The article presents a methodology for analysing historical gas production data and determining the gas reserves and the petrophysical parameters of a reservoir-aquifer system. These parameters are obtained from a fitting algorithm using production data sets. A forecast of the future field gas production can be created on the calibrated mathematical model basis. The developed method is based on the material balance assumptions and the widely used Fetkovich and van Everdingen-Hurst equations for calculating water influx. To conduct the calculations and analyse production data, the computer application was developed using Python programming language. A user-friendly graphical interface makes the proposed application convenient and intuitive to use. The software was calibrated based on the literature data from the gas field of known parameters and then validated using five case studies of the actual gas fields in the Polish Carpathian Foredeep. From the tests, very high compatibility between the computed and the real field values were obtained. An additional comparison with the commercial program MatBal confirmed the proper functioning of the application.

The paper presents the author’s approach to evaluating the dynamic resistance of existing building structures exposed to the action of paraseismic events. The idea of the approach was demonstrated in the example of an existing conveyor bridge, which is an important component of an industrial plant located in an area threatened by the occurrence of mining tremors. A scenario was analysed in which the object’s structure was not adapted to absorb additional dynamic effects. Therefore, it was necessary to determine the load-bearing capacity reserve within which the dynamic effects induced by a mining tremor could be allowed. As part of the analysis, criteria for selecting the authoritative section of the analysed object for further dynamic calculations were established and described in detail. As a result of the implemented evaluation procedure, the limiting values of the ground acceleration components were obtained, which are understood as the resistance of the analysed object in the context of carrying additional dynamic actions induced by a tremor. The determined resistance is included in the ultimate limit state STR framework, which sets the level of strength of particular structures’ components as a criterion. The limit values of the ground acceleration components were calibrated, taking into account other accompanying variable actions according to the Eurocodes guidelines. The study also justified using this approach and provides essential information about dynamic excitation’s most sensitive structural components. Such information can direct the process of retrofit or necessary strengthening of the structure when the evaluated resistance will exceed the intensity of existing or predicted seismic events in the area.

Iron ore blending in an open-pit mine is an important means to ensure ore grade balance and resource recycling in iron mine industrial production. With the comprehensive recovery and utilisation of resource mining, the multi-source and multi-target ore blending method has become one of the focuses of the mining industry. Scientific and reasonable ore blending can effectively reduce the transportation cost of the enterprise. It can also ensure that the ore grade, washability index and iron carbonate content meet the requirements of the concentrator and significantly improve the comprehensive utilisation rate and economic benefits of the ore. An ore blending method for open-pit iron ore is proposed in this paper. The blending method is realised by establishing the ore blending model. This model aims to achieve maximum ore output and the shortest transportation distance, ore washability index, total iron grade, ferrous iron grade and iron carbonate content after the ore blending meets the requirements. This method can meet the situation of a single mine to a single concentrator and that of a single mine to multiple concentrators. According to the results of ore blending, we can know the bottleneck of current production. Through targeted optimisation management, we can tap the production potential of an open-pit mine.

This paper presents the results of the research aimed at improving the accuracy of predictions regarding the maximum values of resultant components for horizontal ground vibration accelerations in areas threatened by induced seismicity. The presented solution proposes a spatial model of the ground vibration attenuation relationship based on the assumptions of the Joyner-Boore model. When performing statistical analyses to verify the models, great emphasis was placed on the correctness of applied estimation methods to meet the assumptions. The starting point for introducing spatiality into the models was the occurrence of spatial autocorrelation of the residual component when estimating the structural parameters of a model with the least-squares method. Spatial interactions were presented using weight matrices, the construction of which was based on the inverse of the distance between units. During the study, it was found that the estimated spatial model of the ground vibration attenuation relationship showed a much better match with empirical data compared to the classical Joyner-Boore attenuation model.

The historical datasets at operating mine sites are usually large. Directly applying large datasets to build prediction models may lead to inaccurate results. To overcome the real-world challenges, this study aimed to handle these large datasets using Gaussian mixture modelling (GMM) for developing a novel and accurate prediction model of truck productivity. A large dataset of truck haulage collected at operating mine sites was clustered by GMM into three latent classes before the prediction model was built. The labels of these latent classes generated a latent variable. Two multiple linear regression (MLR) models were then constructed, including the ordinary-MLR (O-MLR) and the hybrid GMM-MLR models. The GMM-MLR model incorporated the observed input variables and a latent variable in the form of interaction terms. The O-MLR model was the baseline model and did not involve the latent variable. The GMM-MLR model performed considerably better than the O-MLR model in predicting truck productivity. The interaction terms quantitatively measured the differences in how the observed input variables affected truck productivity in three classes (high, medium, and low truck productivity). The haul distance was the most crucial input variable in the GMM-MLR model. This study provides new insights into handling massive amounts of data in truck haulage datasets and a more accurate prediction model for truck productivity.

