Mining Deformation Research Articles

Life Cycle Mining Deformation Monitoring and Analysis Using Sentinel-1 and Radarsat-2 InSAR Time Series

The life cycle of mining results in various patterns of surface deformation as it progresses through development, production, and reclamation. Therefore, the spatial–temporal patterns of ground deformation provide a crucial indicator to understand the mining activities, related geohazards, and environmental restoration. This study investigates the decadal deformation (2012–2022) of three coal mines during different stages of mines’ life cycles in Henan, China, using radar interferometry with Radarsat-2 and Sentinel-1 data. The results reveal multiple deformation patterns across different areas: the Changcun mine area changed from ground subsidence to uplift following the termination of exploitation in 2016; the Xiadian mine area has been continuously developing over the past decade, resulting in a cumulative subsidence of 55.6 mm; and the Liyuan mine area exhibits surface rebound at a rate of 7.9 mm/year since its closure in 2007. We also probe the mining geometry of the production process by using a rectangular model. This study highlights the significance of long-term InSAR observations and deformation modeling in elucidating the mining operation dynamics of small mining zones in their production, transition, and post-closure periods, thereby facilitating the management of small-scale mining.

Analysis of surface deformation and related factors over mining areas based on InSAR: A case study of Fengcheng mine

Abstract. Ground surface deformation in mines affects mining production, damages the ecological environment, and endangers human safety. Mastering the detailed time series deformation and related triggering factors can provide key information for the safety of the mining area. Therefore, the Fengcheng mining area, a large and ancient coal mine in Jiangxi Province, China, was selected as the study area in this work, and the following research was conducted: 1. The accuracy and applicability of the Stacking, Small-Baseline Subset InSAR (SBAS-InSAR), and Interferometric Point Target Analysis (IPTA) methods were preliminarily explored while monitoring the annual deformation rate based on Sentinel-1A data from October 2019 to November 2022. 2. The time-series deformation of the Fengcheng mining area was obtained with SBAS-InSAR technology, and the sedimentation was validated with leveling results. 3. The correlation factors of deformation, such as rainfall and land cover, were studied, and the relationship between the influencing factors, such as coal mining dip angle, digital elevation, coal mining elevation, and deformation, was quantitatively explored with the Grey correlation model and Pearson correlation analysis method. The following conclusions were drawn: The SBAS method has the best adaptability in the dense vegetation mining area, and the root-mean-square error of the difference between deformation results and leveling data does not exceed 4mm. The evolution process of deformation centers is mainly divided into the stages of initial deformation, constant velocity deformation, accelerated deformation, and stable condition. Compared with the natural factors, the settlement of the Fengcheng mining area is mainly affected by human-induced mining and construction of artificial facilities.

Research on operation characteristics of hoisting conveyance under mining deformation action in mine vertical shaft

Research on operation characteristics of hoisting conveyance under mining deformation action in mine vertical shaft

Mining Deformation Monitoring Based on Lutan-1 Monostatic and Bistatic Data

Coal mining leads to surface subsidence, landslides, soil erosion and other problems that seriously threaten the life and property safety of residents in mining areas, and it is urgent to obtain mining subsidence information using high-frequency, high-precision and large-scale monitoring methods. Therefore, this paper mainly studies the deformation monitoring of the Datong mining area using Lutan-1 monostatic and bistatic SAR data. Firstly, the latest Lutan-1 bistatic data are used to reconstruct the DSM, and the interferometric calibration method is used to improve the accuracy of the DSM. Then, the surface deformation monitoring of the mining area is implemented by using DInSAR, SBAS-InSAR and Stacking-InSAR with the reconstructed DSM data and Lutan-1 monostatic SAR data. Finally, the deformation monitoring results are compared with the surface deformation results based on the TanDEM data, and both the results are evaluated using the filed leveling data. Taking 20 images covering the Datong mining area as the data sources, the surface deformation results obtained using different InSAR methods in the mining area were quantitatively evaluated and analyzed. The results indicated that: (1) the DSM obtained using the Lutan-1 bistatic SAR data was assessed and demonstrated with the ICESat laser altimetry data an error of 2.8 m, which meets the Chinese 1:50,000 scale DEM cartographic accuracy standard, and the difference analysis with the TanDEM data shows that the terrain changes are mainly distributed in mountainous areas; (2) Due to the improvement in resolution, the registration accuracy of the SAR images and LT-DSM is higher than that of the TanDEM data in the range direction and azimuth direction; (3) Via evaluation with the filed leveling data, it is found that the surface deformation measurement results based on LT-DSM are less affected by terrain, and the accuracy of LT-DSM-SBAS and LT-DSM-DInSAR is improved by 11.5% and 16.3%, respectively, compared with TanDEM-SBAS and TanDEM-DInSAR, which demonstrates the effectiveness of the Lutan-1 bistatic and monostatic data for mine deformation monitoring.

