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Faults are geological structures that can cause disasters and thereby affect the safety of coal mines. To achieve improved fault interpretation accuracy during 3D seismic exploration of coal mines, we propose a seismic fault identification method based on a combination of kernel principal component analysis (KPCA), genetic particle swarm optimization (GPSO) and a support vector machine (SVM). The Dongwupan area of the Sihe Coal Mine in Shanxi Province, which mainly contains small faults, is the research area, and we extract 20 types of seismic attributes. According to the median difference between fault and nonfault data, we select the 12 leading seismic attributes with differences greater than 0.1 in descending order. Considering information redundancy and the nonlinear relationships among seismic attributes, we adopt the KPCA method to reduce and optimize the selected seismic attributes, thereby effectively capturing the main information contained in the data and eliminating noise. Moreover, we introduce the GPSO algorithm to effectively optimize the SVM model parameters, and we construct a KPCA-GPSO-SVM model to classify and predict faults. Through model testing, the average fault identification accuracy of the model is 98.89%. Relative to the KPCA-PSO-SVM, PCA-GPSO-SVM and GPSO-SVM models, the accuracy is improved by 3.3%, 7.8% and 16.7%, respectively. We apply the proposed model to predict the fault distribution in the research area, and we compare the predictions to the actual exposed faults. The results indicate that the KPCA-GPSO-SVM model can suitably realize fault distribution prediction in a mining area. Moreover, compared to manual fault interpretation, the proposed method is faster, more intuitive and can better identify small faults.

The geophysical quality Q involved in anelastic energy absorption plays a significant role in the study of subsurface pressure, rock types and temperature distributions. However, with respect to newly collected lunar penetrating radar (LPR) data, scholars mainly focused on related parameters such as the permittivity, density and chemical composition, while the Q-value has rarely been estimated. In this study, we improved the multi-channel quality factor Q estimation method to study shallow underground structures of the Moon, interpret the geological structure and provide reference for the exploration of lunar resources. The improved windowed multi-channel Q estimation method uses multiple spatial coherence-constrained inversion to achieve a stable Q estimation of the whole direction profile in the presence of noise. An example of a numerical simulation of the simple lunar geological model illustrates the feasibility of the proposed method in estimating the Q-value. Partial lunar data collected by Chang'e-4 LPR were used to demonstrate its value with respect to the interpretation of the stratigraphic development history, dislocation and relative permittivity of the Moon.

Hot dry rock is generally buried deep within the subsurface and exhibits high temperatures, hardness and density, with low porosity and a lack of permeable fluids. It is thus difficult to investigate and poses a high exploration risk. This paper emphasizes the role of seismic exploration in evaluating hot dry rock exploration by exploiting technical advantages, including strong penetration, high resolution and precise depth determination. Denoising and weak deep effective signal processing, unique processing methods (e.g. high-precision static correction, pre-stack noise attenuation, wide-angle reflection in weak signal areas and fine velocity analysis) are used for high-quality imaging of formations inside the hot dry rock geothermal reservoirs to address the difficulties of data static correction. The joint inversion/data fusion of seismic and other geophysical methods allow the realization of non-linear quantitative prediction and evaluation of hot dry rock reservoirs. The geothermal reservoir parameters, including lithology, physical properties and temperature, are predicted by integrating various geophysical attributes. Further, the development potential of the geothermal reservoir is accurately evaluated, and promising results achieved.

SUMMARY In the process of seismic wave propagation, the presence of fractures will cause a seismic wave response associated with fracture compliance. Full waveform inversion (FWI) is an effective way to quantitatively obtain fracture compliance values, which can simulate seismic wave propagation in a fractured medium and compute the gradient expression of the fracture compliance parameters. To obtain the fracture compliance parameters quantitatively, a new technique based on FWI needs to be proposed. Based on linear slip theory, a new finite-difference scheme using a rotated grid has been developed to simulate the propagation of seismic waves in fractured media. The corresponding adjoint equation for FWI and the gradient of fracture parameter expression are presented. The crosstalk between normal compliance and tangential compliance is analysed in a homogeneous background medium. Numerical simulations in double-layer media show that the new gradient equation is effective.

Among the various geological disasters that threaten the safe operation of long-distance oil and gas pipelines, water-damage disasters are numerous and widely developed. Especially the pipelines crossing river channels or gullies are vulnerable to scouring hazards from storms and floods. A water-damage disaster physical model was established to investigate the characteristics of the riverbed scour profile and the pipeline force when the pipeline was buried at different depths under the condition of different particle size riverbed sediment. Results indicated that the equilibrium scour depth changed in a spoon shape with the gradual increase of the embedment ratio in general. The equilibrium scour depth formed by the fine sand riverbed was the largest, about 1.5 times the pipeline diameter. When the pipeline was half exposed, the clay riverbed was more resistant to the scour of the river than the riverbed of fine sand and very fine pebbles with a larger particle size. In the riverbed of three particle sizes, fine sand was more difficult to withstand the scour of the river. The scour profile formed by the sand bed around the pipeline and the force and deformation of the pipeline were related to pipeline location and riverbed sediment type. Results of this study might be useful for the safety warning and protection measures of underwater pipeline crossing.

