Seismic Survey Geometry Optimization for Complex Terrain Imaging

The patent applies preliminary action by performing a virtual seismic survey and synthetic data generation before the actual field deployment. The method evaluates multiple acquisition geometries in silico using a priori velocity models and imaging algorithms to predict subsurface image quality, allowing the selection of optimal receiver locations before physical deployment occurs. This prevents suboptimal grid-based deployments that would otherwise result in poor image quality for complex 3D structures.

The patent implements dynamics by transitioning from a static regular grid geometry to a dynamic, optimized acquisition geometry. The method uses iterative optimization algorithms that adjust receiver locations based on virtual survey results, a priori velocity models, and imaging quality metrics. This dynamic adaptation allows the acquisition geometry to be tailored to complex 3D geological structures and rugged terrains, improving subsurface image quality while maintaining deployment feasibility.

The patent applies preliminary action by conducting virtual seismic surveys and synthetic data generation before field deployment. This allows the identification of optimal receiver locations that achieve high subsurface image quality with minimized receiver density. By evaluating acquisition geometries in silico using a priori velocity models and imaging algorithms, the method determines the minimum necessary receiver density required for high-quality imaging in complex terrains, avoiding unnecessary deployment complexity and cost.

The patent uses copying by creating virtual copies of the seismic survey through synthetic data generation. Instead of immediately deploying physical receivers in difficult-to-access regions, the method first creates a virtual model of the survey using a priori velocity models and generates synthetic seismic data. This virtual copy allows evaluation of different acquisition geometries and receiver densities to identify the optimal configuration that achieves high image quality with minimal deployment complexity, before committing to actual field deployment.

The patent applies preliminary action by performing virtual seismic surveys and synthetic data generation for deep targets before field deployment. The method uses a priori velocity models to simulate seismic wave propagation to deep targets and evaluates different acquisition geometries using imaging algorithms. This allows determination of the optimal receiver density and distribution required for deep target imaging, avoiding excessive deployment complexity while achieving the necessary penetration depth and image quality.

The patent implements parameter changes by adjusting acquisition geometry parameters based on target depth. The method uses iterative optimization that modifies receiver spacing, profile lengths, and survey area extent according to the depth of the target. For deeper targets, the optimization algorithm determines the appropriate increase in receiver density and survey scale, balancing the need for deep penetration with deployment feasibility and cost constraints.