矿产资源勘查走向深部已成为国际大趋势，深部找矿面临着地表探测到的成矿信息弱缓且混叠等难题，研究深部弱缓异常识别与多尺度信息提取方法是创新深部矿产资源预测与评价的关键之一。本项目选择南岭钨锡多金属成矿带为研究区，基于南岭地区成矿系统的等级自组织性与地质异常的分形自相似性，结合小波多尺度分析功能和分形尺度不变性理论，重点研究小波域各向异性分形密度模型和小波变换系数的多重分形级联模型，在此基础上建立小波域各向异性奇异性分析方法和小波域多重分形多尺度滤波方法，目标在于识别南岭地区深部矿致弱缓异常，提取深部找矿多层次信息。本研究不仅能够进一步丰富和发展非线性成矿信息识别理论与方法，而且有助于深入认知南岭深部成矿系统的多尺度耦合特征，有望为南岭深部找矿提供技术支撑和科学依据。

Discovering potential mineral deposits in deep area is becoming a new international trend, but deep ore prospecting faces with many challenges and of most crucial is that the geo-anomalies caused by such mineral deposits are very weak and heavily mixed due to the fact of large depth. Thus, one of key techniques for deep ore prospecting is to study the competent method for enhancing weak anomalies and extracting multiscale information. In this proposal, the Nanling W-Sn polymetallic district is chosen as case study for exploring the hierarchy of mineral system and the self-similarity of geo-anomaly. Specifically, this program focuses on building anisotropic fractal density model and multiplicative cascade model on the frame of wavelet transform and fractal concept. This idea comes from the fact that multiscale decomposition scheme of wavelet transform is a natural tool for scaling analyzing the fractal measure. Accordingly, the wavelet-based singularity mapping technique and fractal-based wavelet multiscale decomposition method will be proposed respectively for identifying the weak anomalies caused by deeply buried ore deposits, as well as extracting the multiscale deep information buried in mixed geo-anomaly pattern. Of special interest is that the recognized multiscale anomalies will significantly enlighten our knowledge for understanding the hierarchy and coupling of multiscale metallogenic system, therefore assisting in the prediction and exploration of deep mineral resources in Nanling district.