The Impact of Mining Deformations on Road Pavements Reinforced with Geosynthetics

The Impact of Mining Deformations on Road Pavements Reinforced with Geosynthetics

Assessing the application of GACOS atmospheric correction for DInSAR-based mining deformation monitoring by using Sentinel-1 data in Upper Silesian Coal Basin in Poland

Assessing the application of GACOS atmospheric correction for DInSAR-based mining deformation monitoring by using Sentinel-1 data in Upper Silesian Coal Basin in Poland

A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset

This paper presents a strategy for extracting three-dimensional (3D) mining deformation from a single-geometry synthetic aperture radar (SAR) dataset. In light of the directionality of horizontal displacement caused by underground mining, we first re-model the proportional relationship between horizontal displacement and horizontal gradient of subsidence. Afterward, to improve the stability of the re-model, a solution strategy is proposed by setting different solution starting points and directions. The proposed method allows hiring of arbitrary single-geometry SAR data (e.g., air-borne, space-borne, and ground-borne SAR data) to reconstruct 3D displacements of mining areas. The proposed method has been validated through simulation and in-site data. The simulation data monitoring results indicate that the root mean square errors (RMSE) of the 3D displacements extracted by the proposed strategy are 0.45, 0.5, and 2.98 mm for the vertical subsidence, east–west, and north–south horizontal displacements, respectively. The in-site data monitoring results indicate that the RMSE of vertical subsidence compared with the leveling data are 7.3 mm. Furthermore, the MSBAS method was employed to further validate the reliability of the proposed method, the results show that the proposed method is effective to obtain the 3D deformation of the mining area, which greatly improves the applicability of SAR interferometry in the 3D deformation monitoring of the mining areas.

Experimental study on instability mechanism and critical intensity of rainfall of high-steep rock slopes under unsaturated conditions

Two critical factors, namely intense precipitation and intricate excavation, can trigger rock mass disasters in mining operations. In this study, an indoor rainfall system was developed to precisely regulate the flow and intensity of precipitation. A large-scale model experiment was conducted on a self-designed physical simulation experiment platform to investigate the failure and instability of high-steep rock slopes under unsaturated conditions. The real-time reproduction of the progressive failure process in high-steep rock slopes enabled the determination of the critical rainfall intensity and revealed the mechanism underlying slope instability. Experiment results indicated that rainfall may be the primary factor contributing to rock mass instability, while continuous pillar mining exacerbates the extent of rock mass failure. The critical failure stage of high-steep rock slopes occurs at a rainfall intensity of 40 mm/h, whereas a rainfall exceeding 50 mm can induce critical instability and precipitation reaching up to 60 mm will result in slope failure. The improved region growing segmentation method (IRGSM) was subsequently employed for image recognition of rock mass deformation in underground mines. Herein an error comparison with the simple linear iterative cluster (SLIC) superpixel method and the original region growing segmentation method (ORGSM) showed that the average identification error in the X and Y directions by the method was reduced significantly (1.82% and 1.80% in IRGSM; 4.70% and 6.26% in SLIC; 9.45% and 12.40% in ORGSM). Ultimately, the relationship between rainfall intensity and failure probability was analyzed using the Monte Carlo method. Moreover, the stability assessment criteria of rock slope under unsaturated condition were quantitatively and accurately evaluated.

