Applied Geophysics最新文献

Abstract

In the 2017 Jiuzhaigou earthquake sequence, the distribution of aftershocks in the north of the main earthquake was scattered, while the distribution of aftershocks in the south of the main earthquake was linear and concentrated. The objective of this inquiry is to analyze the dynamic causes underlying such divergent patterns, relying on the horizontal strain rosette, areal strain (As), and the coefficient of accommodation (Ca) based on the regional strain rate. The following two conclusions are obtained: (1) approximately one-third of the aftershocks with focal mechanisms in the north of the main shock are thrust-type earthquakes. Because the direction of regional tectonic principal compressional strain is perpendicular to the fault trend north of the main shock, generating thrust-type earthquakes on low dip-angle faults is indeed easy. Simultaneously, the overall thrust-type focal mechanism north of the main shock and the poor consistency between plate tectonic movement and fault movement caused by the seismic sequence lead to substantial scattered aftershocks in the north of the main shock. (2) One of the aftershocks with focal mechanisms in the south of the main shock is a reverse strikeslip type, while the other 30 are strike-slip type earthquakes. Moreover, the angle between the regional tectonic principal compressional strain direction and the fault trend in the south of the main shock is large, which makes it easier for faults in the south of the main shock to produce strike-slip-type earthquakes. Simultaneously, the overall strike-slip focal mechanism in the south of the main shock, the good consistency between fault movements caused by the seismic sequence, and plate tectonic movements lead to more linear and concentrated aftershocks in the south of the main shock. The findings are significant for investigations into the seismogenic properties and activity of the Huya Fault located on the northeastern margin of Bayan Har Block.

The geological environment of underground engineering is complex and full of various uncertainties, and ensuring the reliability of tunnel surrounding rock rating results is crucial for projects. In this study, we first analyze the interrelationships and indicator weights of international mainstream rating methods of tunnel surrounding rock, and summarize the applicability of each method. Next, based on dialectical materialism, we propose that the uncertainties can be divided into multiple levels. Then we analyze the probability distribution law of rating indicators such as rock strength and rock integrity, introduce and use the theory of system reliability analysis, and build functions for the surrounding rocks of different classes. Finally we calculate the reliability probability of surrounding rock rating using Monte Carlo method. The study results indicate that, in view of the uncertainty of surrounding rock rating, the proposed approach fully considers the information of each rating method, and also the data dispersion of local fractured zones, weak interlayers and other tunnel face surrounding rock. Moreover, based on the parameters summary, the proposed approach is proved to be applicable to the current rock mass, and thus makes it possible to evaluate the reliability probability of the tunnel surrounding rock rating. This study helps site personnel to assess surrounding rock rating results more conveniently and accurately, and provides precise guidance for reasonably determining the construction method transition interval and optimizing support parameters.

Abstract

Controlled-source audio magnetotellurics, which is a common technology in geophysical surveys, typically uses the multichannel mode of data acquisition. Often, a capacitive coupling effect occurs among the multiple receiving wires and receiving electrodes and the earth. This effect causes the distortion of the observed apparent resistivity and phase curves. The capacitive coupling of the observation mode is simulated using an equivalent circuit model, and the characteristics of the influence of the length of the receiving wire and grounding resistance of the electrode on capacitive coupling are investigated via the forward simulation of several typical models. The capacitive decoupling of a device for controlled-source audio geomagnetic observation is studied and applied to process the measured data from the Hongtoushan mining area in Liaoning Province, China. This approach effectively weakens the capacitance coupling effect and improves observation quality, and the inversion results match well with known geological information. This study examines the capacitive decoupling technique and offers a scientific foundation for the standardization of the controlled-source audio geomagnetic data gathering technology.