Diffraction imaging is an important technique for high-resolution imaging because of the close relationship between diffractions and small-scale discontinuities. Therefore, we we have developed a diffraction imaging method using a mathematical morphological filter (MMF). In a common image gather, reflections have an evident energy band associated with the Fresnel zone and stationary point, whereas diffractions can be observed in a wide illumination direction and therefore have no energy band. Based on these phenomena, we analyze the amplitude distributions of the diffractions and reflections and develop a time-varying structuring element (SE) in the MMF. Based on the time-varying SE, our method can effectively suppress reflections and has the advantage of automatically preserving the diffractions energy near the stationary point. Numerical and field experiments demonstrate the efficient performance of the proposed method in imaging diffractions and obtaining high-resolution information.

Diffractions are the seismic responses of subsurface small-scale geologic discontinuities or inhomogeneities, whose energy is much weaker than that of reflections. To eliminate the masking effect of strong reflections on weak diffractions, a prestack diffraction separation method is proposed based on the common virtual source gather (CVSG) and the median filter. The reflection generated from a reflector can be regarded as originating from a virtual source (or a focused area). According to this behavior, the reflection can be transformed into its corresponding virtual source position to build the CVSG. Unlike the reflection, diffraction cannot be regarded as originating from one virtual source. Therefore, diffractions have a curved shape, whereas reflections are flat in the CVSG. Based on the traveltime moveout method, the reflection traveltime is calculated for describing reflection events and generating CVSG. Theory and a simple synthetic data test demonstrate that there is almost no energy lost when transforming between a shot gather and CVSG. Then, for removing the reflection, the median filter is used in the CVSG where the reflection appears as a linear event. Complex synthetic and field examples demonstrate that the proposed method can flatten reflection events and thus can separate diffraction events from strong reflections in the prestack domain.

A convolutional neural network (CNN) is a powerful tool used for seismic interpretation. It does not require manual intervention and can automatically detect geological structures using the pattern features of the original seismic data. In this study, we presented the development history of seismic interpretation and the application of CNN in seismic exploration. We proposed a set of CNN prediction methods and processes for coalfield seismic interpretation and realised automatic interpretation of faults and horizons based on the relationship between faults and horizons. We defined a CNN model training method based on structural geological modelling, which allowed rapid and accurate establishment of fault and horizon labels by using structural modelling. We used two examples to verify the accuracy of the algorithm, one to test for synthetic 3D seismic data and one to test for real coalfield seismic data. The results showed that CNNs can effectively predict both faults and horizons at the same time and has high accuracy. Thus, CNNs are potentially novel interpretation tools for coalfield seismic interpretation.

Accurate measurement of coalbed methane (CBM) content is the foundation for CBM resource exploration and development. Machine-learning techniques can help address CBM content prediction tasks. Due to the small amount of actual measurement data and the shallow model structure, however, the results from traditional machine-learning models have errors to some extent. We have developed a deep belief network (DBN)-based model with the input as continuous real values and the activation function as the rectified linear unit. We first calculated a variety of seismic attributes of the target coal seam to highlight the features of the coal seam, then we preprocessed the original attribute features, and finally developed the performance of the DBN model using the preprocessed features. We used 23,374 training data to train our model, 23,240 for pretraining, and 134 for fine-tuning. For the purpose of demonstrating the advantages of the DBN model, we compared it with two typical machine-learning models, including the multilayer perceptron model and the support vector regression model. These two models were trained based on the same labeled training data. The results, obtained from different models, indicated that the DBN model has the least error, which means that it is more accurate than the other two models when used to predict CBM content.

To enable a mathematical description, geologic fractures are considered as infinitely thin planes embedded in a homogeneous medium. These fracture structures satisfy linear slip boundary conditions, namely, a discontinuous displacement and continuous stress. The general finite-difference (FD) method described by the elastic wave equations has challenges when attempting to simulate the propagation of waves at the fracture interface. The FD method expressed by velocity-stress variables with the explicit application of boundary conditions at the fracture interface facilitates the simulation of wave propagation in fractured discontinuous media that are described by elastic wave equations and linear slip interface conditions. We have developed a new FD scheme for horizontal and vertical fracture media. In this scheme, a fictitious grid is introduced to describe the discontinuous velocity at the fracture interface and a rotated staggered grid is used to accurately indicate the location of the fracture. The new FD scheme satisfies nonwelded contact boundary conditions, unlike traditional approaches. Numerical simulations in different fracture media indicate that our scheme is accurate. The results demonstrate that the reflection coefficient of the fractured interface varies with the incident angle, wavelet frequency, and normal and tangential fracture compliances. Our scheme and conclusions from this study will be useful in assessing the properties of fractures, enabling the proper delineation of fractured reservoirs.

Seismic diffractions are ideal carriers of information on small-scale, discontinuous objects and can therefore be used to detect these geologic objects. However, recognizing diffractions is difficult because specular reflection with strong energy masks the weak diffraction. In this study, we propose a diffraction separation and imaging method based on a Mahalanobis-based and phase-based attenuation function used to modify the Kirchhoff migration formula in the full-azimuth dip-angle domain. In this domain, reflections are restricted to within the first Fresnel zone and are distributed in the vicinity of the stationary point, while diffractions are located across a wide range of azimuth and dip angles. Synthetic and field data applications suggest that this new method can effectively separate and image diffractions. The results also demonstrate the efficiency of the new method in clarifying subsurface small-scale objects, which can provide finer information about these structures for seismic interpretation.

