The aim of this paper is to generate the mineral prospectivity mapping (MPM) for a porphyry copper mineralization area. First, three information layers of geochemistry, geophysics, and geology were defined as the main criteria with a total of 13 sub-criteria, eight for geochemical criterion, two for geophysical criterion, and three for geology criteria. As the Cu element is the main variable in copper porphyry mineralization. The geochemical criteria included the concentration values of 36 elements (Cu, Au, Mo, Pb, Zn, Ag, Ni, Co, Mn, Fe, As, Th, Sr, Cd, Sb, Bi, V, Ca, P, La, Cr, Mg, Ba, Ti, B, Al, Na, K, W, Hg, Tl, S, Sc, Se, Ga, and Te) from 87 rock samples that were analyzed by the induced coupled plasma (ICP) method. Before assigning the class scores for the quantitative and qualitative classes, a multivariate geochemical analysis (MGA) was done to reduce the number of the measured elements to a smaller number most related to the Cu mineralization. It was achieved through the probability plot modeling, calculating the threshold values of the Cu variable along with background and anomaly separation. The final step was discriminant analysis (DA), PCA, and agglomerative hierarchical clustering (AHC) analysis that reduced the number of elements to 8 elements as the geochemical sub-criteria. Then, the qualitative information was quantitated for the two criteria of geophysics and geology which were in the form of geophysical maps and geological information respectively. Then, the Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE) as one of the newest multiple attribute decision-making (MADM) methods was performed to obtain the net outranking flow for each criterion and for the integration of all criteria. Finally, the net outranking flow as the input data was used to generate the MPMs in Arc GIS 10.5 software which shows the promising areas for each criterion and for the integration of all criteria. The generated MPMs were then compared and the map obtained by integration of all criteria identified as a better result with the sharper boundary of the promising areas that can be used by decision-makers for future exploration programs.

本文的目的是为斑岩铜矿化区生成矿产远景图 (MPM)。首先，定义地球化学、地球物理和地质三个信息层为主要标准，共13个子标准，其中地球化学标准8个，地球物理标准2个，地质标准3个。由于铜元素是铜斑岩矿化的主要变量。地球化学标准包括36种元素（Cu、Au、Mo、Pb、Zn、Ag、Ni、Co、Mn、Fe、As、Th、Sr、Cd、Sb、Bi、V、Ca、P）的浓度值、La、Cr、Mg、Ba、Ti、B、Al、Na、K、W、Hg、Tl、S、Sc、Se、Ga 和 Te）来自 87 个岩石样品，这些样品由感应耦合等离子体 (ICP) 分析) 方法... 在为定量和定性班级分配班级分数之前，进行了多元地球化学分析 (MGA) 以将测量元素的数量减少到与铜矿化最相关的较小数量。它是通过概率图建模实现的，计算Cu变量的阈值以及背景和异常分离。最后一步是判别分析 (DA)、PCA 和凝聚层次聚类 (AHC) 分析，将元素数量减少到 8 个元素作为地球化学子标准。然后，分别以地球物理图和地质信息的形式对地球物理和地质这两个标准对定性信息进行量化。然后，执行了作为最新的多属性决策 (MADM) 方法之一的富集评估的偏好排名组织方法 (PROMETHEE)，以获得每个标准和所有标准的整合的净排名流。最后，作为输入数据的净排名流用于在 Arc GIS 10.5 软件中生成 MPM，该软件显示了每个标准的有希望的区域以及所有标准的集成。然后将生成的 MPM 进行比较，通过整合所有标准获得的地图被确定为更好的结果，具有更清晰的有希望区域的边界，可供决策者用于未来的勘探计划。作为输入数据的净排名流用于在 Arc GIS 10.5 软件中生成 MPM，该软件显示了每个标准和所有标准的集成的有希望的区域。然后对生成的 MPM 进行比较，通过整合所有标准获得的地图被确定为更好的结果，具有更清晰的有希望区域的边界，可供决策者用于未来的勘探计划。作为输入数据的净排名流用于在 Arc GIS 10.5 软件中生成 MPM，该软件显示了每个标准和所有标准的集成的有希望的区域。然后将生成的 MPM 进行比较，通过整合所有标准获得的地图被确定为更好的结果，具有更清晰的有希望区域的边界，可供决策者用于未来的勘探计划。