AUTOMATION OF GEOLOGICAL-SURVEYOR SUPPORT FOR FORECASTING HYDROECOLOGICAL RISKS ARISING WHEN CLOSING COAL MINES

Abstract

Goal. Development of a method for preparing data for the automation of geological and mine surveying to predict hydroecological risks arising from the closure of coal mines and their modeling using the «SAMARA» program. Methodology. This article proposes a method of preparation for the automation of geological and mine surveying data and modeling the processes of subsidence of the earth's surface, which is mined, also allows to determine the areas and volumes of zones of the flooded earth's surface. For this, the sequence of preparation of geological and mine surveying data is considered to create a database with the help of which a geoinformation model of the submerged earth surface by mining was built. This model is realized using the «SAMARA» soft-ware. Result. The developed methodology made it possible to create, using the «SAMARA» software, a model of the earth's surface, which was flooded during its mining operations on the example of the «Ternovskaya» mine of ZAO DTEK «Pavlogradugol». And also the areas and volumes between the initial and settled surface and be-tween the surface of the settled and the groundwater table were calculated. Scientific novelty. It consists in the development of a methodology for preparing data for the automation of geological and mine surveying to predict hydroecological risks arising from the closure of coal mines and their modeling using the «SAMARA» program. Practical significance. It consists in the development of a database that allows automating the modeling processes and predicting hydro-ecological risks arising from the closure of coal mines. In the process of using the «SAMARA» software, a number of serious shortcomings were identified, which confirm the need to develop software that would make it possible to automate the forecasting of hydro-ecological risks in case of counterfeit-ing by cleaning works of the earth's surface in the conditions of the mines of Western Donbass and would be more efficient.