibratory sources in seismic survey acquisition. Successful application of high-resolution seismic methods requires the evaluation of each element in the seismic system to ensure that each part makes an optimal contribution. This principle extends from seismic signal radiation through to data processing where good performance and correct parameter selections are required. Unfortunately, unlike the data processing stage, this important field operation is not usually optimised. The purpose of our study was to eliminate the obvious non-co-ordination of field operations with data processing so that both stages co-operate fully and optimally. We addressed not only the beginning of the seismic system, the source of the seismic signal, but the system as a whole. To validate its feasibility, this optimisation was based upon the Vibroseis technique, primarily because of its versatility in controlling the signal spectrum. The method illustrated here for optimising a pilot sweep signal, using synthetic data as examples, allows the best data quality to be achieved with limited energy expenses. The reflectivity function, also called the impulse response, allows geophysicists to investigate structural and reflective properties of geologic boundaries in the subsurface. Unfortunately the response is always distorted by the filtering (smoothing) effect of a wavelet radiated by a seismic source (Robinson and Treitel, 1980). In order to remove or, more exactly, to reduce the impact of this factor, special processes known as deconvolution are widely used. Unless such procedures have been implemented, seismic data cannot be interpreted in detail and with confidence. Importantly, the deconvolution methods, among which the Wiener filters are most widespread, usually have an optimum character. Favourable conditions for the subsequent resolution improvement should be created, even in the field, so that both stages of the seismic system, field operations and data processing, blend harmoniously and concur in achieving their common objective. The problem, easily solved in this case, is most germane to Vibroseis systems, controllable and hence adaptable to the seismic properties of any area. The Vibroseis technique, conceived more then 40 years ago, is now mature and deployed by a large variety of users in the oil industry. In recent years, vibrators have been the energy sources for over half of the 2D/3D seismic crews operating worldwide. Strangely enough, however, most if not all of them have not benefited from real optimisation of the sweep signal, the most important parameter of vibratory sources. As a matter of fact, any attempt to optimise the pilot sweep at the input to the seismic system made without reference to the properties of the system (Goupillaud, 1976; Dougherty and Justice, 1988) is doomed to fail. This is because it bears no relation to the optimum result at the output of the system. Instead of special preliminary quantitative estimations, a testing of various sweep parameters – the frequency band and the type of non-linearity with associated characteristics foremost among them – followed by visual (so, subjective) analysis of the results is implemented in order to choose a suitable vibratory signal (e.g. Pritchett, 1994). This conventional approach sometimes causes a highly inefficient distribution of the generated energy along the frequency axis, for example, groundless significant extra expenses, on the one hand, and deterioration of the data quality compared with the best (optimum) that should and could be attained, on the other. A method that takes the properties of the entire seismic exploration system into account was first developed in Widess (1982) for optimisation of the pilot sweep. It supposed a special filter to be used for optimising a local criterion for the vertical resolving power of the system. However, the Wiener deconvolution filter, which has enjoyed widespread use for source wavelet deconvolution in exploration seismology, is certain to be more helpful in such a case. Preoptimisation of the signal spectrum at the input to the Wiener deconvolution filter was described in Franks (1969). To avoid some obstacles, however, the solution was simplified and reduced to a band-limited form. A method for optimisation of the spectrum of the pilot sweep which overcomes the shortcomings of the Vibroseis technique described above is the subject here enabling the most efficient use of the radiated energy as a result of its rational distribution along the frequency axis. Emitting the optimum pilot sweep along with finishing Wiener deconvolution filtering at the very end of processing provides the best data quality under a natural restriction on the source energy available.
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