This research demonstrates a new accurate automated method for seismic first arrival picking that is based on a mathematical approach with considering the fractal dimension of seismic traces. Reliable and accurate detection of the first arrival is a key step for the determination of seismic parameters. In this work, we introduce an adaptive mathematical triggering algorithm by considering the fractal dimension variations along the seismic records. The results show that our proposed algorithm is quite reliable and it is less susceptible to false-positive detection errors. This suggests adaptive mathematical fractal dimension algorithm may be less sensitive to analyst parameter choices than other methods. Our proposed algorithm was verified using seismic records and synthesized seismic records with different noise levels. Also, we showed the performance and the results of the mathematical fractal dimension method on seismic records. The results emphasize that our proposed algorithm is quite practical and reliable for noisy and bad seismic records, and as well as, it is computationally efficient and easy to apply.
This research presents a new accurate automated method for seismic first arrival picking that is based on a mathematical approach with considering the fractal dimension of seismic traces. Our proposed method is quite viable and efficient for the determination of first arrivals.