Prediction of the Intensive Surface Subsidences in Mining Potash Series

Baryakh, A. A.; Telegina, E. A.; Samodelkina, N. A.; Devyatkov, S. Yu.

doi:10.1007/s10913-005-0096-y

Cited by 24 publications

(10 citation statements)

References 1 publication

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“…The IPTA method can complete the extraction of high-precision deformation information in a large range, and in contrast to traditional InSAR technology, it is not seriously affected by incoherent and atmospheric delay factors [16,17]. The phase information for the interference fringes of any two images includes (1) terrain phase information; (2) level flat-earth phase information; (3) the phase of radar line-of-sight (LOS) changes between two images; (4) the atmospheric delay difference; and (5) the image noise difference [18]. During IPTA processing, the interference phase can be decomposed into:…”

Section: Ipta Timing Insar Processingmentioning

confidence: 99%

Application of Gray-Markov Model to Land Subsidence Monitoring of a Mining Area

et al. 2021

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Land subsidence monitoring in mining areas is one of the main applications of surface deformation monitoring, which is of great significance for safety production. Using the IPTA (Interferometric Point Target Analysis) time-series InSAR (Interferometry Synthetic Aperture Radar) method, land subsidence data from the new exploration area in the Weizhou mining area were analyzed and compared with static GPS (Global Positioning System) monitoring data for 2017-2020. Gray-Markov model was established by combining the gray prediction model with the Markov model to predict the surface subsidence of the mining area. The results show that (1) InSAR data have high accuracy and application potential in prediction of long-term surface deformation in mining areas; (2) The Gray-Markov model can better reflect the volatility and practicality of subsidence data in mining areas; (3) The prediction results have high accuracy, and the Gray-Markov model can serve as an effective guide for long-term surface deformation monitoring and safety management.

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Section: Ipta Timing Insar Processingmentioning

confidence: 99%

Application of Gray-Markov Model to Land Subsidence Monitoring of a Mining Area

et al. 2021

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“…Xu et al [14] studied the dynamic process of the key strata of the overlying strata on the surface subsidence. Baryarkh et al [15] established a dynamic surface subsidence prediction method with time factors. Singh et al [16] studied the formation mechanism and prediction method of surface subsidence basins.…”

Section: Introductionmentioning

confidence: 99%

Study of the Stability of the Surface Perilous Rock in a Mining Area

et al. 2022

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As a result of the mining of a C3 coal seam in a mine in Guizhou, perilous rock masses on the surface collapsed. In this study, the stability of perilous rock masses on the surface of the coal mine before and after mining was calculated and examined, and the movement law of the overlying strata in the goaf, the movement and deformation law, and the failure mode of perilous rock were analyzed. This study provides a theoretical basis for the treatment of unstable rock and coal seam mining, and has important guiding significance for the safe and efficient production of the mine. The results show that: (1) The perilous rock is in a basically stable state without the influence of mining. Through theoretical analysis and the construction of the collapse model of perilous rock, it is judged that perilous rocks W1, W3, W4, and W7 were basically stable, perilous rocks W2 and W5 were in an unstable state, and perilous rock W6 was stable without heavy rainfall. (2) As a result of the mining of the C3 coal seam, the cracks in the upper strata began to develop to the surface, and the longitudinal separation cracks gradually appeared between the surface perilous rock and the rock matrix. Due to the existence of these cracks, the perilous rock had a downward shear force. In addition, due to the heavy rainfall in the Guizhou area, the transient saturated zone of perilous rock is expanding and the strength of perilous rock is reduced. The seepage increases the sliding force of the perilous rock and aggravates the opening of cracks at any time. (3) The stability of the surface perilous rock mass is largely affected by the mining of underground coal mines. The simulation analysis was repeated using the method of setting coal pillars. When 45 m permanent protection coal pillars are set at both ends, and 15 m local protection coal pillars are set at 60 m, the safety of coal mining can be ensured without affecting the surface and perilous rock.

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“…Underground mining often causes ground subsidence at surface [1][2][3][4][5][6]. Under certain assumptions, the rate and extent of ground subsidence can be predicted in advance [7][8][9] and mitigation measures can be implemented in a timely manner [10][11][12]. In the case of the Berezniki Potash Mine 1 (Berezniki-1), it was assumed that the structural integrity of the impermeable layer of rock, known as waterproof formation, located between the ceiling of the topmost mined seam and the base of the lowermost aquifer, could be preserved indefinitely and ground subsidence contained.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Deformation Intensity above a Flooded Potash Mine Near Berezniki (Perm Krai, Russia) with SAR Interferometry

Samsonov

Baryakh

2020

Remote Sensing

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In this study we used RADARSAT-2 and Sentinel-1 Synthetic Aperture Radar data for measuring subsidence above a flooded potash mine, which is almost entirely located within the city of Berezniki (Perm Krai, Russia), population 150,000. This area has experienced very fast subsidence since October 2006 when the integrity of the Berezniki-1 mine was compromised, resulting in water intrusion, subsequent flooding and closure of the mine. Due to the ongoing dissolution of carnallite, subsidence in this region is expected to continue in the foreseeable future. In addition to rapid subsidence, at least five sinkholes have formed in the region, with the largest being 440 × 320 m. We observed ground subsidence during the period October 2011–April 2014 (RADARSAT-2) with a vertical rate up to 14 cm/year and horizontal rate up to 10 cm/year; during the period July 2016–June 2020 (Sentinel-1) with a vertical rate up to 17 cm/year. Our results were validated by precise leveling, with a coefficient of correlation of 0.75. Subsidence faster than 17 cm/year observed by precise leveling was not resolvable with Differential Interferometric Synthetic Aperture Radar (DInSAR). Our results show the complementary nature of ground-based and space-borne measurement techniques. The precise leveling captures subsidence along profile lines with high precision but lower temporal resolution, while DInSAR captures subsidence with high spatial and temporal resolutions but with lower precision. DInSAR is also significantly affected by decorrelation outside of urban areas. An important advantage of our methodology is the ability to measure the horizontal east component of the ground deformation when both, ascending and descending, data are available. This measurement directly characterizes the level of anthropogenic load on buildings and infrastructure. We recommend continuing monitoring subsidence using both measurement techniques, which can also be complemented by continuous Global Navigation Satellite System (GNSS).

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Prediction of the Intensive Surface Subsidences in Mining Potash Series

Cited by 24 publications

References 1 publication

Application of Gray-Markov Model to Land Subsidence Monitoring of a Mining Area

Application of Gray-Markov Model to Land Subsidence Monitoring of a Mining Area

Study of the Stability of the Surface Perilous Rock in a Mining Area

Estimation of Deformation Intensity above a Flooded Potash Mine Near Berezniki (Perm Krai, Russia) with SAR Interferometry

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