nznistuНауки о Земле и недропользованиеEarth sciences and subsoil use2686-99932686-7931Federal State Budget Educational Institution of Higher Education "Irkutsk National Research Technical University"10.21285/2686-9993-2021-44-3-219-242nznistu-159Research ArticleГеоинформатикаGeoinformaticsСовместное прогнозирование ресурсов и окружающей среды с использованием интеллектуального анализа больших данных и 3D/4D-моделирования в горнодобывающем районе Луаньчуань, КитайResource-environment joint forecasting using big data mining and 3D/4D modeling in Luanchuan mining district, ChinaВанГунвэньWangGongwen

Ван Гунвэнь, доктор геолого-минералогических наук, профессор, заместитель декана, Школа наук о Земле и минеральных ресурсов

Пекин

Gongwen Wang, Dr. Sci. (Geol. & Mineral.), Professor, Deputy Dean, School of Earth Science and Mineral Resources

Beijing

gwwang@cugb.edu.cnЧжанШоутинZhangShouting

Чжан Шоутин

Пекин

Shouting Zhang

Beijing

ЯньЧанхайYanChanghai

Янь Чанхай

Чжэнчжоу

Changhai Yan

Zhengzhou

ПанЧжэньшаньPangZhenshan

Пан Чжэньшань

Пекин

Zhenshan Pang

Beijing

ВанХунвэйWangHongwei

Ван Хунвэй

Лоян

Hongwei Wang

Luoyang

ФэнЧжанькуйFengZhankui

Фэн Чжанькуй

Лоян

Zhankui Feng

Luoyang

ДунХунDongHong

Дун Хун

Пекин

Hong Dong

Beijing

ЧэнХунтаоChengHongtao

Чэн Хунтао

Лоян

Hongtao Cheng

Luoyang

ХэЯцинHeYaqing

Хэ Яцин

Лоян

Yaqing He, Henan China Molybdenum Co., Ltd., Luoyang, China.

Luoyang

 

ЛиЖуйсиLiRuixi

Ли Жуйси

Пекин

 

Ruixi Li

Beijing

ЧжанЧжицянZhangZhiqiang

Чжан Чжицян

Пекин

Zhiqiang Zhang

Beijing

ХуанЛэйлэйHuangLeilei

Хуан Лэйлэй

Пекин

Leilei Huang

Beijing

ГоНанаGuoNana

Го Нана

Лоян

Nana Guo

Luoyang

Китайский университет наук о ЗемлеКитайChina University of GeosciencesChinaЦентральная лаборатория металлогенических процессов и утилизации ресурсовКитайKey Laboratory of Metallogenetic Processes and Resource UtilizationChinaГеологическая служба КитаяКитайChina Geological SurveyChinaБюро природных ресурсов уезда ЛуаньчуаньКитайLuanchuan County Natural Resources BureauChinaХэнаньская горнодобывающая компания Цзычжоу Чжундин Майнинг Ко. ЛимитедКитайHenan Jiuzhou Zhongding Mining Co., Ltd.ChinaГеологическая и горнодобывающая компания КитаяКитайChina Geology & Mining Co., Ltd.ChinaХэнаньская горнодобывающая компания Чжунсинь Майнинг Ко. ЛимитедКитайHenan Zhongxin Mining Co., Ltd.ChinaХэнаньская компания Китай Молибден ЛимитедКитайHenan China Molybdenum Co., Ltd.China202129102021443219242Copyright © Ван Г., Чжан Ш., Янь Ч., Пан Ч., Ван Х., Фэн Ч., Дун Х., Чэн Х., Хэ Я., Ли Ж., Чжан Ч., Хуан Л., Го Н., 20212021Ван Г., Чжан Ш., Янь Ч., Пан Ч., Ван Х., Фэн Ч., Дун Х., Чэн Х., Хэ Я., Ли Ж., Чжан Ч., Хуан Л., Го Н.Wang G., Zhang S., Yan C., Pang Z., Wang H., Feng Z., Dong H., Cheng H., He Y., Li R., Zhang Z., Huang L., Guo N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.nznj.ru/jour/article/view/159

