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In this paper, we first derive the dynamic solution in a transversely isotropic (TI) elastic and layered half-space, induced by a time-harmonic vertical load on its surface. The solution is obtained via the efficient and unconditionally stable dual variable and position (DVP) matrix method along with the fast Fourier-Bessel series (FBS) expansion approach. In order to study the effect of material anisotropy, the degree of anisotropy, namely the ratio of the horizontal Young's modulus over vertical Young's modulus, is introduced as the key parameter, with a very reasonable assumption on other involved elastic constants in the layered TI half-space. This enables us to investigate the effect of material anisotropy on the wave Green's functions, dispersion curves, ellipticity, and polarity. By comparing with the effect of Poisson's ratio in the corresponding layered isotropic (ISO) half-space, we observe that nearly all the wave features with varying degrees of anisotropy in the TI layered half-space are similar to those with varying Poisson's ratio in the corresponding ISO half-space. This indicates the challenge or non-uniqueness in the inversion of TI velocity profiles using vertical surface loading only. • Unconditionally stable DVP matrix method is combined with the fast Fourier-Bessel series expansion. • Wave characteristics are comprehensively examined in terms of Green's function, waveforms, ellipticity, and polarity. • A more reasonable assumption of independent TI elastic constants is proposed to better represent the degree of anisotropy. • Degree of anisotropy is found to have similar effect on all aspects of wave characteristics as Poisson's ratio. [ABSTRACT FROM AUTHOR]

The paper presents an electromagnetic geothermometer-based two-dimensional temperature model for the Travale (Italy) enhanced geothermal system derived from magnetotelluric and temperature data. Joint analysis of the temperature and electrical resistivity models made feasible a new self-consistent conceptual model of this site, which agrees with available geological data and previous geophysical results. It explains the nature of seismic reflection horizons detected in 1978 and unusual seismicity distribution in depth which could not be properly addressed earlier without temperature predicting beyond boreholes. It is concluded that the heat source feeding this system may be a granitic intrusion located at a depth below 4 km, which corresponds to the isotherm of 600 °C. A sharp temperature gradient above this intrusion forms a contact thermo-metamorphic halo in the depth range of 3–4 km. Assessment of the released fluid volume fraction from the electrical resistivity model indicates that the general amount of thermo-metamorphic and magmatic fluids in the rock-dominated Travale geothermal system is negligible. It is concluded that meteoric waters are the main source of fluids penetrating along normal faults up to 3 km. Despite some supercritical fluids of thermo-metamorphic origin could circulate in the system below this depth, their amount is hardly sufficient for economically justified exploration drilling. The results of the study indicate that building the temperature model of the geothermal area is crucially important for the exploration of enhanced geothermal systems. • Temperature model of the Travale geothermal area is built using EM geothermometer. • New conceptual model of the Travale geothermal system is suggested. • Nature of two seismic reflecting horizons detected 45 years ago is explained. • Maximal number of earthquake hypocenters in the depth range 3–4 km is explained • Amount of supercritical fluids below 3 km does not justify exploration drilling. [ABSTRACT FROM AUTHOR]

Reconstructing in different partitions independently is one of the effective strategies to implement 3D seismic data reconstruction. However, if this strategy is used, the underlying correlations between two adjacent partitions will be neglected. To solve this problem, this paper introduces curvelet transform and provides an improved projection onto convex sets (POCS) method with weighting operator, based on the continuity between two adjacent time slices, to reconstruct each time slice. For each time slice, we constructed this weighting operator based on the support estimation given by the adjacent reconstructed time slice in curvelet domain. Thereby, we provided a 3D seismic data reconstruction method using prior support information. The experiments for both synthetic data and field data demonstrated that our method is superior to the traditional POCS. • Three-dimensional seismic data reconstruction using prior support information. • Better effect and higher convergence speed than traditional method. • Easy to expand to higher-dimensional reconstrution. • Easy to combine with different sparse transformations. [ABSTRACT FROM AUTHOR]

Reliable density information is an essential factor in lithologic interpretation and reservoir evaluation. However, density reconstruction is hampered by a lack of long-wavelength information and the crosstalk between different parameters. The powerful nonlinearity in density inversion constrains the multi-parameter full waveform inversion application. This paper introduces the Wasserstein distance into the full waveform inversion for velocity and density based on the optimal transport theory. We construct an objective function with better convexity to avoid the cycle-skipping caused by the poor initial model. Furthermore, due to the sensitivity of the quadratic Wasserstein distance to low-frequency, we add the low-wavenumber component absent in the conventional density inversion. We acquire a long-wavelength density background using optimal transport inversion and then apply it as an initial model for least-squares inversion. Numerical examples show that our optimal transport inversion effectively builds a reasonable density background model for FWI. Density inversion can be improved by incorporating optimal transport and least-squares theory, leading to a reliable quantitative description for petroleum exploration and development. • Introducing the Wasserstein distance into full waveform inversion to build a low wave-number density structure. • Developing a stepwise density inversion approach utilizing the least squares norm and Wasserstein distance. • Mitigating the impact of inaccurate initial models on density inversion. • Improving stability and accuracy of density reconstruction compared to conventional inversion. [ABSTRACT FROM AUTHOR]

Accurate fault identification provides an important basis for well location deployment, oil and gas resource development. However, obtaining a large number of fault samples through manual labeling or interpretation is difficult. Conventional convolutional neural networks have certain challenges in finely characterizing low-order faults and fault continuity. This paper studies a 3D intelligent fault identification method that integrates deep learning with attention mechanism. Based on 3D-UNet network, the method constructs a dual attention fault identification model with an encoder-decoder structure, which focuses on enhancing low-order fault information and extracting key features. An adaptive hybrid loss function is proposed to address the imbalance problem of fault proportions in seismic amplitude data. The function introduces an adjustment coefficient to adaptively enhance the attention to high-order or low-order faults according to the actual situation of the fault, improving the accuracy and continuity of fault identification. Furthermore, a model re-training learning optimization method is presented to capture the missed fault information in the first training and repair the connectivity of low-order faults. Applying this method to the synthetic data set, the accuracy can be improved to 0.9732, and the loss can be converged to 0.0982. The results of shale reservoirs in the North Sea Basin and Kerry-3D indicate that the method can reduce the situation of fault missing and misidentification, effectively improve fault identification accuracy, and enhance low-order fault identification by obtaining more contextual fault features. • A seismic fault image segmentation network is developed with attention mechanism. • Construct an adaptive hybrid loss function to solve the problem of data imbalance. • A method retraining learning that integrates theory and predictive data is proposed. [ABSTRACT FROM AUTHOR]

As a result of the combined influence of multi-stage and multi-directional tectonic activities, the subsurface medium in complex structural areas can easily develop intricate fault systems with varying scales and directions. Post-stack seismic and azimuth-stack attributes have limited precision in recognizing such complex fault systems. In this paper, we propose an adaptive fault enhancement workflow in offset vector tile (OVT) domain based on anisotropy theory to improve the recognition ability of seismic data for multi-directional faults and minor faults. The vertical directions of fault strikes and tectonic strikes estimated by the gradient structure tensor (GST) can be used as sensitive observation azimuths of faults. At the same time, according to the anisotropic forward modeling and real data amplitude variation with offset (AVO) analysis of minor faults in marine shale of Wufeng-Longmaxi formations in Sichuan Basin, China, the incident angles with the largest difference between isotropic and anisotropic reflection coefficients can be used as sensitive incident angles of faults. A new fault enhancement seismic data can be reconstructed from the OVT gathers by traversing the sensitive azimuths and incident angles adaptively. The 3D model and real data indicate that the faults enhanced by the workflow we proposed are clearer in shape, smaller in scale, and richer in details, which is consistent with geology and well. • We propose an adaptive fault enhancement workflow in OVT domain. • The workflow considers the azimuth and incidence contained in OVT gathers. • We discussed the recognition ability of angle stack for minor faults. • The result of shale reservoir in Sichuan Basin is consistent with geology and well. [ABSTRACT FROM AUTHOR]

