Optimization of blending and spatial sampling in seismic acquisition design

Abstract

The quality and business aspects are both of particular importance in determining the type of seismic acquisition. Usually, a strong emphasis on cost reduction is inevitable. On the other hand, there is an increasing demand for the acquisition of high-quality seismic data that can contribute to the various stages in the field development profile. These conflicting desires eventually make conventional seismic surveys an inadequate option. The application of blended acquisition along with efficient detector and source geometries is capable of providing high-quality seismic data in a cost-effective and productive manner. This way of data acquisition also contributes to minimizing health, safety and environment exposure in the field. Blended acquisition allows multiple source-wavefields to be overlapped in time, space, and temporal and spatial frequency, causing blending interference. The acquisition of less data via sparse detector and source geometries likely violates the Nyquist sampling criterion. Therefore, to make the aforementioned approach technically justifiable, deficiencies in recorded data have to be dealt with through the course of subsequent processing steps. One way to encourage this technique is to minimize any imperfection in processing algorithms. In addition, one may derive survey parameters that enable a further improvement in these processes, which is the primary focus in this thesis.