Diffractions in a Ground-Penetrating Radar (GPR) data carry significant responses from near-surface small-scale fractures or karsts. However, this geological information is generally difficult to extract because of the shielding effect of strong reflections from subsurface layers. In order to solve this problem, a GPR diffraction extraction method is proposed for individually separating and imaging of GPR diffractions that incorporates a local plane-wave destruction filter with an online dictionary learning algorithm. The strong reflections are estimated and eliminated by the local plane-wave destruction method and the weak GPR diffractions are extracted by a sparse coding algorithm. In solving this model, a trust-region algorithm is used for accelerating the sparse coding procedures that can scale up gracefully to a large GPR data processing. A numerical experiment demonstrates the good performance of the proposed method in destroying strong reflections and enhancing weak diffractions from small-scale void holes. Real data application further verifies its potential value in resolving fine details of subsurface small-scale buried targets, such as pipes or void holes.

Shear wave velocity is a critical parameter for the characterization of hydrocarbon reservoirs. Compared with compressional wave velocity which almost exist in every well, shear wave velocity hasn't been recorded in those days for the older wells due to the lack of logging equipment or limited funds. Furthermore, measuring shear wave velocity is fairly time- and money-consuming as it can only be gained by the analysis of core samples conducted in the lab or from the dipole sonic imager (DSI). To cope with the above puzzles, a new methodology, by integrating extreme learning machines (ELM) and technique of mean impact value (MIV), is proposed in this paper with the support of log data collected from two wells located in unconventional shale gas reservoir in Ordos Basin, China. Based on mean impact value, a well-trained ELM model is taken to identify optimal well logs and five well logs are identified to provide the significant and valid information for the estimation of shear wave velocity. 3201 data points collected from well L4 are used in constructing the model. Compared with artificial neural network used in the former studies Levenberg-Marquardt algorithm (ANN-LM), the ELM model's prediction accuracy has been evaluated, the results indicates that the ELM model outperforms ANN-LM model with faster calculating speed and better performance. Additionally, the efficiency of the model proposed here is well investigated by using another well with 3201 data points. Through the comparison among ELM, support vector regression (SVR), convolutional neural network (CNN) and four widely known empirical formulas, what can be concluded is that ELM model is more efficient in fast calculation and high precision. From the result, it can be demonstrated that the use of ELM model, combined with the analysis of mean impact value (MIV), is a more efficient and promising method for shear wave velocity estimation process from conventional well log data, which can be recognized as a promising tool with an extended application. And this research can be applied into a software system for rapid acquisition of shear wave velocity logs.

Interpretation of geologic structures entails ambiguity and uncertainties. It usually requires interpreter judgment and is time consuming. Deep exploitation of resources challenges the accuracy and efficiency of geologic structure interpretation. The application of machine-learning algorithms to seismic interpretation can effectively solve these problems. We analyzed the theory and applicability of five machine-learning algorithms. Seismic forward modeling is a key connection between the model and seismic response, and it can obtain seismic data of known geologic structures. Based on the modeling data, we first optimized the seismic attributes sensitive to the target geologic structure and then we verified the accuracy of the five machine-learning algorithms by the cross-checking method. In this case, the random forest algorithm had the highest accuracy. So we examined the structural interpretation method based on a random forest using the 3D seismic reflection data from coalfield exploration. The prediction effect of this interpretation workflow is verified by comparison with known geologic structures on the plane and profile. The results suggest that the random forest algorithm is feasible to indicate geologic structure interpretations in the case of collapsed column and fault structures and it can effectively improve the efficiency of seismic interpretation and its accuracy. The machine-learning-based workflow provides a new technique for seismic structure interpretation in coal mining.

Separating weak diffractions in the prestack domain plays a vital role in high-resolution imaging small-scale discontinuities or inhomogeneities, which are associated with the migration paths and storage spaces for carbonate fracture-cave reservoirs. A shot-domain diffraction separation method is proposed with a SVMF (space-varying media filter) in the flattened shot domain. The diffractions with fast dynamic changings, including damping amplitudes and phase reversal, are filtered out by the spacing-varying median filter along the prediction-step directions of the flattened shot domain. The proposed method opens a possibility for separating diffractions in the shot domain and has an advantage in the traditional common-offset diffraction separation method. A numerical experiment illustrates the good performance of the proposed method in eliminating reflections and separating diffractions in the shot domain, and the field application further verifies its potential value in resolving the hidden small-scale cavities and tiny faults in carbonate reservoirs.