Research on the spatiotemporal prediction of mining deformation with subcritical extraction integrated with D-InSAR technology

The prediction of surface movement and deformation in the mining area is of great significance to the production of the mining. Since the differential interferometry synthetic aperture radar measurement (D-InSAR) technology cannot predict the deformation caused by mining face, and the existing probability integral method (PIM) prediction model can only predict final mining deformation under critical extraction. Therefore, on the basis of PIM prediction model, the simplified Boltzmann function and Gompertz time function were introduced to form the BPIM dynamic prediction model for the analysis of temporal and spatial characteristics of the mining area. The parameters of BPIM model are inversed by D-InSAR monitoring data combined with optimization algorithm, and the mining of the working face is followed by the dynamic forward prediction of the changes in temporal and spatial characteristics. In addition, we analyzed the sensitivity of the main parameters in the model to the predicted results and the variation relationship of the model subsidence coefficient with the mining of the working face. When the model was applied to the working face of Guobei coal mine, the RMSE of the BPIM dynamic prediction model is 25.1 mm. Constructed with the previous dynamic prediction model established by conventional methods, its deformation accuracy under the prediction of subcritical extraction on the surface of the mining area is improved by 58.7%. The results demonstrated that the BPIM dynamic model effectively avoids the problem of large prediction results under subcritical extraction, and can provide some suggestions for the planning and production of the mining area.

Research on the inherent mechanism of rock mass deformation of oil shale in-situ mining under the condition of thermal-fluid-solid coupling

With the gradual maturity of in-situ mining technology of oil shale, environmental geological problems such as ground subsidence after mining become increasingly important. The existing researches focus more on the improvement of mining technology, but less on the deformation of oil shale after mining. In this study, various experiments are used to test the pore characteristics and mechanical properties of oil shale with temperature. It is found that parallel bedding macro fractures are formed during oil shale pyrolysis, and the mechanical properties change differently in parallel and vertical bedding directions. The anisotropy of mechanical properties of oil shale is related to the anisotropy of pore structure for the first time to explains the mechanism of deformation. Moreover, the constitutive model of in-situ mining deformation of oil shale is established through statistical damage mechanics combined with pore structure. The deformation of in-situ mining of oil shale under thermal-fluid-solid coupling condition is studied by combining the constitutive model with multi-field coupling numerical simulation. The results show that the compression deformation of oil shale is about 6.5 cm per meter at 200 m underground, and the impact of in-situ mining on geological environment is less than that of traditional mining methods.

Research of deformation law about guide rails under the action of mining deformation in mine vertical shaft

To lay a foundation for alleviating the influence of mining shaft deformation (MSD) on the guide rail (GR) and monitoring the shaft deformation state, this paper studies the deformation law and mechanism of the guide rail under the MSD. Firstly, a spring is used to simplify the interaction between the shaft lining and surrounding rock soil mass (SRSM) under MSD, and its stiffness coefficient is deduced by the elastic subgrade reaction method. Secondly, a simplified finite element model is established based on spring element, the stiffness coefficient is calculated by the derivation formula, and its effectiveness is verified. Finally, the deformation law and mechanism of GR are analyzed under different types and degrees of MSD, and the deformation characteristics are studied under the disconnection between the shaft, bunton and guide rail. The results show that the established finite element model can better simulate the interaction between the shaft lining and SRSM, and the calculation efficiency is greatly improved. The guide rail deformation (GRD) has a strong ability to characterize MSD and owns the distinctive feature corresponding to different types and degrees of MSD and the connection state. This research can provide reference and guidance for the shaft deformation monitoring and the maintenance and installation of the GR, and also lays a groundwork for studying operation characteristic of hoisting conveyance under MSD.

