Automated Seismic Acquisition Geometry Design for Optimized Illumination at the Target: A Linearized Approach

In seismic exploration methods, imperfect spatial sampling at the surface causes a lack of illumination at the target in the subsurface. The hampered image quality at the target area of interest causes uncertainties in reservoir monitoring and production, which can have a substantial economic impact. Especially in the case of a complex overburden, the impact of surface sampling on target illumination can be significant. The target-oriented acquisition analysis based on wavefield propagation and a known velocity model has been used to provide guidance for optimizing the acquisition parameters. Seismic acquisition design is usually a manual optimization process, with consideration of many aspects. In this study, we develop a methodology that automatically optimizes an irregular receiver geometry when the source geometry is fixed or vice versa. The methodology includes objective functions defined by two criteria: optimizing the image resolution and optimizing the angle-dependent illumination information. We use a two-step parameterization in order to make the problem more linear and, thereby, solve the acquisition design problem by using a gradient descent algorithm. With simple and complex velocity models, we demonstrate that the proposed method is effective, while the involved computational cost is acceptable. Interestingly, the optimization results in our examples show that the conventional uniform geometry already satisfies the resolution requirement, while optimizing for angle coverage can provide a large uplift and is strongly dependent on the velocity model.

Automated summary

Imperfect spatial sampling in seismic exploration methods results in a lack of illumination at the target in the subsurface, impacting reservoir monitoring and production. This study develops a methodology that automatically optimizes an irregular receiver geometry to improve image resolution and angle-dependent illumination information.