The uplift and denudation history of the orogenic belt and the basin–mountain coupling process have directly or indirectly affected the generation, scale, and preservation of sandstone-type uranium deposits in the eastern Junggar Basin by controlling the uranium source, lithology, facies, hydrogeology, post-generation modification, and other mineralization conditions. Taking the eastern Junggar Basin as the research area, this study proposes the constraints on sandstone-type uranium deposits by the tectonic uplift and denudation history of the orogenic belt in the basin using the apatite fission track (AFT), detrital zircon geochronology, and other methods. The results of the AFT age test and thermal path simulation indicate that the orogenic belt in the eastern Junggar Basin underwent four rapid uplifts; (from approximately 300 Ma to approximately 250 Ma, from approximately 130 Ma to approximately 90 Ma, from approximately 65 Ma to approximately 30 Ma, and from approximately 20 Ma to 0 Ma). Moreover, the timing of the uplift has a spatial trend of gradually becoming younger from south to north. The detrital zircon U-Pb age test showed that the sediment source area of the basin is mainly distributed in three age intervals, i.e., 460–390, 360–270, and 190–170 Ma. The comprehensive evaluation of the clastic sediment composition, stratigraphic distribution of the erosion source area, and thermal history showed that a large amount of exposed Carboniferous–Permian granites in the Qinglidi and Karameri Mountain erosion source areas contributed dominant sediment material and uranium sources for the Triassic and Middle and Lower Jurassic strata in the basin. The Ordovician–Early Devonian granites only provided sediment sources for the Upper Triassic and Lower Jurassic strata in the basin. Altay Mountain contributed some sediment sources for the Middle and Upper Jurassic strata after the magmatic activity and rapid uplift occurred in the Middle Jurassic. Based on the comprehensive analysis of the influence of the tectonic uplift process of the orogenic belt and the transformation of material source areas on uranium mineralization, the granites in the erosion source areas are proposed to contribute both external and internal uranium sources for uranium mineralization. Uranium mineralization mainly occurred in the tectonic retreat period after the rapid uplifts of the Cretaceous and Paleogene. It was terminated by the intensive uplift-induced stratigraphic deformation in the Miocene.

In order to achieve the goal of ecological restoration, plant irrigation, and water retention in the external dump of open-pit coal mine in the arid desert area, it is proposed to use the mudstone in the stripped material to reconstruct the surface aquiclude and improve the water holding capacity of the topsoil. By taking the Hongshaquan Open-Pit Coal Mine as the study object, the red mudstone of mining level +650 was selected as the topsoil aquiclude material through the geological survey. XRD diffraction experiments are used to determine the composition of red mudstone including kaolinite mineral, quartz, potash feldspar, albite, and illite. The moisture content of the red mudstone is 4.16% as measured by the indoor drying experiment. And the particle size of 0.5 mm, 1 mm, and 2 mm and the thickness of 5 cm, 10 cm, and 20 cm rock samples were selected to conduct the indoor soil column experiment. Three indicators of initial infiltration rate, stable infiltration rate, and average infiltration rate were obtained according to the analysis and calculation of the water column drop rate, wet peak drop rate, and cumulative infiltration rate so that the permeability law and coefficient of each group of tests can be known. The finite element transient analysis theory and numerical simulation method were adopted to verify the results of physical experiments. The research results show that +650 level red mudstone has a strong antiseepage ability, and the smaller the particle size, the better the antiseepage performance. For 0.5 mm and 2 mm particle sizes, as the paving height increases, the water-proof effect is better. The laying height of 1 mm particle size has no obvious influence on the water barrier effect. The physical simulation was confirmed to have the same result trend as the numerical simulation, both of which are quadratic functions with the error within a reasonable range.

Factors such as the hydrogeological conditions, the lithological characteristics of the columns’ components, and the lithological characteristics and stress conditions of the coal seam roof and floor are interrelated and jointly affect column collapse. In this study, the disaster-causing mechanism of column collapse was studied. Based on the system theory, a collapsed column is divided into the column and the surrounding fissure zone as two subsystems for analysis. And, the permeability coefficient of the broken rock under different conditions was measured by a self-designed equipment. The variations of the permeability coefficient for rock samples with different particle diameters, different axial pressures Pa, and different seepage velocities were further studied. Through phenomena analysis and experimental data processing, it was concluded that, under the same pressure state, smaller particle diameter meant smaller permeability coefficient; with the increase of axial pressure, the permeability coefficient decreased; and the larger the water flow velocity was, the smaller the permeability coefficient became. For particle diameter Φ = 2.5–5 mm or larger, the tiny particles formed by randomly washing and breaking in the water flow blocked some of the channels. For particle diameters smaller than Φ = 2.5–5 mm, the smaller permeability coefficient was attributed to the turbulence resulting from non-Darcy flow. The study on the permeability of the fractured rock mass clarified the mechanism of water inrush from the fissure zone of the collapsed column: the collapsed column itself was impermeable, and the permeability of the fissure zone around the collapsed column was related to the lithological characteristics of the rock within the fissure zone and the sequencing of rock strata. When mining coal in areas with collapsed columns, experiments on collapsed columns and fissure zones are prerequisites. This study has a certain referential value for coal mining in this region.