The grid tomography velocity inversion method prevails as the most efficacious technique for acquiring background velocity requisite for migration. Originating from imaging gathers, this method not only inverses velocity but also subsequently ascertains the anisotropic parameters field. Traditional approaches utilize a parameter field discretized in a rectangular grid for both ray tracing and parameter inversion. However, the rectangular grids may not provide optimal accuracy for structures with pronounced lateral parameter variations. In contrast, triangular grid discretization allows for grid division along steep slopes, offering sparsity and flexibility when juxtaposed with conventional rectangular grid methods. This paper introduces an optimized triangular grid travel time parameter tomography inversion method, formulated on the parameter sensitivity to travel time and employing angle gathers to derive travel time residuals. Analytical modeling and real data processing substantiate that the triangular grid ray tracing method ameliorates the ill-conditioned nature of the tomography equation and enhances the accuracy of the inversion parameter field effectively. • Ray tracing for obtaining sensitive kernel functions in triangular meshes • Improving the continuity of mid deep and steep structural layers • Layer constraints can improve inversion accuracy. • Accurately simulate undulating layers and velocity interfaces on triangular grids. [ABSTRACT FROM AUTHOR]

As the high-density seismic acquisition is progressively becoming an essential mode of seismic exploration, developing high-precision imaging methods for 3D datasets has become an urgent industry requirement. Unfortunately, the two-dimensional least-squares reverse time migration (LSRTM) can hardly deal with the influence of the third dimension because the structure of reflectors is constantly changing in nearly all directions. Furthermore, anisotropy is very common in underground media, which makes the LSRTM based on isotropic assumption fail to locate the reflectors accurately and seriously limits the identification of geological stratification. Considering the above two problems, this paper derives the least-squares reverse time migration in three-dimensional vertical transversely isotropic media (3D-VTI-LSRTM) and develops a workflow which can realize 3D-LSRTM in VTI media based on this theory. Our workflow uses multi-GPU acceleration and heterogeneous CPU/GPU parallelism. Compared with the general parallel CPU workflow or single GPU workflow, it is feasible that the GPU application significantly improves computing efficiency in practical applications. In addition, this paper extends VTI-LSRTM from 2D to 3D, which solves the problem that the 2D algorithm cannot eliminate the lateral direction reflection artifacts. For the self-made 3D-VTI depression model and the 3D-VTI-SEG/EAGE salt model, we use four NVIDIA Tesla k40c graphics cards for testing. The results of the tests are correct and significantly improved compared to the 3D-VTI-RTM method. • Algorithm derivation of 3D-VTI-LSRTM. • Multi-GPU acceleration. • Eliminating artifacts using 3D imaging. [ABSTRACT FROM AUTHOR]

Noise removal is a critical stage in the processing of seismic data. Recent data-driven approaches require pre-assumptions about the distribution of noise for training the model, but in the actual denoising work, the natural noise does not obey the assumed distribution and the ability of the network to deal with this kind of noise is limited. Therefore, this paper proposes an adversarial learning method, FDT, which based on hybrid loss and domain transform. It treats noisy seismic data and clean seismic data as two different domains, and performs adversarial training by cycling between the two domains. Then the network will automatically learn a mapping that converts noisy seismic data into clean seismic data, which can achieve promising denoising result despite the noisy distribution is unknown. Moreover, single pixel-level loss similar to L 1 and L 2 is not adequate to characterize the texture and structure of the seismic data, in this paper, we combined SSIM(Structure Similarity Index Measure) and L 1 together as a reconstruction loss to ensure that seismic data remains the same geological and tectonic information after denoising. Experimental results demonstrate that the method in this paper can effectively remove most types of noise from seismic data and achieve advanced results on both synthetic and real datasets. And it outputs a PSNR(Peak Signal-to-Noise Ratio) value of 27.97 with a standard deviation of 0.2 for large scale noise, maintaining a highly reliable denoising performance. • Denoising in noise of unknown distribution. • Hybrid SSIM and L 1 to preserve geological and tectonic information. • Excellent denoising for both strong and natural unknown noise. [ABSTRACT FROM AUTHOR]

This paper describes the application of a comprehensive surface geophysical investigation of underground karst systems ahead of the tunnel face in the Xiaoheyan section in the main line of the water supply project from Songhua River, located in Jilin, China. To make an accurate investigation, Surface Electrical Resistivity Tomography (S-ERT), Transient Electromagnetic Method (TEM), Geological Drilling (Geo-D) and Three-dimensional Cross-hole Electrical Resistivity Tomography (3D cross-hole ERT) were applied to gain a comprehensive interpretation. To begin with, S-ERT and TEM are adopted to detect and delineate the underground karst zone. Based on the detection results, surface and in-tunnel Geo-D are placed in major areas with more specific and accurate information gained. After that, survey lines of 3D cross-hole ERT are used to conduct detailed exploration towards underground karst system. In the comprehensive investigation, it is the major question to make the best of prior information so as to promote the quality of detection. The paper has put forward strategies to make the full use of effective information in data processing and the main ideas of those strategies include: (1) Take the resistivity distribution of the subsurface stratum gained by S-ERT inversion as the initial model of TEM inversion; (2) Arrange borehole positions with the results of S-ERT and TEM. After that, gain more accurate information about resistivity of subsurface stratum using those boreholes located; (3) Through the comprehensive analysis of the information about S-ERT, TEM and Geo-D, set the initial model of 3D cross-hole resistivity inversion and meanwhile, gain the variation range of stratum resistivity. At last, a 3D cross-hole resistivity inversion based on the incorporated initial model and inequality constraint is conducted. Constrained inversion and joint interpretation are realized by the effective use of prior information in comprehensive investigation, helping to suppress the non-uniqueness problem of inversion so as to raise its reliability. In this way, a 3D detailed model of underground karst system which is 30 m ahead of tunnel face is finally formed. At the end of the paper, there is a geological sketch of the revealed karst caves, which illustrates the effectiveness of the presented strategy. To sum up, in the comprehensive investigation of underground karst caves, the integrated use of prior information can help to yield more accurate and detailed results. [ABSTRACT FROM AUTHOR]

Seismic data are always contaminated with high noise components, which present processing challenges especially for signal preservation and its true amplitude response. This paper deals with an extension of the conventional median filter, which is widely used in random noise attenuation. It is known that the standard median filter works well with laterally aligned coherent events but cannot handle steep events, especially events with conflicting dips. In this paper, an iterative dip-steering median filter is proposed for the attenuation of random noise in the presence of multiple dips. The filter first identifies the dominant dips inside an optimized processing window by a Fourier-radial transform in the frequency-wavenumber domain. The optimum size of the processing window depends on the intensity of random noise that needs to be attenuated and the amount of signal to be preserved. It then applies median filter along the dominant dip and retains the signals. Iterations are adopted to process the residual signals along the remaining dominant dips in a descending sequence, until all signals have been retained. The method is tested by both synthetic and field data gathers and also compared with the commonly used f-k least squares de-noising and f-x deconvolution. [ABSTRACT FROM AUTHOR]

This paper is counted as a numerical investigation into the capability of Poisson's Partial Differential Equation (PDE) at Earth's surface to extract the near-surface mass-density from land-based gravity data. For this purpose, first it focuses on approximating the gradient tensor of Earth's gravitational potential by means of land-based gravity data. Then, based on the concepts of both the gradient tensor and Poisson's PDE at the Earth's surface, certain formulae are proposed for the mass-density determination. Furthermore, this paper shows how the generalized Tikhonov regularization strategy can be used for enhancing the efficiency of the proposed approach. Finally, in a real case study, the formulae are applied to 6350 gravity stations located within a part of the north coast of the Persian Gulf. The case study numerically indicates that the proposed formulae, provided by Poisson's PDE, has the ability to convert land-based gravity data into the terrain mass-density which has been used for depicting areas of salt diapirs in the region of the case study. [ABSTRACT FROM AUTHOR]