Predicting Young’s modulus of Indian coal measure rock using multiple regression and artificial neutral network

Accurate information on Young’s modulus (E) is required for simulating rock deformation in mines; on the other hand, it is very cumbersome to obtain in the laboratory and collecting drilled cores in sufficient amounts, especially in the case of soft rocks, is quite impossible. Empirical equations were deducted for E from easily determinable rock properties, and the final model was selected through different statistical strength parameter tests. The generalization of the equation was verified through the normal distribution tests of residues of the equation. R2 came to be 0.609 and was validated using an artificial neural network with an improved value of 0.73

Raw Gangue Filling Mining under Construction <br/>—A Case Study in China

In order to recover the strip pillar coal resources, reduce the amount of gangue mountain and realize remediation of the goaf environment in the old mining area, the raw gangue filling mining technology was proposed. According to the previous practical experience, the feasibility of the implementation of raw gangue filling mining technology in the coal-pressed area was analyzed. Through the filling gangue compaction test, the deformation under different loading stages was obtained. Further, a reasonable prediction of the deformation beyond the experimental limited loading load was made based on the experimental results. Through the deformation source analysis of the whole process of gangue filling, the key factors for controlling deformation before, during, and after filling were determined. Additionally, the proportion of deformation during different stages was quantified. Considering the protection of surface buildings, mining fullness of the working face and mining technology, the production parameters of 1209 and 1210 filling working faces were preliminarily determined. Through numerical simulation, the rationality of mining scheme was verified. Based on the practice of 1209 working face and the key factors to control the deformation of gangue filling, the mining system and process in 1210 working face were optimized. According to the measured surface rock movement, raw gangue filling mining technology can meet the requirements of surface building protection level. Especially, this paper provides a method to quantitatively calculate the equivalent mining height (EMH) of raw gangue filling and its mining deformation, which has reference significance for old mining areas.

Underground mine deformation monitoring using Synthetic Aperture Radar technique: A case study of Rajgamar coal mine of Korba Chhattisgarh, India

Coal mines are the major source of energy in industries and are important indicators of the economic growth of a country. Excessive withdrawal of coal from underground coal mines without stowing leads to surface deformation. In this study, Synthetic Aperture Radar Technology has been used to identify the surface deformation in the Korba Coal Mines of India. Korba coal mines are major coal-producing mines in India that come under South Eastern Coalfields Limited (SECL). It covers three underground mines. Depillaring has been done through the caving method, which may lead to the deformation of the area and its surroundings. Deformation may have devastating consequences if overlooked. So, it requires continuous monitoring of the area. Space-based SAR interferometry is the most preferred technique to monitor any mining area over a period of time. In this technique, known as the DInSAR technique, a deformation map can be generated from images of the same area acquired over different points of time. In the present study, images of the month of February of the years 2015, 2016, 2017, and 2019 have been successfully utilized for DInSAR analysis over the Rajgamar area. The Interferogram allows analysis of an entire mine site including pits and their surrounding area. High precision monitoring over wide coverage enables to bring out accurate deformation results due to the presence of coherent targets and monitoring risk across the study area. Maps generated from data were scrutinized and interpreted. Consequentially, 2015–2016 shows greater deformation than the other two corresponding maps generated 2015–2017 and 2015–2019 data. Results were validated through ground observations. Overall the area of the Rajgamar coal mine is getting deformed at a slow rate.

Application of Machine Learning in Forecasting the Impact of Mining Deformation: A Case Study of Underground Copper Mines in Poland

Open access to SAR data from the Sentinel 1 missions allows analyses of long-term ground surface changes. The current data-acquisition frequency of 12 days facilitates the continuous monitoring of phenomena such as volcanic and tectonic activity or mining-related deformations. SAR data are increasingly also used as input data in forecasting phenomena on the basis of machine learning. This article presents the possibility of using selected machine learning algorithms in forecasting the influence of underground mining activity on the ground surface. The study was performed for a mining protective area with a surface of over 500 km2 and located in western Poland. The ground surface displacements were calculated for the period from November 2014 to July 2021, with the use of the Small Baseline Subset (SBAS) method. The forecasts were performed for a total of 22 identified subsidence troughs. Each of the troughs was provided with two profiles, with a total of more than 10,000 identified points. The selected algorithms served to prepare 180-day displacement forecasts. The best results (significantly better than the baseline) were obtained with the ARIMA and Holt models. Linear models also provided better results than the baseline and their performance was very good at up to 2 months forecasting. Tree-based models including their sophisticated ensemble versions: bagging (Random Forest, Extra Trees) and boosting (XGBoost, LightGBM, CatBoost, Gradient Boosting, Hist Gradient Boosting) cannot be used for this type of predictions since Decision Trees are not able to extrapolate and thus are not a valid stand-alone tool for forecasting in this type of problems. A combination of satellite remote sensing data and machine learning facilitated both the simultaneous quasi-permanent monitoring of ground surface displacements and their forecasting in a relatively long time period.