Taking the sand-inrushing accident of the Selian No. 1 coal mine in the Ordos of inner Mongolia as the research background, four main factors of sand-inrushing, including sand source, channel, sand-breaking power, and flowing space, were analysed. The disaster formation process (SCPS) illustrated that sand-inrushing disasters in shallowly buried coal seams with soft surrounding rock have the characteristics of being significantly influenced by mining, the development of vertical overburden channels, and sufficient space for water-sand mixed particles to flow. Universal Distinct Element Code (UDEC) software has been used to reveal that the vertical cracks in the overburden between the coal wall and support undergo a process of development and expansion along with the cumulative stress of mining. This showed that the vertical fissure through the overburden is the main pathway for the disaster. Combined with the site conditions, disaster occurrence mechanism, and numerical simulation results, a comprehensive prevention and control technology based on the working face and roadway grouting to block the channel was proposed. It contains reasonable mining height and optimisation of advancing speed, so that safe and efficient mining of coal seams in shallow-buried soft surrounding rocks could be achieved.

Given that a source is located underground and detected by sounds that cannot be completely known or predicted, every stage of the operation from grade changes to product sales exhibits uncertainties. Parameters and constraints used in mining optimizations (sales price, costs, efficiency, etc.) comprise uncertainties. In this research, chrome open-pit resource optimization activities were performed in the province of Adana, Turkey. Metallurgical recovery, which is considered a constant as an optimization parameter in mining software, has been optimized as a variable based on fixed and variable values related to the waste material grade of processing. Based on scenario number 7, which yields the highest net present value in both optimizations, this difference corresponds with an additional $1.4 million, i.e., 7% minimum. When the number of products sold were compared, a difference of 25,977 tons of concentrate production was noted (Optimization II produces less than Optimization I). In summary, concentrated efficiency and economic findings show that using variable metallurgical recovery parameters in NPV estimation improves optimization success by reducing the level of uncertainty.

With the increase of coal mining depth, the gas content in coal seams could also become larger and larger, which could suddenly cause an inrush of gas into the longwall mining face. It is very dangerous for miners’ safety in the underground. The U-shaped ventilation pattern of longwall mining face that underground coal mines currently use is not enough to deliver sufficient air quantities to dilute gases in mining faces, which could result in the gas concentration over the required celling limit by government laws. Thus, the mine must stop production. In this paper, the high level roadway (HLR) is designed and the U + HLR new ventilation pattern is proposed to control gas emission in a longwall mining face. Using computational fluid dynamics simulation (CFD) software, the flow field and gas transportation in the mine gob are studied. The optimized ventilation parameters are summarized. It is found that the best vertical distance of the HLR is 35 m over the coal seam and the horizontal distance is 25 m from the air return roadway. It is recommended that the negative suction pressure design of the high level roadway should be ranged from 9000 Pa to 10000 Pa. Based on the study outcomes, the gas emission could be well controlled in mining faces and avoid any gas disaster accidents.

The occurrence of faults in coal seams has an impact on the possibility of methane hazard. There are several methods for identifying tectonic faults, but they cannot be applied directly to solve dynamic hazard problems in coal mine. Thus, searching for appropriate methods, that can detect faults in regional and local scales is needed. In order to meet this need, the paper proposes a new measurement method of estimating changes to the coal structure, based on profilometry measurements (roughness analysis) and application of madogram functions. Based on examining coal samples from near fault zones it was shown that the proposed approach allows us to detect changes of the coal surface that appear as the distance to a tectonic fault gets shorter. The proposed method, due to its simplicity and speed of measurement, implies a potential for practical application in the process of detecting local tectonic dislocations in coal mines.

The paper presents the results of works related to the analysis of microclimate hazards in the Crystal Caves of the Wieliczka Salt Mine. The paper focused on the development of a device for monitoring, testing and preliminary measurements of the gravimetric water content of rock in the Crystal Caves. The multisensory measurement system equipped with capacitive soil moisture sensors has been developed, calibrated and optimised. The system was used for monitoring moisture content in the sidewall and thill of the Crystal Caves.