Research On The Key Technologies Of Knowledge-Driven Quantitative Prediction And Evaluation Of Mineral Resources

As finding mineral resources becoming harder and harder, the innovation and breakthroughs of mineralization theory and exploration technology have become the technological innovation and core competencies. The exploration model method is not suited to guide the ore-prospecting if it only depends on prospecting criteria. Using the conceptual model and the genetic model to guide prospecting is a hotspot in current exploration research. In this paper, a new method of quantitative prediction and evaluation of mineral resources based on knowledge-driven was put forward and a new idea of using modeling workflow techniques to predict and evaluate mineral resources in the entire process was developed. This paper introduces the new technologies and methods of integrated data storage and management, data analysis and mining and workflow into the mineral resources prediction, and constructs metallogenic prediction model with the various metallogenic regularities, metallogenic prediction theory and prediction and evaluation theory for mineral resources combined with GIS spatial database and geological data, which expands the quantitative characterization factors of ore-controlling and prospecting criteria and establishs a set of evaluation system, which is a positioning, quantitative and probability prediction method. This paper also designed the GIS workflow of prospecting model, which realized the shared prospecting model and automotive forecasting process and provided a research platform for the people of geological prospecting, quantitative modeling and GIS analysis. This research combined the geological theory and practical problem solving, mathematical modeling and information technology application in mineral resources evaluation.The paper mainly includes the following results.(1) Summarized the genesis concept method and technical process of quantitative prediction and evaluation in mineral resources. It is roughly divided into five parts, including build data modeling, build genesis model, analyze and extract mineralization favorable information, predict with positioning, quality and probability and integrate the results and mining information.(2) Designed and realized the workflow of prospecting model based on WPF. Using the model process modeling technology in the whole process of mineral resources prediction not only realized the prospecting model of visualization, forecasting process visualization and data statistical analysis of visualization, but also implemented the repeatability, reproducibility of the prediction and the modifiability of prediction scheme.(3) Put forward a new method of quantitative expressions of ore-controlling factors by combining the geological data and mineral geology concepts, expand the new variables On 2D and 3D level, such as lithologic interface, tectonic layers(layer) parsing, morphological characteristics of rock mass, and the determining of search ellipsoid parameters in interpolation.(4) Integrated the information and mining information using virtual reality technology, 3 s technology, database technology, the multiple of 3D modeling and visualization technology. The function of cutting section can validate the engineering design and the mining data can be regard as new data to input again.