Some Experiences of Resistivity and Induced Polarization Methods on the Exploration of Sulfide: A Review

Sulfide minerals are a group of compounds with the presence of sulfur. This group’s most abundant and economically members are pyrites, pyrrhotite, chalcocite, galena, sphalerite, and the group of copper sulfides minerals. Resistivity and Induced Polarization (IP) methods, which play an essential role in mineral exploration, showed great success in sulfide exploration. This paper started on reviewing sulfide formation by giving details which help to understand their genesis better. To make the reader understand the procedures and appropriate mineral exploration methods, we have briefly covered the theory, the basic principles of resistivity and IP methods, and different investigation techniques using one, two, and three-dimensional surveys. Based on many electrical surveys, we discussed with examples of resistivity and IP methods applied to the exploration of sulfide deposits: the data inversion and interpretation of the geophysical signatures of most of the sulfide deposits in various geological environments were analyzed and end by showing both successful surveys and limitations of the methods.

顾及邻近点变形因素的高斯过程建模及预测

针对传统的变形监测建模方法一般针对单一监测点的变形预测模型,未考虑到监测点间相互作用的变形特点,该文分析了变形监测点间的相互关联性,通过相关系数法对监测点进行分类,并将邻近监测点的观测序列值作为和时间因素等同的影响因子应用到建模过程中,利用高斯过程算法进行训练,建立预测模型。为提高高斯过程算法的模型预测精度,应选择适合工程案例最优协方差函数。通过实例分析,比较GM(1,1)、多点灰色预测模型和顾及邻近点变形因素的高斯过程等3种模型在基坑围岩、滑坡等变形监测数据处理中的预测精度,表明该文算法考虑到监测点间的变形关联性,充分利用高斯过程在针对小样本、非线性数据建模时的高自适应性等优点,具有较高的预测精度。