Seismic Multiple Attenuation via Iterative Parameter Refinement

The patent implements an iterative processing loop where the system dynamically adjusts user-defined parameters across multiple passes. The method computes initial multiple models, evaluates processing results, modifies parameters based on evaluation metrics, and recomputes until convergence criteria are met. This dynamic adaptation resolves the contradiction by allowing the system to start with initial parameter estimates and progressively improve accuracy through iterative refinement.

The patent incorporates feedback mechanisms where processing results from each iteration are evaluated and fed back into parameter modification. The system assesses the quality of multiple attenuation, identifies deficiencies, and adjusts user-defined parameters accordingly for the next iteration. This feedback loop enables continuous improvement of processing accuracy without requiring perfect initial parameter selection.

The patent applies partial action by implementing convergence criteria that allow the iterative process to terminate when sufficient accuracy is achieved, rather than continuing indefinitely. The system evaluates whether parameter modifications produce meaningful improvements and stops when diminishing returns are detected. This resolves the contradiction by performing just enough iterations to achieve acceptable accuracy without unnecessary time expenditure.

The patent performs preliminary parameter optimization in early iterations where coarse parameter adjustments yield significant accuracy improvements. By addressing the most critical parameter deficiencies first and then performing finer adjustments in subsequent iterations, the system achieves high accuracy efficiently. This preliminary action on critical parameters reduces the total processing time compared to uniform fine-tuning of all parameters.