Extracting geochemical anomalies from geochemical exploration data is one of the most important activities in mineral exploration. Geochemical anomaly detection can be regarded as a binary classification problem. The similarity between geochemical samples can be measured by their distance. The key issue of this classification is to find the intrinsic relationship and distance between geochemical samples to separate geochemical anomalies from background. In this paper, a hybrid method that integrates random forest and metric learning (RFML) is used to identify geochemical anomalies related to Fe-polymetallic mineralization in Southwest Fujian Province of China. RFML does not require any specific statistical assumption on geochemical data, nor does it depend on sufficient known mineral occurrences as the prior knowledge. The geochemical anomaly map obtained by the RFML method showed that the known Fe deposits and the generated geochemical anomaly area have strong spatial association. Meanwhile, the receiver operating characteristic curves for the results of RFML and another method, namely maximum margin metric learning, indicated that the RFML method exhibited better performance, suggesting that RFML can be effectively applied to recognize geochemical anomalies.
Hydrothermal vent incidence was once thought to be proportional to the spreading rate of the mid-ocean ridges (MORs). However, more and more studies have shown that the ultraslow-spreading ridges (e.g., Southwest Indian Ridge (SWIR)) have a relatively higher incidence of hydrothermal venting fields. The Qiaoyue Seamount (52.1°E) is located at the southern side of segment #25 of the SWIR, to the west of the Gallieni transform fault. The Chinese Dayang cruises conducted eight preliminary deep-towed surveys of hydrothermal activity in the area during 2009 and 2018. Here, through comprehensive analyses of the video and photos obtained by the deep-towed platforms, rock samples, and water column turbidity anomalies, a high-temperature, ultramafic-hosted hydrothermal system is predicted on the northern flank of the Qiaoyue Seamount. We propose that this hydrothermal system is most likely to be driven by gabboric intrusions. Efficient hydrothermal circulation channels appear against a backdrop of high rock permeability related to the detachment fault. 相似文献