Research on the Applicability of DInSAR, Stacking-InSAR and SBAS-InSAR for Mining Region Subsidence Detection in the Datong Coalfield

Intensive and large-scale underground coal mining has caused geological disasters such as local ground subsidence, cracks and collapse in the Datong coalfield, China, inducing serious threats to local residents. Interferometric synthetic aperture radar (InSAR) has the capability of surface deformation detection with high precision in vast mountainous areas. DInSAR, stacking-InSAR and SBAS-InSAR are commonly used InSAR-related deformation analysis methods. They can provide effective support for mine ecological security monitoring and prevent disasters. We use the three methods to conduct the deformation observation experiments in the Datong coalfield. Sentinel-1A data from November 2020 to October 2021 are used. As a result, a total of 256 deformations in the Datong coalfield were successfully detected by the three methods, of which 218 are mining deformations, accounting for 85% of the total deformations. By comparing the results of the three methods, we found that DInSAR, stacking-InSAR, and SBAS-InSAR detected 130, 256, and 226 deformations in the Datong coalfield, respectively, while the deformations caused by coal mining were 128, 218, and 190. DInSAR results with long spatiotemporal baselines are seriously incoherent. SBAS-InSAR results of displacement rate are more precise than stacking-InSAR, and the mean standard deviation is 1.0 mm/a. However, for areas with lush vegetation or low coherence, SBAS-InSAR has poor performance. The detection deformation area results of DInSAR and SBAS-InSAR are subsets of stacking-InSAR. The displacement rates obtained by stacking-InSAR and SBAS-InSAR are consistent; the mean difference in the displacement rate between the two methods is 2.7 mm/a, and the standard deviation is 5.1 mm/a. The mining deformation locations and their shapes in the study area can be identified with high efficiency and power by stacking-InSAR. Therefore, with a comprehensive understanding of the advantages and limitations of the three methods, stacking-InSAR can be an effective and fast method to identify the level, location and range of mining deformation in lush mountainous areas.

Application of Optimized Grey-Markov Model to Land Subsidence Monitoring With InSAR

Land subsidence prediction in mining areas is one of the most important applications of land deformation monitoring, which is significance for safe production. We used interferometric point target analysis (IPTA) timing series interferometry synthetic aperture radar (InSAR) processing technology to analyze the land subsidence results for the Xinfa mining area from 2017 to 2020; and compared them to global positioning system (GPS) static monitoring data. We proposed a residual correction theory based on deviation coefficient using the grey prediction and Markov models, and an optimized Grey-Markov model (RGM-M model) was established to predict the land subsidence of the mining area. Our results show that: (1) The maximum difference between InSAR timing processing results and GPS monitoring data in the same period is 10.91mm; they have roughly the same subsidence trend, indicating that IPTA timing series InSAR technology are strongly reliable in mining deformation. (2) Compared to the traditional Grey-Markov model, the improved residual correction and dynamic assignment of the Grey-Markov model improves the prediction accuracy. The optimized residual correction and dynamic empowerment of the Grey-Markov model prediction results are more suitable for the actual fluctuation of land subsidence value in the mining area. The maximum root mean square error of the prediction results is 0.751mm, and the maximum average absolute percentage error is 7.46%, which has a certain guiding significance for the work of monitoring, prediction and safety management of land deformation in the mining area.