It is important to study the mechanism of water inrush on a seam floor by exploring the rules of permeability variations during rock deformation on the seam floor and in the course of fracturing as well as their responses to characteristics of the macromechanical environment such as mine ground pressure, engineering geology, and fluid mechanics. First, through the analysis of bearing pressure changes in the process of exploiting the working face, a mechanical model for the seam floor above the confined water is established. Based on the graphic data-processing software Mathcad, the computational process and methods for assessing the vertical, horizontal, and shear stresses are provided together with the corresponding variation curve of the rock stratum 5 m below the floor, covering the entire process from a position 120 m away from the working face to a position 280 m behind it. Second, the permeability coefficients of different lithologies are measured in the laboratory. For rock stratum 5 m below the floor, the corresponding external loading path is set up according to its actual stress. The actual dynamic stress environment of the rocks is simulated, and their permeability characteristics are studied. In addition, based on data fitting, the permeability coefficient variations in the mining process are determined for a rock stratum 5 m below the floor. Finally, in accordance with the permeability variation law of the floor of the working face, the seam floor is divided into six areas, namely, the compression and expansion zone, the bed separation and expansion zone, the pressure relief zone, the compression zone, the stable recovery zone, and the stability zone. Thus, the water-resisting performance of the floor can be expressed more objectively.

Seismic diffractions contain valuable information regarding small-scale inhomogeneities or discontinuities, and therefore they can be used for seismic interpretation in the exploitation of hydrocarbon reservoirs. Velocity analysis is a necessary step for accurate imaging of these diffractions. A new method for diffraction velocity analysis and imaging is proposed that uses an improved adaptive minimum variance beamforming technique. This method incorporates the minimum variance, coherence factor, and correlation properties to improve the signal-to-noise ratio and enhance correlations. Our method can make seismic diffractions become better focused in semblance panels, allowing for the optimal migration velocity for diffractions to be accurately picked. Synthetic and field examples demonstrate that the migration velocity for the diffractions can differ from that for the reflections. The results suggest that the diffraction velocity analysis and imaging method is feasible for accurately locating and identifying small-scale discontinuities, which leads to the possibility of using this approach for practical application and seismic interpretation.

The localization of diffractors is a great challenge for seismic data with a low signal to noise ratio, and it is also difficult to preserve the polarity characteristics of edge diffracted waves in the separated diffractions. In this paper, we present a method to locate the diffraction points and extract the diffractions from reflected data by using the Hilbert transform, the modified apex-shifted Radon transform (ASRT) and double-branch Radon transform. The Hilbert transform is used to weaken the impact of dominant reflection amplitude on detecting weaker diffractions in instantaneous phase data. The modified ASRT and double-branch Radon transform are applied to locate the apex of diffractions and preserve the polarity reversal of edge diffracted waves emitted from reflector discontinuities, respectively. The synthetic and real data applications illustrate that the method not only accurately locate the diffraction apices but also discriminate the responses of the small-scale scattering objects and the reflector edges.

Three-dimensional seismic survey is widely applied, but 3-D filtering technology has yet to be fully utilized for the analysis of seismic field data. The common approach is to first filter inline and then crossline. However, an effective 3-D filtering method is expected to eliminate coherent noise, such as the ground roll. We propose a 3-D Butterworth filtering method in the time-space domain. Firstly, a Butterworth-type filter in the frequency-wavenumber-domain is designed to suppress the linear noise with a specific apparent velocity. Secondly, transforming this filter to the time and space domain yields 3-D partial differential equations (PDEs), which are applied to suppress the linear noise. Factorizing the finite-difference equations in a different direction other than decreasing the 3-D PDEs to 2-D PDEs produces a highly accurate and efficient algorithm. Designing the 3-D Butterworth filter, selecting the filtering parameters, and showing its application to synthetic data and a 3-D high-density onshore seismic field data from a region in western China are discussed in detail. Numerical experiments with 3-D high-density onshore seismic field data demonstrate that it is more effective than the 3-D frequency-wavenumber-wavenumber (FKK) filtering method.

Small-scale structures and tectonic stress are known to affect the production of coalbed methane. Ultrasonic borehole image logging (UBI) can be used to identify fractures and breakout zones around the wellbore and to analyze tectonic stress fields. In this study, a variety of image processing and automated fracture detection methods were used to process and interpret the ultrasonic logging data in a coal bed methane well. Combined with other logging data in the well, this study analyzed the ultrasonic logging response characteristics of the formation lithology and structure. Statistical analysis has been completed to identify the fracturing pattern. The results showed that the dip angle and orientation of the natural fracture were related to regional tectonics. The paleo-stress field, reflected by the natural fractures, was consistent with the geological conditions, while the current stress field, reflected by the breakout zones, was found to be different from the paleo-stress field. This study proposed a new method by using fractures with associated conjugate joints, which are obtained from UBI logs, to estimate the paleo-stress orientation.

Seismic diffractions are the responses of small-scale inhomogeneities or discontinuous geological features, which play a vital role in the exploitation and development of oil and gas reservoirs. However, diffractions are generally ignored and considered as interference noise in conventional data processing. In this paper, a new scheme for velocity analysis and imaging of seismic diffractions is proposed. Two steps compose of this scheme in our application. First, the plane-wave destruction method is used to separate diffractions from specular reflections in the prestack domain. Second, in order to accurately estimate migration velocity of the diffractions, the time-domain dip-angle gathers are derived from a Kirchhoff-based angle prestack time migration using separated diffractions. Diffraction events appear flat in the dip-angle gathers when imaged above the diffraction point with selected accurate migration velocity for diffractions. The selected migration velocity helps to produce the desired prestack imaging of diffractions. Synthetic and field examples are applied to test the validity of the new scheme. The diffraction imaging results indicate that the proposed scheme for velocity analysis and imaging of diffractions can provide more detailed information about small-scale geologic features for seismic interpretation.

