3D seismic tomography models of the Baikal Rift zone and surrounding areas based on regional seismological data

Summary First-arrival picking is a fundamental and challenging task in seismic data processing. Existing algorithms such as the cross-correlation algorithm (CCT) struggle to achieve satisfactory noise immunity while maintaining picking efficiency. In this paper, we propose the first-arrival picking through mathematical morphology and edge detection (FPME) algorithm with three steps. The converting step transforms the original data into a binary image though a filtering technique, where the binary image represents the global energy distribution of high-energy and low-energy samples. The rendering step delimits the signal zone in the binary image through morphological operations, where the signal zone eliminates the noise in the upper part. The picking step detects first arrivals in the signal zone through the edge detection methods, where an evaluation function is designed to select the optimal detection results as first arrivals. Experiments were performed on four field datasets. The results demonstrated that FPME is more stable and reliable than five classic and popular algorithms.

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3D seismic tomography models of the Baikal Rift zone and surrounding areas based on regional seismological data

Cited by 2 publications

References 77 publications

Thermal state and nature of the lower crust in the Baikal Rift Zone: Insight from xenoliths of Cenozoic and Paleozoic magmatic rocks

Thermal state and nature of the lower crust in the Baikal Rift Zone: Insight from xenoliths of Cenozoic and Paleozoic magmatic rocks

Stable first-arrival picking through mathematical morphology and edge detection

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