Prediction of Mining-Induced Kinematic 3-D Displacements From InSAR Using a Weibull Model and a Kalman Filter

Accurately predicting ground surface deformation is a crucial task in mining-related geohazards control. Interferometric synthetic aperture radar (InSAR) technique can widely detect historical line-of-sight (LOS) displacements with a high spatial resolution. By incorporating with spatio-temporal deformation models, InSAR can predict kinematic 3-D displacements due to underground mining. However, this method depends on the geometric parameters (at least seven generally) of underground mined-out areas, hindering its practical applications especially over a large area. To circumvent this, we proposed a new method for predicting kinematic 3-D mining displacements by incorporating InSAR with a temporal model, rather than spatio-temporal models used before, in this article. In doing so, much less prior parameters (only three and can be empirically given) are required, with respect to the previous InSAR-based methods. To achieve this, we first revealed that InSAR LOS displacements caused by underground longwall mining at a single point temporally follow an S-shaped growth pattern. Meanwhile, we also showed that a Weibull model can describe the temporal evolution well. Based on these findings, the proposed method first predicts, in a point-wise manner, the kinematic LOS mining displacements from historical InSAR measurements using the Weibull model and a Kalman filter. The kinematic 3-D displacements are then resolved from the predicted LOS displacements with the help of a common prior information relating to mining deformation. The proposed method was tested in the Datong coal mining area of north China. The results show an averaged accuracy of about 0.007 m of the resolved kinematic 3-D displacements.

Cause and Solution to Roadway Deformation in Vietnam Underground Coal Mines

The deformation and support method of roadways have always been important issues in safemining and production. Vinacomin's statistics show that, by 2021, there will be 64.19 km of roadwaysthat need to be repaired (accounting for 25% of the total new roadways). Thus, the problem of maintainingroadway stability is facing difficulties in underground coal mines in Vietnam. To find out the causes ofroadway failures, a case study at roadways of the Khe Cham I and Khe Cham III coal mines, Vietnam, ispresented in this paper. Based on the results of a detailed field survey, the deformation characteristics ofroadways and the failure mode of support structures were investigated. The results show that the roadwaydeformation is severe and the main support cannot control surrounding rock mass. Also, the destructionof support structure is frequent on reused roadways, affecting production efficiency and work safety.Therefore, to reduce deformation and increase roadway stability, a new support method called “multistageanchor of rock bolt + cable bolt” has been developed and a new longwall mining system with criticalcoal pillar width has been proposed. The new findings of the research can provide references for scientificstudies, and apply them in Vietnam's underground coal mine practices.

Deformation and damage to buildings caused by ground movements in mining areas (case study)

Human activity causes transformations in the near-surface layers of the rock mass, which result in long-term impacts on buildings and engineering infrastructure. Mining activities are particularly disadvantageous in this context, as they trigger severe deformation processes that reach the soil surface as a result of the excavation of deposits. The prevention of accidents and disasters caused by these impacts is based on knowledge derived from observation. Therefore, the aim of this study was to acquire and update knowledge on the impact of mining-related ground deformation and tremors on buildings. The paper presents the results of measurements carried out on a group of buildings located in an underground mining area. The buildings have been affected by mining impacts since their construction in the 1980s. Despite the implementation of appropriate structural protection, the structures have been suffering deformation and damage. For the purposes of the study, two two-axis inclinometers were installed on the 15.2 m high bell tower, taking measurements at 6-hour intervals. Over a period of 10 months, changes in the leaning of the tower were measured and the condition of the other buildings observed.The study resulted in obtaining:
 
 values for the change in tilt of the two perpendicular walls of the tower (over a period of 10 months),
 correlation of the results with tremors measurements and periodic surveying measurements of the inclination of the vertical edge of the tower,
 image of damage to buildings caused by mining deformation of the ground.
 
 On the basis of an analysis of the location and timing of minefields excavation, the occurrence of real ground movement in the mining areas, continuing even after the end of mining works, was confirmed and irregular deformation of the originally perpendicular walls of the masonry tower building was demonstrated. The tower did not behave as a rigid body; its horizontal profile was deformed.