Coal seam thickness is of great significance in mining coal resources. The focus of this study is to determine the relationship between coal seam thickness and seismic wave amplitude, and the factors influencing this relationship. We used a wedge model to analyze this relationship and its influencing factors. The results show that wave interference from the top and bottom interfaces is the primary reason for the linear relationship between seismic wave amplitude and wedge thickness, when the thickness of the wedge is less than one quarter of the wavelength. This relationship is influenced by the dominant frequency, reflection coefficients from the top and bottom boundaries, depth, thickness, and angle of the wedge. However, when the lateral shift between the reflected waves is smaller than the radius of the first Fresnel zone, the wedge angle and change in lithology at the top and bottom layers are considered to have little effect on the amplitude of the interference wave. The difference in the dominant frequency of seismic waves can be reduced by filtering, and the linear relationship between amplitude and coal thickness can be improved. Field data from Sihe coal mine was analyzed, and the error was found to be within 4% of the predicted seismic wave amplitude. The above conclusions could help predict the thickness of coal seam by seismic amplitude.

To study the impact of modern coal mining on the overlying formation, a full-lifecycle four-dimensional seismic monitoring study has been carried out. Four seismic data campaigns have been performed using flexi-bin geometry with square bins, with total duration of 171 days. The four seismic datasets have been processed with the same processing workflow and parameters; major problems such as statics correction, signal-to-noise ratio, resolution, and consistency processing are addressed taking into account the geological features of the research area. This guarantees that remaining four-dimensional differences between the time-lapse datasets show mostly geological factors due to the coal mining and effects such as surface subsidence. Our four-dimensional seismic monitoring of modern coal mining shows that mined and unmined areas have significant zoning characteristics; coal mining has a direct impact on the overlying formation. The mining leads to obvious event subsidence, which reflects that overlying formations undergo subsidence during the mining process. The overlying formation appears as two zones called caving zone and fractured zone. We determine the fault dip of the overlying formation at one end of the working face to be 56°or so by calculation and conversion. We also see that, during the coal mining process, over time, the overlying formation has a self-recovery capability, which gradually strengthens from the roof siltstone upward to the Aeolian sandstone near the surface. The stability of 20-m coal pillars between working faces displays a strengthening trend and remains safe during the mining process due to both coal seam supporting and formation compaction effects.

We consider sparsity-constraint inversion method for detecting seismic small-scale discontinuities, such as edges, faults and cavities, which provide rich information about petroleum reservoirs. However, where there is karstification and interference caused by macro-scale fault systems, these seismic small-scale discontinuities are hard to identify when using currently available discontinuity-detection methods. In the subsurface, these small-scale discontinuities are separately and sparsely distributed and their seismic responses occupy a very small part of seismic image. Considering these sparsity and non-smooth features, we propose an effective L 2-L 0 norm model for improvement of their resolution. First, we apply a low-order plane-wave destruction method to eliminate macro-scale smooth events. Then, based the residual data, we use a nonlinear structure-enhancing filter to build a L 2-L 0 norm model. In searching for its solution, an efficient and fast convergent penalty decomposition method is employed. The proposed method can achieve a significant improvement in enhancing seismic small-scale discontinuities. Numerical experiment and field data application demonstrate the effectiveness and feasibility of the proposed method in studying the relevant geology of these reservoirs.

The identification of small faults is of great significance to safe and efficient coal mining. In this study, a support vector machine (SVM) algorithm was applied to fault recognition problems using multi-attributes acquired from the Zhaozhuang coal mine in Shanxi Province, China. Using a fault model with varying throws, we analyzed the response characteristics of eight seismic attributes in the coalfield. Correlation and cluster analyses were used to select five attributes—variance, curvature of orientation, dip deviation, dip continuity, and maximum amplitude—as training data. The fault model revealed that small faults respond weakly to these attributes. Consequently, we developed an improved method to enhance the response of small-throw faults. A particle swarm algorithm was used to find the optimal parameters for an SVM model to identify faults in the Zhaozhuang mining region. Subsequently, experimental results showed that the SVM model produced accurate fault recognition results.

Summary Time-lapse apparent resistivity monitoring carries out multiple observations for the same stratum at certain time intervals to study the temporal-spatial variations of aquifer characteristics of overlying strata, which can be repeated multiple 2D observation. Time-lapse apparent resistivity monitoring involves aspects such as data acquisition, processing and interpretation and inversion.

Large scale roof strata caving that occurs during coal extraction can irreversibly damage floor strata and result in riskier mining operations. Four research models incorporating floor water pressure were assessed for floor strata failure, using eight methods and two classification systems. A connection between floor strata failure and the coefficient of impact risk was developed. The derived equations represent a potentially effective method for providing a preliminary assessment of the risks associated with floor strata failure due to caving. A classification system of floor failure potential can be constructed to minimize risks during mining.

