Sonic Slowness Estimation Using Ray Tracing Optimization

The patent implements an iterative feedback mechanism where the slowness model is updated based on the comparison between predicted travel times (from ray tracing) and actual measured travel times. The objective function quantifies the misfit and guides the optimization process, creating a closed-loop system that continuously refines the slowness estimates until convergence is achieved, thereby eliminating the need for manual quality control.

The patent replaces traditional motion detection algorithms and semblance processing with a physics-based ray tracing approach combined with optimization theory. Instead of relying on heuristic signal processing methods, the solution uses fundamental acoustic wave propagation physics (ray tracing) coupled with mathematical optimization (objective function minimization) to directly compute slowness values, achieving both robustness and accuracy.

The patent creates a self-correcting system where the optimization algorithm automatically detects and corrects erroneous arrival time detections through the objective function. The system self-regulates by comparing predicted versus actual travel times and iteratively adjusting slowness values until the misfit is minimized, eliminating the need for external manual quality control intervention while maintaining high processing efficiency.

The patent performs preliminary ray tracing calculations to predict travel times before comparing them with actual measurements. This preliminary action establishes expected travel time patterns based on the slowness model, which then serves as a reference for automatically identifying and correcting anomalies in the measured data, enabling fully automated quality control.

The patent transforms the complex problem of robust slowness estimation into a parameter optimization problem. By defining an objective function that quantifies the misfit between predicted and actual travel times, the complex geological interpretation task is reduced to finding the optimal slowness parameters that minimize this misfit, thereby achieving robustness through mathematical optimization rather than complex hardware or manual procedures.

The patent segments the subterranean formation into discrete geological cells, each assigned a constant slowness value. This segmentation simplifies the continuous geological medium into manageable discrete units, allowing the complex ray tracing and optimization process to operate on a finite set of parameters (one slowness value per cell) rather than attempting to model continuous variability, thus reducing computational complexity while maintaining robustness.