Evaluation of Sequential Hybrid Inversion in the MASW Method: A Case Study in Santa Fe, Granada, Spain

The MASW (Multichannel Analysis of Surface Waves) method oriented toward seismic microzoning has been evolving consistently and steadily for several decades, providing increasingly reliable solutions that are consistent with field and laboratory data typical of classical geotechnics. This study evaluates the improvement achieved when using a sequence of inversion algorithms on MASW test results: first with a global algorithm—specifically Differential Evolution (DE)—and subsequently, using the best model obtained from the global search, a second local algorithm—Trust Region Reflective (TRF). This second stage refines the previous model, further adjusting it to the borehole model used as the starting point of the sequence. The procedure has been automated using a Python script that incorporates two innovations compared to traditional inversion approaches. These consist of parameterising two variables: (i) an adaptive expansion factor for the Vs limits establisheda priori in the borehole model, and (ii) a subdivision into thinner layers for borehole models with excessively thick strata. This provides the algorithms with greater flexibility, particularly in scenarios with complex stratification. Additionally, to better define the deeper layers, the passive ESAC method in an “L-shape” configuration was also employed. The parameterised sequential hybrid inversion process was validated using synthetic data from two curves (Curve #1 and Curve #2), obtained by adding 5% Gaussian noise to the forward modelling results of the same initial synthetic model. The TRF refinement stage in the sequential hybrid inversion succeeded in reducing the error obtained by the global algorithm by percentages ranging from 59.7% to 5.8% across all conducted tests, confirming the stability of the methodology used.