Currently, deblending is the main strategy for dealing with the intense interference problem of simultaneous source data. Most deblending methods are based on the property that useful signal is coherent while the interference is incoherent in some domains other than common shot domain. In this paper, two simultaneous source field trials were studied in detail. In the first trial, the simultaneous source survey was not optimal, as the dithering code had strong coherency and the minimum distance between the two vessels was also small. The chosen marine shot scheduling and vessel deployment made it difficult to deblend the simultaneous source data, and result was an unexpected failure. Next, we tested different parameters (the dithering code and the minimum distance between vessels) of the simultaneous source survey using the simulated blended data and got some useful insights. Then, we carried out the second field trial with a carefully designed survey that was much different from the first trial. The deblended results in common receiver gather, common shot gather or the final stacked profile were encouraging. We obtained a complete success in the second field trial, which gave us confidence in the further test (such as a full three dimensional acquisition test or a high-resolution acquisition test with denser spatial sampling). Remembering that failures with simultaneous sourcing seldom reported, in this paper, our contribution is the discussion in detail about both our failed and successful field experiments and the lessons we have learned from them with the hope that the experience gained from this study can be very useful to other researchers in the same field. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) data obtained by using an m-sequence source is typically segmented with an m-sequence cycle, and the random noise is suppressed by stacking the earth impulse responses recovered from each data segment. However, the stack cannot suppress the powerline noise, which is normally several orders of magnitude greater than the random noise. In this paper, the powerline noise reduction with different data lengths were compared by numerical simulation; the results show that there is always an optimal data length, not a single cycle but several cycles that can achieve maximum powerline noise suppression. The concept of an identification system was proposed and the identified earth impulse response is obtained by measuring the system output with the input of the voltage response. The optimal data length was summarized in two cases by analyzing the identification system with different data lengths. Coding frequency optimization was proposed to shorten the optimal data length to increase the stacking times. Finally, the validity of the theory described in this paper was verified by field data processing. Different from the traditional subtraction method and notch filter, the powerline suppression method presented here does not need a noise record or filter design; the powerline noise is suppressed accompanied by the identification processing without any additional workload; the simple and practical method provides a new insight into the powerline noise reduction. With this method, the utilization of field data is improved and the anti-noise performance of the m-sequence is also fully exploited. [ABSTRACT FROM AUTHOR]

In this paper, multi-source (geophysical, geochemical, geological and remote sensing) datasets were used to construct multi-scale (district-, deposit-, and orebody-scale) 3D geological models and extract 3D exploration criteria for subsurface Mo-polymetallic exploration targeting in the Luanchuan district in China. The results indicate that (i) a series of region-/district-scale NW-trending thrusts controlled main Mo-polymetallic forming, and they were formed by regional Indosinian Qinling orogenic events, the secondary NW-trending district-scale folds and NE-trending faults and the intrusive stock structure are produced based on thrust structure in Caledonian-Indosinian orogenic events; they are ore-bearing zones and ore-forming structures; (ii) the NW-trending district-scale and NE-trending deposit-scale normal faults were crossed and controlled by the Jurassic granite stocks in 3D space, they are associated with the magma-skarn Mo polymetallic mineralization (the 3D buffer distance of ore-forming granite stocks is 600 m) and the NW-trending hydrothermal Pb-Zn deposits which are surrounded by the Jurassic granite stocks and constrained by NW-trending or NE-trending faults (the 3D buffer distance of ore-forming fault is 700 m); and (iii) nine Mo polymetallic and four Pb-Zn targets were identified in the subsurface of the Luanchuan district. [ABSTRACT FROM AUTHOR]

In this paper we discuss the design and verification of wide-band, multi-frequency, tuning circuits for large-moment Transmitter (TX) loops. Since these multi-frequency, tuned-TX loops allow for the simultaneous transmission of multiple frequencies at high-current levels, they are ideally suited for frequency-domain geophysical systems that collect data while moving, such as helicopter mounted systems. Furthermore, since multi-frequency tuners use the same TX loop for all frequencies, instead of using separate tuned-TX loops for each frequency, they allow for the use of larger moment TX loops. In this paper we discuss the design and simulation of one- and three-frequency tuned TX loops and then present measurement results for a three-frequency, tuned-TX loop. [ABSTRACT FROM AUTHOR]

This paper develops a method for separation and extraction of pipeline leakage signals. The independent component analysis is applied to separate acoustic signals, which is then coupled with the image similarity distance matching fusion algorithm for the extraction of the signals due to leakage. Acoustic signals generated by real pipeline leakage and common interference noise are collected respectively in order to form a multi-channel matrix with random mixing of leakage signal and uncorrected noise signals. It is demonstrated that the suspected leakage signals extracted after re-sequencing match well with the original leakage signal in terms of coherence and peak cross-correlation. They are further verified based on the cumulative energy distribution and the energy ratio at low and high frequencies. By effective separation of leak signals from the uncorrected background noise signals, the method presented in this paper provides the basis for the improvement of pipeline leak localization. • The proposed method is applied to separate pipe leakage signals. • Tests were conducted to collet signals from four different noise sources. • Experimental results confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Harmonic noise represented by power-line noise is the main interference of Multi-transient electromagnetic (MTEM), and traditional filtering methods inevitably suffer from noise residue and waveform distortion. The key step in MTEM is the extraction of the earth impulse response, which is equivalent to filtering the voltage response signal using an identification system. This paper modulates the spectrum of the identification system by extending the source signal to increase the attenuation at these target frequencies in order to filter out harmonic noise when extracting the earth impulse response, which we named as Extended Spectrum Modulation Method (ESMM). This paper first deduces the mathematical relationship between data length and target frequency. The filtering of power-line harmonics by ESMM is then demonstrated and compared with a conventional notch filter. This paper also proposes a rapid deployment method for ESMM to improve data utilization. Since ESMM filters out noise while extracting the earth impulse response, there is no additional hardware cost or time overhead. Finally, a field experiment demonstrates the superior performance and ultimate convenience of ESMM. • The ESMM filters the periodic noise while extracting the earth impulse response. • The ESMM is achieved by modulating the spectrum of the identification system. • The target frequency can be flexibly adjusted with the extension times. • The ESMM is more practical, lower cost, and better performing than notch filters. [ABSTRACT FROM AUTHOR]

Convolutional Neural Networks (CNN) are widely applied to Ground Penetrating Radar (GPR) inversion because they have strong data-driven capabilities and are suitable for the data structure form of GPR. For CNN, the computation increases with the distance that the convolutional block moves from one region to another when it calculates the relationship between two regions. For GPR data, the target reflection exists in the surrounding traces and full time-window of the target, which leads to high degree of remote relationship. In this paper, we propose GPR-TransUNet, a deep-learning based inversion network which use self-attention mechanism. According to the characteristics of GPR data, regression network and GPR-Loss mechanism were used. Both numerical and model experiments were arranged to test the performance of the network, and the result as well as comparative analysis demonstrate the superiority of GPR-TransUNet. Finally, we applied this method to the field GPR data of Guangxi as an attempt. [Display omitted] • GPR-TransUNet based on Regressive Self-Attention Mechanism and U-net is proposed. • GPR-TransUNet is successfully used to reconstruct the permittivity map of complex subsurface defects. • GPR-TransUNet is verified by synthetic and field data. [ABSTRACT FROM AUTHOR]

