Szczegóły publikacji
Opis bibliograficzny
Application of land subsidence inversion for salt mining-induced rock mass movement / Ryszard HEJMANOWSKI, Agnieszka A. MALINOWSKA // W: Advances and applications in geospatial technology and earth resources : proceedings of the international conference on Geo-Spatial Technologies and Earth Resources 2017 : [GTER-2017 : October 5–6, 2017, Hanoi, Vietnam] / eds. Dieu Tien Bui, [et al.]. — Cham : Springer International Publishing, cop. 2018. — ISBN: 978-3-319-68239-6; e-ISBN: 978-3-319-68240-2. — S. 340–354. — Bibliogr., Abstr. — Publikacja dostępna online od: 2017-10-06
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 109572 |
|---|---|
| Data dodania do BaDAP | 2017-10-25 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-319-68240-2_21 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Geo-Spatial Technologies and Earth Resources |
Abstract
Modelling of strains and deformations in salt mine areas encounters considerable difficulties because of the varying strength properties of salt, complex morphological formation of dome deposits and rheological properties of salt. Due to such properties the impact of salt extraction increases over hundreds of years and accurate determination of strains at a given moment and place is burdened with high uncertainty. Numerical modelling is useful when the model is reduced to one or several chambers. A broader range considerably lowers the accuracy and efficiency of calculations in such models. Stochastic models allow for 3D modelling of an entire mining complex, provided the model has been parametrized in detail. The process of strain and deformation modelling was presented on the example of one of the biggest salt mines in Europe, where the volume of over 21 million m3 of salt deposit was extracted. The stochastic model could be parametrized thanks to the documented measurements results of panel convergence and levelling on the surface. The use of land subsidence inversion in the least squares method allowed to estimate the optimum values of the model parameters. The correctness of the evaluation was qualitatively and quantitatively confirmed graphically by comparing modelled and measured values of subsidence. The presented model can be applied in the future extraction projects for predicting strains and deformations for an arbitrary moment.
