Développement d'une nouvelle technique de pointé automatique pour les données de sismique réfraction

摘要

Accurate picking of first arrival times plays an important role in many seismic studies, particularly in seismic tomography and reservoirs or aquifers monitoring. A new adaptive algorithm has been developed based on combining three picking methods (Multi-Nested Windows, Higher Order Statistics and Akaike Information Criterion). It exploits the benefits of integrating three properties (energy, gaussianity, and stationarity), which reveal the presence of first arrivals. Since time uncertainties estimating is of crucial importance for seismic tomography, the developed algorithm provides automatically the associated errors of picked arrival times. The comparison of resulting arrival times with those picked manually, and with other algorithms of automatic picking, demonstrates the reliable performance of this algorithm. It is nearly a parameter-free algorithm, which is straightforward to implement and demands low computational resources. However, high noise level in the seismic records declines the efficiency of the developed algorithm. To improve the signal-to-noise ratio of first arrivals, and thereby to increase their detectability, double stacking in the time domain has been proposed. This approach is based on the key principle of the local similarity of stacked traces. The results demonstrate the feasibility of applying the double stacking before the automatic picking.