Microseismic technology has been widely used in geological hazard monitoring. However, the effective identification and classification of microseismic events in mines have always been a challenge in hazard monitoring. In this paper, a new method combining the empirical mode decomposition (EMD) algorithm and artificial neural network is proposed for the classification and identification of microseismic waveforms. This is the first study to explore such a model in the microseismic monitoring of coal mines. The data for this study were collected from a coal mine in northern China. A total of 2768 microseismic events and 2435 non-microseismic events were manually selected from a large amount of data. Firstly, the microseismic waveform reconstruction was performed using the 4th to 8th Intrinsic Mode Function (IMF) obtained by the EMD algorithm. Secondly, the peak factor, clearance factor, impulse factor, kurtosis, skewness, and waveform factor of each reconstructed microseismic waveform were used as features. Subsequently, the convolutional neural network (CNN) was used to classify microseismic events. Among them, data from 3600 microseismic events were used as the training set, and data from 1603 microseismic events were used as the test set. Finally, the original waveform data were used as input and compared with the classification results processed with the EMD algorithm. The classification methods of the BP neural network and Radial Basis Function (RBF) neural network were used for verification. The results of the processed features showed a significant increase in accuracy. The classification accuracy of CNN, BP neural network, and RBF neural network are 97.37%, 91.99%, and 94.23%, respectively. The results show that the utilization of the feature processing technique and CNN algorithm in this study demonstrates superior efficacy in microseismic event classification, which can be used in practice. • The EMD algorithm and ANN was constructed to classify microseismic waveforms. • Six features of the reconstructed waveform were selected as the classification basis. • The EMD algorithm was used to make the six waveform characteristics more significant. [ABSTRACT FROM AUTHOR]

This paper studies the propagation of oblique incident seismic P waves as they pass through joints containing saturated fluids with different media on both sides. For joints containing saturated fluids, the viscoelastic model is used to study the dynamic deformation characteristics. The complete solution for seismic P waves propagating through joints is derived. The reflection and transmission coefficients that occur at arbitrary angles for different ratios of wave impedance are studied. The effects of the frequency, viscosity coefficient and ratio of wave impedance on the reflection and transmission coefficients are discussed. The results show that the reflection and transmission coefficients vary continuously as the angle increases when the ratio of wave impedance is <1.00. However, when the ratio of wave impedance is >1.00, the reflection coefficients are continuous, but the transmission coefficients are discontinuous. When the viscosity of the joint is not considered, as the frequency of the incident wave increases, the reflection coefficients of the reflected P wave and SV wave increase, the transmission coefficient of the transmitted P wave decreases, and the transmission coefficient of the transmitted SV wave first increases and then decreases. When the viscosity of the joint is considered, the difference between the reflection and transmission coefficients under different viscosity coefficients decreases as the frequency increases. Moreover, with increasing values of the viscosity coefficient, the reflection and transmission coefficients are closer to those values that viscosity is not considered. The results also show that the reflection coefficients are continuous, while the transmission coefficients are discontinuous as the ratio of wave impedance increases. • P wave through joint containing saturated fluid with different media was studied. • The analytical solutions of reflection and transmission waves were derived. • Effect of viscosity coefficient on reflection and transmission was discussed. • Effect of ratio of wave impedance on reflection and transmission was studied. [ABSTRACT FROM AUTHOR]

This paper describes some numerical experiments for stress modeling in the zone around a reservoir in a sedimentary basin, where oil and gas exploration is real or potential. We aim to map mainly low- and high-pressure zones, under the principle that they act as push-and-pull natural pumps for fluid accumulation. The necessary data for practical work is based on seismic data, as a post-migration process with the knowledge of velocities of the P and S waves, and the density information. The computation is designed for simple geometries to represent a reservoir geology, and it is addressed as a boundary value problem (BVP) involving the Beltrami-Michell's partial differential equation with Dirichlet conditions. The method employed was the Green's function expressed by Fourier series for the solution of the BVP, where the boundary conditions are given by the stress components along the boundary of the target volume. The first stress invariant controls the elastic mechanical behavior of the subsoil; therefore, once the distribution of rock pressure is obtained, and the boundary conditions are defined, solving the BVP allows the calculation of the stress components distribution (normal and tangential) within a separate target volume for details. The relationship between rock pressure and stress components is established by the Beltrami-Michell problem, which takes the form of a Poisson's equation. The proposed method was applied in a more complex target zone present in the Marmousi model, which contains reservoirs within regions of interest, expanding to more realistic complex problems. [Display omitted] • The low- and high-pressure zones act as natural pumps for fluid accumulation. • The first stress tensor invariant rules the subsoil elastic mechanical behavior. • The Beltrami-Michell equation relates rock pressure and stress tensor components. • The Beltrami-Michell solution is closely related to stress boundary conditions. • The Poisson's ratio values can cause deviations in the expected solution. [ABSTRACT FROM AUTHOR]

The anisotropic ray tracing equations of elastic waves are derived for calculating the central ray's travel time, trajectory, and parameters P and Q. Based on the anisotropic ray tracing algorithm, we proposed a transversely isotropic elastic dynamically focused beam migration for two dimensional media. Based on the two dimensional Kirchhoff-Helmholtz integral of elastic waves, the elastic imaging weight coefficients are used to reduce the crosstalk noise. Then, based on the previous research, we introduced a sign function to eliminate the effect of polarity reversal in qPqSV wave migration. Through model tests, it can be found that the proposed method can process the multicomponent seismic data and image the complex structures for anisotropic media. The optimized dynamic ray tracing algorithm is superior to the conventional one in computational efficiency. Furthermore, the proposed method eliminates the limitations of the Gaussian beam imaging. This method not only does not affect the accuracy of shallow imaging, but also enhances the energy focusing and the amplitude of deep layers. The model tests have shown the accuracy and effectiveness of our proposed method. • Based on the previous research, an anisotropic ray tracing equation of elastic waves is derived. • A dynamically focused beam migration of elastic waves in TI media is developed in this paper. • A sign function is introduced to solve the polarity reversal problem in converted wave migration. [ABSTRACT FROM AUTHOR]

Pre-stack seismic amplitude versus offset (AVO) inversion estimates reservoir properties by relying on the variation of seismic data amplitude with offset, usually ignoring the role of frequency information in seismic data, which leads to its limited and incomplete use of seismic data. Because the reservoir medium has certain viscoelastic properties, its seismic response changes with the offset, and also has a frequency variation response. The traditional linearized PP wave reflection coefficient of viscoelastic medium is only suitable for small angle incidence, and the inversion based on this equation is difficult to meet the requirements of high-precision parameter estimation for complex media. In this paper, starting from the scattering matrix of a viscoelastic medium, a modified second-order viscoelastic scattering coefficient equation based on perturbation theory is derived, and a nonlinear inversion strategy based on the combination of amplitude and frequency is proposed. The new equation has a wider application range because it considers the viscoelasticity and nonlinear approximation of the medium at the same time, and includes five model parameters to be inverted, namely the P-wave velocity, S-wave velocity, density, quality factor (Q-factor) of P-wave, and Q-factor of S-wave. Accuracy analysis shows that the newly proposed approximation equation is more accurate than the traditional linear approximation equation. In addition, a pre-stack seismic nonlinear frequency-dependent inversion method for viscoelastic media is proposed, which realizes the simultaneous estimation of five model parameters. Synthetic example and field seismic data set are also used to demonstrate the stability and accuracy of the proposed method. • A second-order viscoelastic scattering coefficient equation of P -wave reflectivity is derived based on perturbation theory. • A high-order pre-stack seismic nonlinear frequency-dependent inversion method (FANNI) is proposed. • Through the proposed FANNI inversion method, the high-precision direct extraction of quality factors can be realized. [ABSTRACT FROM AUTHOR]