Studying geological fractures from seismic data not only requires performing forward modeling and backward inversion, but also required an understanding of the rock mechanisms and some geophysical hypotheses related to fractures. In this chapter, many indispensable fundamental concepts are reviewed that are associated with fracture formations, fracture types, fracture parameters, fracture detections, fracture equivalent hypotheses (effective fractures), fractured media composition, and decomposition and fracture interface boundary conditions especially, rock deformations, Anderson’s principal stresses classification (Trans Edinb Geol Soc 8: 387–402, 1905), petrophysics technologies, linear slip theory (Schoenberg in J Acoust Soc Am 68: 1516–1521, 1980), Schoenberg and Muir calculus theory (Geophysics 54: 581–589, 1989), welded contact boundary conditions, and nonwelded contact boundary conditions are explored and integrated to form a substantial body of material supporting the geological fractured media forward modeling in Chap. 3 and seismic inversion in Chap. 4 of this book.

Chapter 2 stated that the fractures play a very important role in the oil and gas production since they significantly affect the reservoir permeability, and the petrophysical detection technique is the most reliable in the integrated method for seeking fractures because it directly acquires data from the reservoir with a higher resolution. However, petrophysical data are extremely sparse and fracture patterns rapidly change, thus accurate delineation of fracture distributions in the subsurface imperatively demands geophysical seismic data that can provide global information coverage of the reservoir. The seismic measurements are wave reflection data that could imprint complex geological information with a relatively lower resolution. However, detecting fractures from seismic data is a big challenging problem because of the lack of understanding of the fracture responses in the intricate seismic data. Therefore, the main goals of this chapter are to address the problem by studying forward modeling of fractures to reveal the fracture representations in seismic data.

The synthetic seismograms for the fractures in Chap. 3 suggest that the fractures are also reflection generators for reflecting waves propagating in the media. Consequently, the recorded surface seismic data inevitably contain fracture reflections when the acquisition reservoir contains fractures. In this chapter, we derived new PP- and PS-wave reflection and transmission coefficient equations based on the principle of nonwelded boundary conditions. The new AVO equations for the horizontally fractured medium with impedance contrast are finally presented. In the new AVO equations, the reflection coefficients are divided into a welded contact part (a conventional impedance contrast part) and a nonwelded contact part (the fracture part) which makes them flexible for truly inverting for the rock properties of the fractured medium with impedance contrast.

The broken pattern of the overburden strata induced by mining has a non-ignorable effect on overlying strata movement, failure, and safety in mining production. To study the caving pattern of overlying strata and determine the calculation method of fracture pathway parameters due to roof caving induced by coal mining, the trapezoidal broken models were developed to explain and prevent water leakage, and even water inrush, during the mining process. By incorporating the variation of the volume expansion coefficient, a connection among the parameters of the fracture pathways and fracture angles, face width, and mining height could be established, which shows that the larger the degree of the fracture angle is, the smaller the value of the volume expansion coefficient and face width is with a relatively larger mining height. This relationship was also used to determine the eventual evolution configuration of the trapezoidal broken model. The presented approaches may help us to better understand the movement of overburden strata and provide an idea to help settle conflicts related to fracture space calculations induced by coal mining.

The State Key Laboratory of Coal Resources and Safe Mining at the China University of Mining and Technology organized a workshop on the large-scale geophysical laboratory model site (LGLMS) in Lincheng County, Hebei Province, People's Republic of China on 9 June 2018. The theme of the workshop was on the design and construction of the LGLMS.

The coal bed methane content (CBMC) in the west mining area of Jincheng coalfield, southeastern Qinshui Basin, is studied based on seismic data and well-logs together with laboratory measurements. The results show that the Shuey approximation has better adaptability according to the Zoeppritz equation result; the designed fold number for an ordinary seismic data is sufficient for post-stack data but insufficient for pre-stack data regarding the signal to noise ratio (SNR). Therefore a larger grid analysis was created in order to improve the SNR. The velocity field created by logging is better than that created by stack velocity in both accuracy and effectiveness. A reasonable distribution of the amplitude versus offset (AVO) attributes can be facilitated by taking the AVO response from logging as a standard for calibrating the amplitude distribution. Some AVO attributes have a close relationship with CBMC. The worst attribute is polarization magnitude, for which the correlation coefficient is 0.308; and the best attribute is the polarization product from intercept, of which the correlation coefficient is −0.8136. CBMC predicted by AVO attributes is better overall than that predicted by direct interpolation of CBMC; the validation error of the former is 14.47%, which is lower than that of the latter 23.30%. CBMC of this area ranges from 2.5 m3/t to 22 m3/t. Most CBMC in the syncline is over 10 m3/t, but it is below 10 m3/t in the anticline; on the whole, CBMC in the syncline is higher than that in anticline. Keywords: Coal bed methane content, Amplitude versus offset, AVO attribute, Correlation coefficient