Промышленная эра четвертого поколения и интеллектуальная связь 5G + в «четвертой парадигме науки» XXI века открывают новые возможности для исследований взаимосвязи между развитием горнодобывающей промышленности и защитой окружающей среды. Эта статья основана на теории металлогенической геодинамики, металлогенических процессах и количественной оценке на примере района Луаньчуань в качестве тематического исследования с использованием глубинного искусственного интеллекта и трехмерного / четырехмерного (3D/4D) междисциплинарного, многопрофильного параметрического и многомасштабного моделирования больших данных, включая многомасштабные геологические, геофизические, геохимические, гиперспектральные и высокоразрешающие данные дистанционного зондирования (разновременные), данные о добыче полезных ископаемых в реальном времени, с выполнением построения трехмерной геологической модели, модели металлогенического процесса и количественной модели разведки от локального района до масштабов месторождения, а также количественного прогнозирования и оценки региональных полиметаллических минеральных ресурсов Mo. Цель исследования заключается в реализации динамической оценки высокоточной трехмерной геологической модели (горные породы, структура, гидрология, почва и т. д.), охраны окружающей среды, комплексного освоения и использования минеральных ресурсов в цифровой среде. Исследование ориентировано на предоставление научной информации по устойчивому развитию минеральных ресурсов и горнодобывающей отрасли в изучаемом регионе. Результаты исследования заключаются в следующем. 1. Большие данные геонаук, связанные с прогнозированием и оценкой минеральных ресурсов в исследуемом районе, включают данные горных работ, такие как трехмерное геологическое моделирование, интерпретация геофизики, геохимия и моделирование дистанционного зондирования, которые объединены с программным обеспечением GeoCube3.0. Проведены оптимизация глубинных данных и комплексная оценка минеральных ресурсов в районе Луаньчуань (500 км2 , глубина – 2,5 км), в том числе 6,5 млн тонн Mo, 1,5 млн т W и 5 млн т Pb-Zn-Ag. 2. Трехмерное геологическое моделирование геологии, месторождений полезных ископаемых и геологоразведочных работ связанно с окружающей средой рудника. Данные разведки и добычи на карьерах месторождений Нанниху – Сандаочжуан – Шанфан и в глубоких руслах месторождений Луотуошань и Сигоу показывают слабую пространственную корреляцию между порфирово-скарновыми месторождениями северо-западного простирания и рудными телами. Разломы северо-восточного простирания обычно представляют собой структуры растяжения или растяжения-кручения, сформированные в пост-металлогенический период и являющиеся путями миграции гидротермального Pb-Zn флюида соответствующего месторождения. Существует риск загрязнения подземных вод в высокогорных зонах добычи Pb-Zn, таких как месторождения Ленгшуй и Байлугоу, контролируемых разломами северо-восточного простирания и разрабатывающихся за пределами месторождений порфирово-скарнового типа Mo (W) в районе Луанчуань. 3. Моделирование минеральных ресурсов, оценка состояния окружающей среды и принятие решений в интеллектуальных цифровых рудниках: трехмерная геологическая модель создается на крупных рудниках и связана с древними горными пещерами, карьерами и глубокими дорожными сооружениями в районах добычи для обеспечения разумной ориентации и устойчивого развития горнодобывающей промышленности. Гиперспектральная база данных используется для построения трехмерных моделей полезных и вредных элементов с целью реализации взаимосвязи минералогии, разведки, добычи и переработки полезных ископаемых для извлечения вредных элементов (As, Sb, Hg и т. д.). Используются изображения Worldview2 с разрешением 0,5 м для определения распределения Fe в сточных водах и шламах важных хвостохранилищ, позволяющие защитить поверхностный сток и загрязнение почвы.

The Fourth generation industrial age and 5G + intelligent communication in the "Fourth Paradigm of Science" in the 21st century provide a new opportunity for research on the relationship between mining development and environmental protection. This paper is based on the theory of metallogenic geodynamics background, metallogenic process and quantitative evaluation and chooses the Luanchuan district as a case study, using deep-level artificial intelligence mining and three/four-dimensional (3D/4D) multi-disciplinary, multi-parameter and multi-scale modeling technology platform of geoscience big data (including multi-dimensional and multi-scale geological, geophysical, geochemical, hyperspectral and highresolution remote sensing (multi-temporal) and real-time mining data), carrying out the construction of 3D geological model, metallogenic process model and quantitative exploration model from district to deposit scales and the quantitative prediction and evaluation of the regional Mo polymetallic mineral resources, the aim is to realize the dynamic evaluation of highprecision 3D geological (rock, structure, hydrology, soil, etc.) environment protection and comprehensive development and utilization of mineral resources in digital and wisdom mines, it provides scientific information for the sustainable development of mineral resources and mine environment in the study area. The research results are summarized as follows: (1) The geoscience big data related to mineral resource prediction and evaluation of district include mining data such as 3D geological modeling, geophysics interpretation, geochemistry, and remote sensing modeling, which are combined with GeoCube3.0 software. The optimization of deep targets and comprehensive evaluation of mineral resources in Luanchuan district (500 km2, 2.5 km deep) have been realized, including 6.5 million tons of Mo, 1.5 million tons of W, and 5 million tons of Pb-Zn-Ag. (2) The 3D geological modeling of geology, mineral deposit, and exploration targeting is related to the mine environment. The data of exploration and mining in the pits of Nannihu – Sandaozhuang – Shangfang deposits and the deep channels of Luotuoshan and Xigou deposits show a poor spatial correlation between the NW-trending porphyryskarn deposits and the ore bodies. The NE-trending faults are usually tensional or tensional-torsional structures formed in the post-metallogenic period, which is the migration pathway of hydrothermal fluid of the related Pb-Zn deposit. There is a risk of groundwater pollution in the high-altitude Pb-Zn mining zones, such as the Lengshui and Bailugou deposits controlled by NE-trending faults are developed outside of porphyry-skarn types of Mo (W) deposits in the Luanchuan area. (3) Construction of mineral resources and environmental assessment and decision-making in intelligent digital mines: 3D geological model is established in large mines and associated with ancient mining caves, pit, and deep roadway engineering in the mining areas to realize reasonable orientation and sustainable development of mining industry. The hyperspectral database is used to construct three-dimensional useful and harmful element models to realize the association of exploration, mining, and mineral processing mineralogy for the recovery of harmful elements (As, Sb, Hg, etc.). 0.5 m resolution Worldview2 images are used to identify the distribution of Fe in the wastewater and slag slurry of important tailings reservoirs, so as to protect surface runoff and soil pollution.

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