Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and ho...Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.展开更多
The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and divers...The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and diverse geological background for mineralization.In this study,isometric logarithmic ratio(ILR)transformations of Au,Cu,Pb,Zn,and Sb contents were performed in the1:50,000 soil geochemical data of the Jianbiannongchang area.Robust principal component analysis(RPCA)was conducted based on ILR transformation.The local singularity and spectrum-area(S-A)methods were used to extract information on mineralogic anomalies.The results showed that:(1)the transformed data eliminated the influence of the original data closure effect,and the PC1and PC2 information obtained by applying RPCA reflected ore-producing element anomalies dominated by Au and Cu.(2)The local singularity method can enhance the information of the local strong and weak slow anomalies.After performing local singularity analysis on PC1 and PC2,the obtained local anomalies reflected the local singularity spatial anomaly patterns related to Cu and Au mineralization in this area,which is an effective method for trapping ore-producing anomalies.(3)Furthermore,the composite anomaly decomposition of PC1 and PC2 was performed using the S-A method,and the screened anomalous and background fields reflect the ore-producing anomalies related to Cu and Au mineralization.This information is in agreement with known Cu and Au mineralization.(4)The geochemical anomalies with mineralization potential were obtained outside the known mineralization sites by integrating the information of oreproducing anomalies extracted by the local singularity and S-A methods,providing the theoretical basis and exploration direction for future exploration in the study area.展开更多
文摘Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.
基金supported by the Project of the Natural Science Foundation of Liaoning Province(2020-BS-258)the Scientific Research Fund Project of the Educational Department of Liaoning Provincial(LJ2020JCL010)+1 种基金The project was supported by the discipline innovation team of Liaoning Technical University(LNTU20TD-14)the Key Research and Development Project of Heilongjiang Province(GA21A204).
文摘The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and diverse geological background for mineralization.In this study,isometric logarithmic ratio(ILR)transformations of Au,Cu,Pb,Zn,and Sb contents were performed in the1:50,000 soil geochemical data of the Jianbiannongchang area.Robust principal component analysis(RPCA)was conducted based on ILR transformation.The local singularity and spectrum-area(S-A)methods were used to extract information on mineralogic anomalies.The results showed that:(1)the transformed data eliminated the influence of the original data closure effect,and the PC1and PC2 information obtained by applying RPCA reflected ore-producing element anomalies dominated by Au and Cu.(2)The local singularity method can enhance the information of the local strong and weak slow anomalies.After performing local singularity analysis on PC1 and PC2,the obtained local anomalies reflected the local singularity spatial anomaly patterns related to Cu and Au mineralization in this area,which is an effective method for trapping ore-producing anomalies.(3)Furthermore,the composite anomaly decomposition of PC1 and PC2 was performed using the S-A method,and the screened anomalous and background fields reflect the ore-producing anomalies related to Cu and Au mineralization.This information is in agreement with known Cu and Au mineralization.(4)The geochemical anomalies with mineralization potential were obtained outside the known mineralization sites by integrating the information of oreproducing anomalies extracted by the local singularity and S-A methods,providing the theoretical basis and exploration direction for future exploration in the study area.