Attenuation of incoherent noise can effectively improve signal-to-noise ratio (SNR) of seismic data. Recently, unsupervised denoising methods have emerged as solutions for the data collection problem to learn directly from single noisy data. However, the loss of input information based on their blind spot strategy leads to poor denoising performance. In this paper, we propose a complementary mask unsupervised learning framework based on visible blind spot (CMVB) to overcome the information loss. First, a Splitter-Splicer is designed to act on the complementary mask of the input. This approach makes full use of all the data to preserve weak signals. Second, a new blind-spot-based loss function is proposed to integrate blind-spot and non-blind-spot data. The addition of non-blind-spot data enhances the continuity of seismic events. Finally, the attention mechanism is integrated into the encoder-decoder structure, improving the ability of blind spot networks to capture detailed information. Experiments are conducted on three synthetic datasets and two field datasets to compare with two existing state-of-the-art unsupervised denoising methods. The results demonstrate that our method excels in recovering weak reflections. • A new unsupervised learning framework. • Complementary blind-spot sampling alleviates the data loss problem. • Designing visible blind loss functions for application to seismic data denoising. • Excellent denoising performance on background noise and natural unknown noise. [ABSTRACT FROM AUTHOR]

Downward continuation is a useful transformation in the processing and interpretation of potential field data. However, this transformation is known for its inherent instability. In this paper, we proposed a stable iterative Runge-Kutta method for downward continuation that uses an average slope over the interval of continuation. Because of the truncation error, we combine the ideas of Runge-Kutta with the iterative downward continuation methods in a single method to improve the accuracy and the precision of the method. The presented method needs only the computation of the first order vertical derivatives (slope) over the whole interval of continuation using the Tikhonov regularization. To validate the efficiency of the proposed method, various tests were conducted on synthetic magnetic data as well as real aeromagnetic data. The obtained results clearly show the stability of our method for the downward continuation of potential field data. • We present a new method for downward continuation based on an iterative process using the Runge-Kutta method. • Our method is stabilized using the Tikhonov regularization process, and the optimal value of the regularization parameter is selected based on the c-norm criterion. • Our study shows that the developed method has a high correlation rate close to 98% when applied to synthetic data and can be used for a variety of potential field data. • The results suggest that our method efficiently reduces noise. • Our method is a valuable tool for geophysicists working with potential field data. [ABSTRACT FROM AUTHOR]

Accurately determining the parameters of the dynamic constitutive model is significant to analyzing the dynamic response characteristics of the surrounding rock at the proximal and distal ends of a railroad tunnel blasting. Hence, this paper analyzes the propagation and attenuation of blasting vibration waves in the rock by utilizing the vibration velocity monitoring data of the Xinbin Tunnel at the Liaoning section of the Shenbai High-speed Railway. The data are provided by the drilling and blasting method. Additionally, the IA-BP inverse analysis method was established to invert the parameters of the JH-2 constitutive model of the rock by numerically analyzing the simulated blasting vibration waves using the inversion parameters. The results highlight that the inversion value obtained by the IA-BP algorithm is slightly different from the calculated test value but still highly accurate, demonstrating the rationality of the inverse analysis method. Meanwhile, the numerical simulation results supplement the proximal vibration velocity, which is difficult to monitor in the project. This is because the vibration velocity of the tunnel surrounding the rock has a noticeable directional effect. Specifically, the vibration velocity law varies as the blast center distance increases, where the peak vibration velocity direction at the far end of the blast changes from the Y direction (vertical direction) to the Z direction (blast direction). The linear attenuation formula of the vibration velocity in the three principles of the tunnel arch, arch shoulder, and arch foot is obtained by fitting, which is an adequate prediction of the safety of the subsequent construction. • A large number of on-site monitoring for the blast distal vibration velocity. • The formula for the attenuation of blasting distal vibration velocity in different locations and directions is derived. • The difficult problem of determining the parameters of the surrounding rock at the site is solved. • The differentiated analysis of blasting proximal vibration velocity and blasting distal vibration velocity are realised. [ABSTRACT FROM AUTHOR]

Seepage is a common phenomenon in earthfill dams, and one that typically warrants episodic assessment and monitoring by regulatory agencies. Geophysical surveys provide a convenient, cost-effective, and convenient means for assessing seepage, but only if they are applied in effective combinations and if the data are analyzed properly. In the present study, a self-potential survey of streaming potential and a 2D electrical resistivity tomography survey were notably successful in detecting seepage under the embankment of the nearly 90-year-old Standing Rock Dam No. 1 in South Dakota, USA. Self-potential (SP) measurements show a localized negative anomaly of up to 27 mV on the upstream side of the dam, which we interpret to be the inlet or recharge zone for seepage, and a positive anomaly of up to 20 mV on the downstream side, which we interpret to be the outlet or discharge zone. The spatial correlation between our resistivity models, SP data, and topography was excellent. Water-saturated, conductive deposits in the dam's embankment match a negative SP amplitude in the inlet or recharge area. Similarly, water-saturated electrically conductive sediments are characterized by a positive SP amplitude in the discharge area where surface seepage occurs in a topographic low. Six years of water-level measurements in the existing piezometers interpreted relative to the properties and spatial distribution of coarser-grained alluvium (sand and gravel) underneath the dam's embankment fill, suggest that most seepage occurs under the dam. Our approach to assessing seepage in this project should be widely applicable to earthfill dams worldwide, and our modeled results constitute a valuable case study. • This paper is an integrated geophysical and geotechnical investigation of water seepage through earthfill dam. • We used 2D resistivity and Self-Potential methods to discover the seepage zone. • The geotechnical data explained the main reason for seepage under the dam. • The streaming potential created by water flow is a key to detecting the seepage zone. [ABSTRACT FROM AUTHOR]

Waveform stacking is frequently employed in the analysis of microseismic data due to its adaptability, effectiveness, and noise immunity. However, the low signal-to-noise ratio and inaccurate velocity model have a considerable negative impact on the waveform stacking location method's performance. A time-frequency transform-based characteristic function and the addition of a multi-master event method to waveform stacking location are presented as solutions to the aforementioned issues. In this paper, non-smooth statistical features of characteristic function are extracted and enhanced using time-frequency transform. Based on the two-pair double-difference method, multi-master events are introduced and a reference criterion for selecting the master events is proposed. Experiments with simulated and actual microseismic data show that the conversion of time-domain signals into time-frequency signals by wavelet transform can enhance the peak capacity of the signal and reduce the background noise, enhancing the imaging resolution. The introduction of multi-master events not only reduces the sensitivity of the waveform stacking method to velocity error but also improves the clustering effect of the master event method. • Using multi-master event waveform stacking to localize microseismic. • Time-frequency transform-based characteristic functions are proposed • The multi-master event waveform stacking method is more stable and accurate, and less sensitive to velocity models [ABSTRACT FROM AUTHOR]

