基于数据与成矿机制的深度矿产预测研究
Research on Deep Mineral Prediction Based on Data and Metallo-genic Mechanisms
宋永元1
作者信息
- 1. 河北省地质矿产勘查开发局第八地质大队,河北秦皇岛 066000
- 折叠
摘要
对深部矿产结果的预测是当前矿产勘查工作的热点与难点.提出了一种数据与成矿机制双向驱动的计算机模拟矿产结果预测技术,在获取到拟勘探矿床的地质构造信息、岩矿石物性参数以及流体参数之后,先利用最优力—热—流多场耦合数值模拟计算模型进行多物理场数值模拟计算,通过训练得到的最佳成矿机制下的多个无法被直接测量的成矿条件参数,然后再利用该成矿条件参数以及训练得到的最优矿产结果预测模型确定拟勘探矿床的矿产预测结果,从而有效改善矿产预测结果的准确性.
Abstract
Predicting the results of deep mineral resources is a hot and difficult topic in current mineral exploration work.A computer simulation mineral result prediction technology driven by both data and mineralization mechanism is proposed.After obtaining geological structure information,rock and ore physical properties parameters,and fluid parameters of the proposed exploration deposit,the optimal force heat flow multi field coupled numerical simulation calculation model is first used for multi physical field numerical simulation calculation.Multiple mineralization condition parameters that cannot be directly mea-sured under the best mineralization mechanism are obtained through training.Then,the accuracy of mineral prediction results of the proposed exploration deposit is determined by using the optimal mineralization condition parameters and the trained opti-mal mineral result prediction model,thereby effectively improving the accuracy of mineral prediction results.
关键词
数据/成矿机制/深度矿产Key words
data/metallogenic mechanism/deep mineral resources引用本文复制引用
出版年
2024
NETL
NSTL
万方数据