In the generalized continuum mechanics (GCM) theory framework, asymmetric wave equations encompass the characteristic scale parameters of the medium, accounting for microstructure interactions. This study integrates two theoretical branches of the GCM, the modified couple stress theory (M-CST) and the one-parameter second-strain-gradient theory, to form a novel asymmetric wave equation in a unified framework. Numerical modeling of the asymmetric wave equation in a unified framework accurately describes subsurface structures with vital implications for subsequent seismic wave inversion and imaging endeavors. However, employing finite-difference (FD) methods for numerical modeling may introduce numerical dispersion, adversely affecting the accuracy of numerical modeling. The design of an optimal FD operator is crucial for enhancing the accuracy of numerical modeling and emphasizing the scale effects. Therefore, this study devises a hybrid scheme called the dung beetle optimization (DBO) algorithm with a simulated annealing (SA) algorithm, denoted as the SA-based hybrid DBO (SDBO) algorithm. An FD operator optimization method under the SDBO algorithm was developed and applied to the numerical modeling of asymmetric wave equations in a unified framework. Integrating the DBO and SA algorithms mitigates the risk of convergence to a local extreme. The numerical dispersion outcomes underscore that the proposed SDBO algorithm yields FD operators with precision errors constrained to 0.5‱ while encompassing a broader spectrum coverage. This result confirms the efficacy of the SDBO algorithm. Ultimately, the numerical modeling results demonstrate that the new FD method based on the SDBO algorithm effectively suppresses numerical dispersion and enhances the accuracy of elastic wave numerical modeling, thereby accentuating scale effects. This result is significant for extracting wavefield perturbations induced by complex microstructures in the medium and the analysis of scale effects.

Characterizing reservoir porosity is crucial for oil and gas exploration and reservoir evaluation. Due to the increasing demands of oil and gas exploration and development, characterizing reservoir porosity to the required precision using current methods is challenging. Therefore, this study proposes a Pearson correlation–random forest (RF) scheme to select optimal seismic attributes for predicting reservoir porosity and a one-dimensional convolutional neural network–gated recurrent unit (1D CNN–GRU) joint model for reservoir porosity prediction based on well logs and seismic attribute data. First, Pearson correlation–RF is used to select the optimal combination of seismic attribute data suitable for network training. The model learns the nonlinear mapping between porosity logs at well sites and seismic attribute data. It can precisely predict three-dimensional porosity volumes by extending these mappings to nonwell areas. By performing tests near a tight sandstone reservoir, the predicted porosities of the proposed 1D CNN–GRU joint model were a better fit for true porosity values than those of single-network models. Furthermore, the proposed model obtained a laterally contiguous description of the shape and porosity distribution of the tight sandstone reservoir. By integrating advanced machine learning techniques with seismic data analysis, this method provides new approaches and ideas for wide-area porosity predictions for tight sandstone reservoirs using seismic data and opens up possibilities for more detailed and accurate subsurface mapping.

The finite-difference frequency domain (FDFD) method is widely applied for simulating seismic wavefields, and a key to achieving successful FDFD simulation is to construct FDFD coefficients that can effectively suppress numerical dispersion. Among the existing FDFD coefficients for seismic wavefield simulation, adaptive FDFD coefficients that vary with the number of wavelengths per grid can suppress numerical dispersion to the maximum extent. The current methods for calculating adaptive FDFD coefficients involve numerical integration, conjugate gradient (CG) optimization, sequential initial value selection, and smooth regularization, which are difficult to implement and inefficient in calculations. To simplify the calculation of adaptive FDFD coefficients and improve the corresponding computational efficiency, this paper proposes a new method for calculating adaptive FDFD coefficients. First, plane-wave solutions with different discrete propagation angles are substituted in the FDFD scheme, and the corresponding least-squares problem is constructed. As this problem is ill-conditioned and obtaining smooth adaptive FDFD coefficients by the conventional solving method based on normal equations is difficult, this paper proposes solving the least-squares problem by solving the corresponding overdetermined linear system of equations through QR matrix decomposition. Compared with the existing methods for calculating adaptive FDFD coefficients based on numerical integration, CG optimization, and sequential initial value selection, the proposed method allows for a simplified computational process and considerably higher computational efficiency. Numerical wavefield simulation results show that the adaptive-coefficient FDFD method based on QR matrix decomposition can achieve the same accuracy as those based on numerical integration, CG optimization, and sequential initial value selection while requiring less computation time.

