Theoretical approach to estimate the probability of strata convergence: implications for mining induced fractures and potential health risk

Raktim Ghosh

doi:10.1117/12.2327103

9 October 2018 Theoretical approach to estimate the probability of strata convergence: implications for mining induced fractures and potential health risk

Raktim Ghosh

Author Affiliations +

Proceedings Volume 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX; 107901B (2018) https://doi.org/10.1117/12.2327103
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Estimating probability of strata convergence in relation to the distribution of stresses around the excavated wall as well as quantifying the time-dependent displacement are of paramount importance. Convergence is defined as the gradual decrease in the interval between to specified rock units or geological horizons as a result of thinning of intervening strata. The heterogeneous distribution of induced stresses with time resulting into simultaneous strata displacement which is extremely difficult to predict under the robust mining environment. As a result of unpredictable stresses, during the time of subsequent excavation around a specified geologic condition, significant amount of gravitational potential energy decreases due to increasing kinematic energy of overburden. Furthermore, the equilibrium of underground mining conditions is disturbed subsequently with time after the initial uncovering of side wall and roof top. This paper proposes an approach to construct a functional equation of convergence purely based on idealized geological conditions. There are several implications which are associated with the prediction of convergence such as reducing health risk of mining workers, contributions of fractures over the dynamic convergence mechanism and so on.

Conference Presentation

Citation Download Citation

Raktim Ghosh "Theoretical approach to estimate the probability of strata convergence: implications for mining induced fractures and potential health risk", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 107901B (9 October 2018); https://doi.org/10.1117/12.2327103

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