The Laojunshan ore cluster region is situated at the north Song Chay dome, which is the junction of the Yangtze, the Cathaysia, and the Indo-China Blocks. The north Song Chay dome characterized by the Laojunshan metamorphic core complex is an important ore-forming region for W-Sn-Pb-Zn-In elements related to the Late Cretaceous granitic magmatism. In this paper, the Bi-dimensional empirical mode decomposition (BEMD) is applied to separate gravity components from the original gravity data, combined with the known geological and mineralized information, to explore the relationships between the gravity components and various ore-controlling factors at different depths. Four intrinsic mode functions (IMFs) and a residue are obtained. They may imply the spatial distribution of the geological bodies with featured gravity components at different depths. The results are shown as follows: (1) The low-pass filtering gravity component (BIMF4) implies the deeply buried geological units in the study region. The Cretaceous Laojunshan granitic complex and the Nanwenhe gneissic granite display negative gravity components and weak positive gravity components, respectively. The former is closely related to Sn-Zn-In mineralization, the latter is closely related to W polymetallic deposits. Therefore, the negative gravity components showing the Laojunshan granitic complex are the prospecting targets for deeply buried Sn-Zn-In deposits. The weak positive gravity components displaying the Nanwenhe gneissic granite are the prospecting targets for deeply buried W polymetallic deposits. (2) The band-pass filtering gravity component (BIMF3) implies the geological units at middle depth. The skarn-type Sn-W polymetallic deposits are observed in the transition zones from the positive to the negative gravity components, which coincide with the contact metasomatic zones between the Cretaceous granite and the Cambrian-Devonian carbonate rocks. Some small quartz vein W deposits occur within the Cretaceous Laojunshan granite with negative gravity components, and some layered W deposits occur in the Silurian gneissic granite with a weak positive gravity component. (3) High-pass filtering gravity component (BIMF2) implies geological units at the shallow crust, which shows that most of the deposits (occurrences) are located within the positive gravity component zones. These positive gravity component zones should be ore-finding targets for further prospecting for the undiscovered Sn and W polymetallic deposits. (4) The gravity components separated by BEMD coincide with the spatial distribution of the granites associated with various types of mineralization and alteration zones at different depths, which will give insights for further prospecting for concealed ore bodies in this study region. [Display omitted] • The mineralized characteristics of both the Sn-Zn-In and the W polymetallic deposits are recognized. • The gravity components implying ore-controlling factors at different depths are separated using BEMD. • The ore-finding targets of both the Sn-Zn-In and the W polymetallic deposits are identified using the gravity components. [ABSTRACT FROM AUTHOR]

Heat supply pipelines are a critical component of urban infrastructure, with numerous underground projects relying on this crucial and often concealed system. In cases where blueprints are unavailable, it is crucial to determine the precise location and depth of heat supply pipelines. One of the most straightforward methods for detecting these pipelines is measuring underground temperature. Temperature gradient data is less sensitive to environmental temperature changes for detecting shallow heat sources than temperature data. This paper presents an extension of the correlation imaging method to handle temperature gradient data. This method can accurately determine the horizontal center position and the depth of the heat source. This temperature tomographic approach is reliable and has a high resolution, as evidenced by both synthetic and field examples. • Extended the correlation imaging method to process temperature gradient data. • Determined the optimal duration for measuring geothermal gradient data through field experiments. • Located the heat supply pipeline using temperature gradient data measured from the shallow underground. [ABSTRACT FROM AUTHOR]

The electromagnetic methods based on long-wire sources, whether in the time or frequency domain, are mainly detected in the far-source zone. Because the observation array is far away from the transmitting source, the amplitude and bandwidth of the signal have a large loss, which limits the detection depth and accuracy of these methods. In the near-source zone, the loss of signal amplitude and bandwidth is relatively small, conducive to improving the detection performance. However, the complex excitation field in the near-source zone makes the observation seriously affected by the source effect. This paper mainly researched the influence of the shadow effect (one of the source effects) on the observation of the short-offset transient electromagnetic method (SOTEM), which is a near-source time-domain method. The results show that the shadow effect has relatively limited influence only on the specific observation channels of the time series of observation data. Based on this, the research on eliminating shadow effects under single / multi-source, multi location and multi polarization excitation modes is carried out. The results show that using a single excitation source with multiple polarization directions or using excitation sources with different polarization directions can improve the detection accuracy of underground targets. All of these lays a foundation for further development of the SOTEM method. • In this paper, the influence of the shadow effect on the SOTEM is studied. • Analyzing the feature of shadow effect is helpful to eliminate shadow effect. • The feasibility of multi-position and multi-polarization excitation is analyzed. [ABSTRACT FROM AUTHOR]

Laboratory measurements of elastic properties are presented for carbonate samples from the Saudi Arabian Arab formation. Compressional and shear wave velocities (at 1 MHz) and the quasi-static strains of 37 carbonate rock samples were measured as functions of the saturating fluid and the confining pressure. Furthermore, P- and S-wave velocities of the saturated samples were measured at constant differential pressure of 15 MPa. The lithology, mineralogy, porosity, pore type and pore size distribution of each sample were obtained using a combination of thin section and scanning electron microscopy, helium porosimetry and mercury intrusion porosimetry. The samples showed a high sensitivity to the applied differential pressure especially for the high porosity samples. Due to the lack of closing microcracks and compliant pores in low porosity samples, the travel times show slight changes with the confining pressure whereas the high porosity samples showed a remarkable reduction of the travel time with an increase in confining pressure for both P- and S-waves. We found that the sample physically deformed at pressure above 25 MPa. Evidence of inelastic deformation were observed in a few samples even at a differential pressure of 25 MPa. Both P- and S-wave velocities show a visible deviation with respect to the conventional velocity-porosity inverse relationships, with large variabilities in the velocities at a given porosity. The tight samples only measured a 3% average increase in velocity over the pressure range, whereas the porous samples measured a 20% average increase in velocity over the same pressure range. Despite the nature of porosity, the measured velocities showed a general increase with pressure. Also, all measured samples showed an increase in the bulk modulus of the rock after water saturation with 60% and less than 1% increases. There was no trivial correlation between porosity and the magnitude of the bulk modulus increase. Indeed, the shear modulus of the rock should be insensitive to any changes in water saturation, however, we observed some changes. The presence of anhydrite reduced both P- and S-wave velocities and had a significant influence on the velocities of carbonate rocks at any given porosity. A second paper will build on the results and will consist of predicting and validating suitable rock physics models using the measured carbonate data. The data that support findings of this study are openly available in ERA: Education and Research Archive University of Alberta at https://doi.org/10.7939/R3091B • This paper studies the effect of rock microstructure on the elastic properties. • Ultrasonic velocities and quasi-static strain were measured on carbonates samples. • Measured samples showed an increase in the bulk modulus of the rock with saturation. • The shear modulus should be insensitive to water saturation, but we observed changes. • We noticed velocity variations with mineralogy. [ABSTRACT FROM AUTHOR]

In this paper, numerical simulations are conducted to study elastic wave transport, scattering, and attenuation in a naturally fractured rock associated with length-correlated fracture normal and shear stiffnesses. The model represents the pattern of a real fracture outcrop in an explicit fashion based on the discrete fracture network approach and computes the dynamical interaction between waves and fractures based on the displacement discontinuity method. A broad spectrum of geologically relevant fracture stiffness values are explored to analyse the impact of fracture normal and shear stiffness components on the wavefield evolution. It is observed that when the fracture normal and shear stiffnesses are both high, the wavefield is a propagative mode dominated by a forward ballistic transport. With the reduction of fracture normal and/or shear stiffnesses, the wavefield becomes diffusive characterised by the emergence and dominance of coda waves. If the fracture stiffnesses are very low, waves become trapped entering the so-called localisation regime associated with an absence of effective transport as well as a profound attenuation. Our results show that the scattering attenuation of S waves tends to be greater than that of P waves in the propagation and diffusion regimes, but becomes similar in the localisation regime. The research findings of this paper have important implications for understanding and predicting the seismic wave attenuation behaviour in naturally fractured rocks for various geophysical applications. • Elastic wave transport in a naturally fractured rock is numerically simulated. • Fracture stiffnesses exert a significant impact on wave scattering and attenuation. • S waves are more attenuated than P waves in the propagative and diffusive regimes. • Anderson localisation of elastic waves emerges when fracture stiffnesses are very low. [ABSTRACT FROM AUTHOR]