High-speed rails with determined length and load run for long periods at almost uniform speeds along fixed routes, constituting a new stable and repeatable artificial seismic source. Studies have demonstrated the wide bands and discrete spectra of high-speed rail seismic signals. Exploring the abundant information contained in massive high-speed rail seismic signals has great application value in the safety monitoring of high-speed rail operation and subgrade. However, given the complex environment around the rail network system, field data contain not only high-speed rail seismic waves but also ambient noise and the noise generated by various human activities. The foundation and key to effectively using high-speed rail seismic signals is to extract them from field data. In this paper, we propose an adaptive variational mode decomposition (VMD)-based separation algorithm for high-speed rail seismic signals. The optimization algorithm is introduced to VMD, and sample entropy and energy difference are used to construct the fitness function for the optimal adjustment of the mode number and penalty factor. Furthermore, time–frequency analysis is performed on the extracted high-speed rail signals and field data using the synchrosqueezed wavelet transform (SSWT). After verifying the processing of simulated signals, the proposed method is applied to field data. Results show that the algorithm can effectively extract high-speed rail seismic signals and eliminate other ambient noises, providing a basis for the imaging and inversion of high-speed rail seismic waves.

The shale oil reservoir within the Yanchang Formations of Ordos Basin harbors substantial oil and gas resources and has recently emerged as the primary focus of unconventional oil and gas exploration and development. Due to its complex pore and throat structure, pronounced heterogeneity, and tight reservoir characteristics, the techniques for conventional oil and gas exploration and production face challenges in comprehensive implementation, also indicating that as a vital parameter for evaluating the physical properties of a reservoir, permeability cannot be effectively estimated. This study selects 21 tight sandstone samples from the Q area within the shale oil formations of Ordos Basin. We systematically conduct the experiments to measure porosity, permeability, ultrasonic wave velocities, and resistivity at varying confining pressures. Results reveal that these measurements exhibit nonlinear changes in response to effective pressure. By using these experimental data and effective medium model, empirical relationships between P-and S-wave velocities, permeability and resistivity and effective pressure are established at logging and seismic scales. Furthermore, relationships between P-wave impedance and permeability, and resistivity and permeability are determined. A comparison between the predicted permeability and logging data demonstrates that the impedance–permeability relationship yields better results in contrast to those of resistivity–permeability relationship. These relationships are further applied to the seismic interpretation of shale oil reservoir in the target layer, enabling the permeability profile predictions based on inverse P-wave impedance. The predicted results are evaluated with actual production data, revealing a better agreement between predicted results and logging data and productivity.

Acoustic emission (AE) source localization is a fundamental element of rock fracture damage imaging. To improve the efficiency and accuracy of AE source localization, this paper proposes a joint method comprising a three-dimensional (3D) AE source localization simplex method and grid search scanning. Using the concept of the geometry of simplexes, tetrahedral iterations were first conducted to narrow down the suspected source region. This is followed by a process of meshing the region and node searching to scan for optimal solutions, until the source location is determined. The resulting algorithm was tested using the artificial excitation source localization and uniaxial compression tests, after which the localization results were compared with the simplex and exhaustive methods. The results revealed that the localization obtained using the proposed method is more stable and can be effectively avoided compared with the simplex localization method. Furthermore, compared with the global scanning method, the proposed method is more efficient, with an average time of 10%–20% of the global scanning localization algorithm. Thus, the proposed algorithm is of great significance for laboratory research focused on locating rupture damages sustained by large-sized rock masses or test blocks.