Quantitative prediction methods and applications of digital ore deposit models

Abstract

With the depletion of surface mineral deposits, attention has shifted to deep mineral exploration prospecting. The emergence of three-dimensional digital ore deposit models, facilitated by the advancement of computer technology, has transformed traditional two-dimensional geological models into computer-recognizable numerical-symbolic digital models. This transformation allows qualitative geological concepts, originally expressed in natural language, to be quantitatively expressed, thereby enhancing the accuracy of deep mineral exploration. This paper first outlines the development from traditional ore deposit models to digital ore deposit models, asserting that digital ore deposit models can encompass a more comprehensive array of multidisciplinary geological information, including mineralogy, ore deposit types, structural geology, geochemistry, and geophysics. Building upon digital ore deposit models, a three-dimensional geological model is constructed, combining regional metallogenic regularities, identifying ore-forming favorable information, and conducting quantitative extraction. Subsequently, a comprehensive prospecting model is established, followed by the integration of deep learning methods for deep-seated mineral exploration, forming a unified system of quantitative prospecting methodology for hidden mineral deposits under the framework of geological prospecting models, three-dimensional geological modeling, and three-dimensional quantitative prospecting. Finally, using the Zaozigou gold deposit in Gansu Province as a case study, this approach is applied to mineral exploration prospecting, delineating prospective target areas and providing valuable reference for future exploration efforts.