Evaluation and comparison of the results of the NET-VISA seismic event association method based on Bayesian theory

Seismic monitoring is an important verification technique under the Comprehensive Nuclear-Test-Ban Treaty. Phase association technology, which is an important component of seismic data processing, associates signals generated from the same event source recorded at multiple stations and determines event information based on signal features. Seismic event association based on the historical seismic data feature model is a research hot spot in the field of seismic monitoring. In this paper, an event association method called NET-VISA based on Bayesian theory is introduced; then, the application of the historical data feature model in NET-VISA is analyzed. The NET-VISA method is evaluated using the International Data Centre LEB bulletins published by the Comprehensive Nuclear-Test-Ban Treaty Organization, the ISC Reviewed Bulletins, and the China Earthquake Networks Center bulletin as reference sets. The results show that for the global sparse network, NET-VISA is generally superior to the GA method currently used by the IDC, which verifies NET-VISA's effectiveness. However, NET-VISA misses some events detected by the GA. The reasons might be that these events are located in regions with low seismic activity and that insufficient historical event data exists, resulting in unreasonable scoring results.Finally, the application method and research direction of NET-VISA in actual scenarios are discussed.

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