Gravitational anomalies play a significant role in qualitative and quantitative interpretations of structural settings. Vertical derivative, horizontal derivative and their combinations of gravity anomaly are popularly utilized for edge detection and depth estimations. However, the results are usually deviated from the actual location even for vertical-sided geological sources, especially in the case of deeper ones. The tilt angle (TA) and normalized tilt angle (TDX) as well as their Euler deconvolution have been proved to be more effective than the traditional methods to calculate the horizontal position and depth of sources, yet there are unstable results from the Tilt_Euler and TDX_Euler techniques. This is mainly because the derivatives of the TA and TDX are not calculable while the horizontal derivatives of gravitational anomalies approach to zero. This paper propose an extended tilt angle (ETA) and its Euler deconvolution (ETA_Euler) that guarantees the stability of the results. Results from theoretical models with noise-free and noise-corrupted gravity anomalies indicate that the solutions obtained from the proposed methods approximate to the actual parameters. We compare our proposed method to traditional methods, and the results demonstrate that solutions from ETA_Euler deconvolution are more accurate and concentrated when delineating gravity–anomalous locations and depth. However, the results of the ETA_Euler are sensitive to noise due to the calculation of second-order derivative. Our methods employ upward continuation to an appropriate height to reduce the influence of noise. This paper utilized the above methods to gravity data from the Longmenshan thrust belt (province of Sichuan, China) and adjacent areas. The results indicate that faults within the Longmenshan thrust belt and adjacent areas mainly extend northeast and northwest, correlating well those inferred from other geological and geophysical methods. • An extended tilt angle (ETA) and its Euler deconvolution (ETA_Euler) were proposed. • The applicability of ETA_Euler method was discussed. • The ETA_Euler solutions under peak constraints are more accurate and concentrated. • The application of this method to gravity data in Longmenshan was studied. • The ETA_Euler method has an advantage in detecting shallow geological bodies. [ABSTRACT FROM AUTHOR]

Small-scale mining faces many challenges, such as the proportionally higher costs related to mineral exploration, the time for the results associated with these activities to become available and the difficulties to dispose of waste throughout the mine life. This paper considers three innovative approaches to address small-scale mining issues: application of the Electrical Resistivity and Induced Polarization geophysical method in a barite deposit, preliminary geological modeling and conceptual pit design. These approaches were tested as an alternative to conventional exploration and exploitation methods for small-scale mining of barite deposits. The methods were applied to a barite deposit and the results allowed for a targeted drilling campaign that provided savings of over 58%, with the reduction of nearly 62% in time and 93% in waste generated by the future mining operation. The proposed approach also allowed for the construction of targeted, smaller pits aimed at the best exploitation of the deposits. Hence, the proposed methodology proved to be a feasible alternative for the mine planning cycle of small-scale barite deposits. • The paper offers approach to reduce geological uncertainty in the mineral industry. • A geophysics-oriented approach is proposed for cost-effective drilling campaigns. • Geoelectrical methods were applied on a small-scale deposit of barite. • The approach reached reduction in drilling execution time and costs. [ABSTRACT FROM AUTHOR]

This paper is the first phase of an integrated geophysical investigation of an abandoned gypsum mine in Blackhawk, South Dakota, USA. Recent ground collapses have occurred over these tunnels, the extent of which was heretofore unknown. Summarized herein are survey results from the northern and northeastern parts of the study area. We used Electrical Resistivity Tomography (ERT) as the main method of exploration due to its high resolution, accuracy, and high data coverage. We measured nine resistivity lines using Wenner and Dipole-Dipole arrays. We also applied the Self-Potential (SP) and Frequency Domain Electromagnetic (EM31) methods in the northeastern part of the study area. Our results reveal: (1) many low-resistivity tunnel-shaped anomalies in the eastern zone, which is flooded; and (2) high-resistivity tunnel-shaped anomalies in the western zone, which is dry. The flooded and dry zones are clearly differentiated by the resistivity method. A negative SP anomaly—created by the downward seepage of CaSO 4 -water in the tunnels—is a key to outlining abandoned mine tunnels. • This paper is an integrated geophysical investigation of an abandoned gypsum mine. • We used resistivity and electromagnetic methods to discover an abandoned gypsum mine. • The presence of shallow mine tunnels onsite is the major factor in ground collapse. • The Self-Potential created by downward seepage is a key to detect the tunnels. [ABSTRACT FROM AUTHOR]

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In elastic reverse time migration (RTM), one of the problems that are often encountered is the cross-talk between P- and S-wavefields. A useful processing technique to reduce the cross-talk is separating the P- and S-wavefields by using divergence and curl operators before applying an elastic imaging condition. However, the separated wavefields lose their physical meaning because their phase and amplitude are changed. In this paper, we modify the divergence and curl operators to give the separated wavefields a clear physical meaning: the separated wavefield is the first derivative of the input wavefield with respect to time. Another problem often encountered is polarity reversals in PS and SP images, which can cause destructive interference in the final stacked image and thus destroy the migrated events. In this paper we also develop a procedure for polarity reversal correction based on the polarization vectors of the P- and S-wavefields in the common-shot domain. The correction factor is first calculated at every imaging point during the wavefield reconstruction and is then multiplied by the PS and SP images at each time step when an elastic imaging condition is applied. Numerical examples with synthetic data have shown that the modified wavefield separation method is correct, and the procedure of polarity reversal correction is effective for a complex model. [ABSTRACT FROM AUTHOR]

Laterally constrained inversion (LCI) has been successfully applied to the inversion of dc resistivity, TEM and airborne EM data. However, it hasn't been yet applied to the interpretation of controlled-source audio-frequency magnetotelluric (CSAMT) data. In this paper, we apply the LCI method for CSAMT data inversion by preconditioning the Jacobian matrix. We apply a weighting matrix to Jacobian to balance the sensitivity of model parameters, so that the resolution with respect to different model parameters becomes more uniform. Numerical experiments confirm that this can improve the convergence of the inversion. We first invert a synthetic dataset with and without noise to investigate the effect of LCI applications to CSAMT data, for the noise free data, the results show that the LCI method can recover the true model better compared to the traditional single-station inversion; and for the noisy data, the true model is recovered even with a noise level of 8%, indicating that LCI inversions are to some extent noise insensitive. Then, we re-invert two CSAMT datasets collected respectively in a watershed and a coal mine area in Northern China and compare our results with those from previous inversions. The comparison with the previous inversion in a coal mine shows that LCI method delivers smoother layer interfaces that well correlate to seismic data, while comparison with a global searching algorithm of simulated annealing (SA) in a watershed shows that though both methods deliver very similar good results, however, LCI algorithm presented in this paper runs much faster. The inversion results for the coal mine CSAMT survey show that a conductive water-bearing zone that was not revealed by the previous inversions has been identified by the LCI. This further demonstrates that the method presented in this paper works for CSAMT data inversion. [ABSTRACT FROM AUTHOR]

The coal water-filled zones have become a growing safety hazard, so effective detection techniques and accurate interpretation methods are of great concern. In this paper, we adopt multi-radiation source transient electromagnetic method (TEM) in the data collection, and employ joint imaging method in the data interpretation. A single-radiation source can only be coupled with the geological body from one side, making holographic photography problematic, but multi-radiation source can suppress random noise, improve the signal-to-noise ratio, and reduce the volume effect. Typically, the apparent resistivity method can reflect the electrical distribution characteristics, while the pseudo-seismic imaging method (PSI) can quickly locate the position and shape of the geological structure, so the two imaging methods can be combined. Therefore, firstly using multi-window time-sweep wavefield inverse transformation technology converts the TEM data into the multi-resolution pseudo-wave, then utilizing the joint interpretation method obtains the underground electrical distribution characteristics, the location of the water-filled zones and stratum's continuous undulations. In this paper, through the calculation of the theoretical model, the results verify the effectiveness of the proposed method. Through processing the field data in Gansu, China, the results demonstrate that the joint interpretation method can map the coal water-filled zones and reflect the geological structures. • Detecting the Coal water-filled zones in Gansu, China. • Multi-radiation Source of TEM is adopted in the data acquisition. • Joint imaging method is used in the post processing. • Second-order Born approximation imaging method achieves pseudo-seismic imaging. [ABSTRACT FROM AUTHOR]

