Mineral product result prediction method and device, computer equipment and storage medium

Abstract

The invention is suitable for the technical field of computers, and provides a mineral product result prediction method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining the geological structure information, rock and ore physical parameters and fluid parameters of a to-be-explored ore deposit; performing multi-physical field numerical simulation calculation on the parameters by utilizing a force-heat-flow multi-field coupling numerical simulation calculation model to obtain a plurality of mineralization condition parameters; and determining a mineral prediction result according to the mineralization condition parameters and the optimal mineral result prediction model. In the mineral product result prediction method, after basic characteristics of a to-be-explored ore deposit are obtained, multi-physical-field numerical simulation calculation is carried out for fitting a mineralization process, the plurality of mineralization condition parameters which cannot be directly measured are obtained, and the mineralization condition parameters are used for determining the mineral prediction result, so that the mineralization mechanismand data dual-driven mineral result prediction method is provided, and the accuracy of the mineral prediction result can be effectively improved.

Description

technical field [0001] The invention belongs to the field of computer technology, and in particular relates to a mine result prediction method, device, computer equipment and storage medium. Background technique [0002] Mineral outcome prediction is a hot and difficult point in current mineral exploration work, especially the prediction of deep mineral outcome. With the development of machine learning algorithms, machine learning algorithms provide an effective way to establish a data-driven prediction model for the prediction of deep mineral deposits. Using machine learning algorithms to establish complex mathematical relationships between mineralization response variables and predictor variables can To achieve the purpose of quantitatively predicting mineral production and optimizing mineralization predictor variables. [0003] However, the mineral outcome prediction model generated by machine learning algorithm training reveals only the numerical relationship between th...

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Problems solved by technology

[0005] The purpose of the embodiments of the present invention is to provide a mining result prediction method, which aims to solve the technical problem of insufficient prediction accuracy in the existing mining result prediction model generated by purely using machine learning algorithm training

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