Abstract

3D Seismic Data acquisition in land is suffering from data gaps and fold loss as time is progressing due to growing urbanization and severe logistic constraints. To start with, source locations are getting irregular, which is increasing day by day and getting random. The same case is with the receivers. Then the question arises that how to address this issue of disorder where the departure in source and receiver locations is high from the regular geometry. The question also arises can we acquire a reasonable meaningful 3D data. The answer is yes, provided we take recourse to real time dynamic modelling through an algorithm. This will not replace the regular geometry data but help in minimizing the irregularity in attributes of the acquired 3D data, which will be more meaningful than the highly random data that we acquire today. This requires a real time monitoring of 3D data in 3-dimensional attribute space namely fold, offset and azimuth. This will definitely lead to increase in source locations and receiver locations than that arrived with regular geometry but at the same time provides advantage for regularization at processing level. This paper deals with the change in approach towards tackling logistic constraint in 3D data acquisition in land areas, with the help of an algorithm, developed to aid the decision-making process. This approach will provide optimal source locations, receiver locations and spread for each source location thereby optimizing the overall acquisition and provide the best 3D data. Such 3D seismic data acquisition will be closer to the planned acquisition.