Anisotropy exists widely in the earth medium. For anisotropic medium, the traditional isotropic migration will lead to the inaccurate images and unfocused energy. Especially for a deep target exploration, ignoring anisotropy will further affect the subsequent seismic data interpretation. As an improved ray method, Gaussian beam migration overcomes the imaging problems of caustics and shadow zones in Kirchhoff migration, and avoids the time-consuming problems of wave equation migrations. However, the imaging quality of the Gaussian beam migration is controlled by the initial beam width at the surface. In this paper, we extend Nowack (2011)'s algorithm to anisotropic media and present an anisotropic dynamically focused beam migration by modifying the propagator of the Gaussian beams. We use anisotropic kinematic and dynamic ray tracing with optimized coefficients to obtain travel times, trajectories and dynamic information. We then use dynamically focused beams for weakly anisotropic media to calculate the Green's function and the Claerbout imaging condition to obtain images. This strategy enables us to improve the imaging quality in the middle and deep layers without reducing the imaging quality in the shallow layers, which will help to overcome the limitation of the initial beam width in Gaussian beam migration. The results for a VTI fault model and the Shengli complex structure model show the accuracy and validity of the proposed method in this paper. • Implementation of anisotropic ray tracing with optimized coefficients and apply it to migration. • Development of a dynamically focused beam migration algorithm for anisotropic media. • The method studied in this paper shows higher accuracy and validity for complex structure. [ABSTRACT FROM AUTHOR]

Electrical resistivity tomography (ERT) is a geophysical technique that can be used to obtain three-dimensional images of the bulk electrical conductivity of the subsurface. Because the electrical conductivity is strongly related to properties of the subsurface and the flow of water it has become a valuable tool for visualization in many hydrogeological and environmental applications. In recent years, ERT is increasingly being used for quantitative characterization, which requires more detailed prior information than a conventional geophysical inversion for qualitative purposes. In addition, the careful interpretation of measurement and modelling errors is critical if ERT measurements are to be used in a quantitative way. This paper explores the quantitative determination of the electrical conductivity distribution of a cylindrical object placed in a water bath in a laboratory-scale tank. Because of the sharp conductivity contrast between the object and the water, a standard geophysical inversion using a smoothness constraint could not reproduce this target accurately. Better results were obtained by using the ERT measurements to constrain a model describing the geometry of the system. The posterior probability distributions of the parameters describing the geometry were estimated with the Markov chain Monte Carlo method DREAM (ZS) . Using the ERT measurements this way, accurate estimates of the parameters could be obtained. The information quality of the measurements was assessed by a detailed analysis of the errors. Even for the uncomplicated laboratory setup used in this paper, errors in the modelling of the shape and position of the electrodes and the shape of the domain could be identified. The results indicate that the ERT measurements have a high information content which can be accessed by the inclusion of prior information and the consideration of measurement and modelling errors. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) is a non-destructive geophysical technique that is widely used to determine the relative condition of reinforced concrete. This paper presents case studies from Missouri, USA, where a ground-coupled GPR system was used to assess the condition of eleven concrete bridge decks. The main goal of this paper is to develop appropriate acquisition and processing parameters in order to conduct rapid, efficient, and cost-effective assessment of bridge decks. To accomplish this goal, the GPR data sets were collected with slightly different acquisition parameters and processed using different parameters. The quality of the results and the time required for each bridge deck survey are analyzed. Additionally, several experimental data sets were collected across a 12th concrete bridge deck to examine the influence of weather conditions on reflection amplitude values, since amplitude analysis is used in this study. Based on the authors' experience and findings, appropriate GPR acquisition and processing parameters are suggested and described for use of the ground-coupled GPR method for bridge deck assessment. [ABSTRACT FROM AUTHOR]

Leachate recirculation is a key process in municipal waste landfills functioning as bioreactors. To quantify the water content and to assess the leachate injection system, in-situ methods are required to obtain spatially distributed information, usually electrical resistivity tomography (ERT). This geophysical method is based on the inversion process, which presents two major problems in terms of delimiting the infiltration area. First, it is difficult for ERT users to choose an appropriate inversion parameter set. Indeed, it might not be sufficient to interpret only the optimum model (i.e. the model with the chosen regularisation strength) because it is not necessarily the model which best represents the physical process studied. Second, it is difficult to delineate the infiltration front based on resistivity models because of the smoothness of the inversion results. This paper proposes a new methodology called MICS (multiple inversions and clustering strategy), which allows ERT users to improve the delimitation of the infiltration area in leachate injection monitoring. The MICS methodology is based on (i) a multiple inversion step by varying the inversion parameter values to take a wide range of resistivity models into account and (ii) a clustering strategy to improve the delineation of the infiltration front. In this paper, MICS was assessed on two types of data. First, a numerical assessment allows us to optimise and test MICS for different infiltration area sizes, contrasts and shapes. Second, MICS was applied to a field data set gathered during leachate recirculation on a bioreactor. [ABSTRACT FROM AUTHOR]

Most current airborne EM data interpretations assume an isotropic model, which is sometimes inappropriate, especially in regions with distinct dipping anisotropy due to strong layering and stratifications. In this paper, we investigate airborne EM modeling and interpretation for a 3D earth with arbitrarily electrical anisotropy. We implement the staggered finite-difference algorithm to solve the coupled partial differential equations for the scattered electrical fields. Whereas the current density that is connected to the diagonal elements of the anisotropic conductivity tensor is discretized by using the volume weighted average, the current density that is connected to the non-diagonal elements is discretized by using the volume current density average. Further, we apply a divergence correction technique designed specifically for 3D anisotropic models to speed up the modeling process. For numerical experiments, we take both VMD and HMD transmitting dipoles for two typical anisotropic cases: 1) anisotropic anomalous inhomogeneities embedded in an isotropic half-space; and 2) isotropic anomalous inhomogeneities embedded in an anisotropic host rock. Model experiments show that our algorithm has high calculation accuracy, the divergence correction technique used in the modeling can greatly improve the convergence of the solutions, accelerating the calculation speed up to 2 times for the model presented in the paper. The characteristics inside the anisotropic earth, like the location of the anomalous body and the principal axis orientations, can also be clearly identified from AEM area surveys. [ABSTRACT FROM AUTHOR]

The use of Surface Wave Methods for the characterization of the shear wave velocity profile of the soil has become increasingly attractive due to its non-invasive nature and its ability to provide information at a larger scale. Their main drawbacks are the non-uniqueness of the solution and high uncertainty of the results at higher depths. Its application in dense urban areas can be challenging due to the proximity to underground structures, high background noise level and space limitations. This paper describes a case study on the use of surface wave based methods on stiff soil in urban environment within a confined area located in Lisbon city, Portugal, surrounded by buildings and between an underground car park and the subway tunnel. The old building, built in the study area, was demolished for the construction of a new building with five basement floors. During this process, passive and active linear array and passive three-component single-station measurements were made at the surface level, before the works started, and at 2 deeper excavation levels. The results obtained using shallow and in depth measurements were compared, including HVSR and Rayleigh wave ellipticity curves and V s profiles obtained through the conventional MASW method and through the joint inversion of both Rayleigh wave dispersion and ellipticity curves. A deeper V s profile with low uncertainty was obtained through the joint analysis of Rayleigh wave dispersion and ellipticity curves, compatible with V s profile obtained in depth. • Characterization of an urban confined area, located between underground structures, using surface wave methods. • Seismic tests performed at the surface level and at two deeper excavation levels. • Estimation of the V s profile through the joint inversion of Rayleigh wave ellipticity and dispersion curves. • Rayleigh wave dispersion curves dominated by higher modes. • The use of Ryleigh wave ellipticity curve as a tool to avoid mode misidentification and constrain deeper layers. [ABSTRACT FROM AUTHOR]