Details of the Abstract
| Title of paper | Frequency Fusion for Spread-Spectrum-Induced-Polarization Data Processing |
| List of authors | Yao, H., Guo, Z., Chen R., He L., Wu Y., Yang S. |
| Affiliation(s) | Central South University, Central South University, Central South University, Chinese Academy of Sciences, Central South University, Giant Sequoia Artificial Intelligence Technology (Changsha) Co., Ltd. |
| Summary | Induced Polarization (IP) method, which can measure both resistivity and chargeability, is widely used in the exploration of metal ore deposits. Addressing the issues of weak anti-interference capability and difficulty in distinguishing between ore and non-ore IP anomaly with conventional IP methods, we propose and implement a spread spectrum IP (SSIP) data processing method. This method utilizes the rich fundamental frequency components of pseudo-random spread spectrum signals to distinguish IP anomalies between ore and non-ore zones and employs a frequency fusion method to improve the anti-interference capability of IP parameters. Finally, field-measured data were used for processing tests. The results show that frequency fusion can enhance the anti-interference capability of IP parameters and allow for the adjustment of the number of frequencies fused according to the level of interference, ensuring the distinction of IP anomalies between ore and non-ore zones while maintaining data quality. |
| Session Keyword | 1.0 Instrumentation, data acquisition and processing |
| File upload |
1.0_frequency_fusion_for_spre_yao.pdf
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