DB/T 96-2024 in English
VALIDReport writing specifications for the field verification of observedseismic anomaly-Seismometry
- Issued on:2024-03-01
- Implemented on:2024-09-01
- File Format:PDF
- Delivery:Via email within 1~3 business days
$175.00
本文件规定了测震异常现场核实报告的基本要求、资料收集与分析的主要内容以及编排格式。
本文件适用于测震异常现场核实报告的编写。
Introduction
Technical background and evolution of the standard
As an important part of the DB/T series, this standard inherits and develops the technical framework of the 2005 version of "Terms for Earthquake Disaster Prevention and Reduction" and the 2007 version of "Earthquake Case Summary Specification". With the popularization of the digital seismic station network, the accuracy of anomaly identification has been improved from ±0.5 to ±0.1, prompting the verification report to include more sophisticated waveform analysis and parameter calculation.
Core Content Analysis
| Elements | Traditional Requirements | Innovations of This Standard |
|---|---|---|
| Abnormal Determination | Qualitative Description-Based | Quantitative Index System (5 items including b-value, modulation ratio, etc.) |
| On-site Investigation | Radius 10km | 20km Dynamic AdjustmentMechanism |
| Prediction Effectiveness | Experience Judgment | Three-level Reliability Classification (Reliable/Relatively Reliable/Reference) |
Key Technical Points
Four-step method for anomaly analysis
- Background analysis: It needs to include a three-dimensional model of the tectonic stress field (the deviation of the principal compressive stress direction is ≤15°)
- Time series analysis: It requires NME three-parameter synchronization verification (sampling rate ≥1Hz)
- Spatial correlation: Adopt repositioning technology (positioning error <1km)
- Environmental interference elimination: Establish a reservoir/mine activity database for comparison
Implementation suggestions
1. Multi-source data fusion: It is recommended to integrate InSAR surface deformation data and seismic parameters
2. Efficiency improvement: Adopt machine learning algorithm to optimize b value calculation (random forest model is recommended)
3. Quality Control: Establish a three-level review system for reports (analyst-technical leader-expert group)

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