Studies have identified that the methanogenic consortia live in bituminous and lignite coal beds. The two main goals of this study are to verify the existence of the consortia in anthracite and to determine whether this high rank coal bed could provide nutrients for the methanogenic consortia. Research has confirmed that types of methanogenic consortia live in the Qinshui basin and use some compounds in anthracite as carbon sources to yield biogas. Maceral analysis confirmed that volatile matter is a controlling factor in the biological methane yield process. The CH 4 and CO 2 yield process showed that the methanogenic consortia can degrade volatile matter in anthracite into bio-methane in situ. This study confirmed that the methanogenic consortia bio-degradation process can work on anthracite to increase the CH 4 concentration in the Qinshui basin, which is located in the Shanxi province and is an important methane-producing coal seam in China. It was estimated that approximately 3.0 × 10 − 2 ~ 4.0 × 10 − 2 m 3 /kg of methane can be generated in the Qinshui basin by microbial bio-degradation.

Shisanjianfang Area in the eastern margin of Taibei Sag, Tuha Basin, is an important region for oil and gas exploration. In this study, a large number of source rock geochemical data were used to analyze the geochemical characteristics of coal-measure source rocks in the Shisanjianfang Area, Tuha Basin, from three aspects, i.e., organic matter abundance, organic matter type, and organic maturity. The results show that the Jurassic Xishanyao Formation (J2x) in the study area has great thickness, continuous distribution, and high source rock maturity, and is the major source rock horizon in the study area. The seismic data are used in combination with 1D and 2D basin simulation technology to study the distribution characteristics of the source rocks in Shisanjianfang Area. The results of the simulation research on the source rock maturity history in the study area indicate the following: (1) The source rocks in the Xishanyao Formation (J2x) have a hydrocarbon generation threshold depth of 1800 m, threshold temperature of 95 °C, and hydrocarbon generation threshold time of about 162 Ma. (2) The Xishanyao Formation (J2x) has a current formation temperature of 50~110 °C and Ro of 0.6~1.1 % in the peak oil generation stage. (3) The source rock maturity in the study area is shown as being higher in the west while lower in the east, and higher in the north while lower in the south, and the favorable exploration area mainly lies in the northwest of the study area. The results of this study could have important implications for the oil and gas exploration in the margins of Xiaocaohu Sag, Tuha Basin.

A staggered-grid finite difference method is used to model seismic wave records in a coal bearing, porous medium. The variables analyzed include the order of the difference calculations, the use of a perfect match layer to provide absorbing boundary conditions, the source location, the stability conditions, and dispersion in the medium. The results show that the location of the first derivative of the dynamic variable with respect to space is coincident with the location of the first derivative of the kinematic variable with respect to time. Outgoing waves are effectively absorbed and reflection at the boundary is very weak when more than 20 perfect match layer cells are used. Biot theory considers the liquid phase to be homogeneous so the ratio of liquid to solid exposure of the seismic source depends upon the medium porosity. Numerical dispersion and generation of false frequencies is reduced by increasing the accuracy of the difference calculations and by reducing the grid size and time step. Temporal second order accuracy, a tenth order spatial accuracy, and a wavelength over more than ten grid points gave acceptable numerical results. Larger grid step sizes in the lateral direction and smaller grid sizes in the vertical direction allow control of dispersion when the medium is a low speed body. This provides a useful way to simulate seismic waves in a porous coal bearing medium.

The fly ash from the Jungar Power Plant, Inner Mongolia, China, is unique because it is highly enriched in alumina (Al2O3 > 50%). The fly ash mainly consists of amorphous glass and mullite and trace amounts of corundum, quartz, char, calcite, K-feldspar, clay minerals, and Fe-bearing minerals. The mullite content in fly ash is as high as 37.4% because of high boehmite and kaolinite contents in feed coal. Corundum is a characteristic mineral formed during the combustion of boehmite-rich coal. Samples from the economizer were sieved into six size fractions ( 500 mesh) and separated into magnetic, mullite + corundum + quartz (MCQ) and glass phases for mineralogical and chemical analysis. The corundum content increases but amorphous glass decreases with decreasing particle size. Fractions of small particle sizes are relatively high in mullite, probably because mullite was formed from fine clay mineral particles under high-temperature combustion condition. Similarly, fine corundum crystals formed in the boiler from boehmite in feed coal. The magnetic phase consists of hematite, magnetite, magnesioferrite, and MgFeAlO4 crystals. The MCQ phase is composed of 89% mullite, 6.1% corundum, 4.5% quartz, and 0.5% K-feldspar. Overall, the fly ash from the power plant is significantly enriched in Al2O3 with an average of 51.9%, but poor in SiO2, Fe2O3, CaO, MgO, Na2O, P2O5, and As. Arsenic, TiO2, Th, Al2O3, Bi, La, Ga, Ni, and V are high in mullite, and the magnetic matter is enriched in Fe2O3, CaO, MnO, TiO2, Cs, Co, As, Cd, Ba, Ni, Sb, MgO, Zn, and V. The remaining elements are high in the glass fraction. The concentration of K2O, Na2O, P2O5, Nb, Cr, Ta, U, W, Rb, and Ni do not clearly vary with particle size, while SiO2 and Hg decrease and the remaining elements clearly increase with decreasing particle size.