Search Results (217)

Accurate gas prediction is crucial for identifying gas-bearing zones in tight sandstone reservoirs. Traditional seismic techniques, primarily grounded in elastic theory, often overlook inelastic dispersion effects inherent to such formations. To overcome this limitation, we introduce a gas prediction approach utilizing a dispersion attribute derived from frequency-dependent inversion based on an AVO equation parameterized by a gas indicator and related properties. Rock physics modeling, based on multi-scale fracture theory, reveals the frequency-dependent gas indicator is highly responsive to variations in porosity and gas saturation. Seismic AVO simulations exhibit distinguishable signatures corresponding to these variations, supporting the potential to estimate reservoir properties from pre-stack seismic data. Synthetic data tests confirm that the values of the proposed dispersion attribute increase with increasing porosity and gas saturation. Additionally, the calculated dispersion attribute exhibits a strong positive correlation with gas content, validating its effectiveness for gas evaluation. Field application results further demonstrate that the proposed dispersion attribute shows prominent anomalies in sandstone reservoirs with high gas content. Compared to the conventional P-wave dispersion attribute, the proposed dispersion attribute exhibits superior reliability in detecting gas-rich zones. These results demonstrate the utility of the method in predicting gas-bearing regions in tight sandstone reservoirs. Full article

Existing theoretical models of wave-induced flow face challenges in coal applications due to the scarcity of experimental data in the seismic-frequency band. Additionally, traditional viscoelastic combination models exhibit inherent limitations in accurately capturing the attenuation characteristics of rocks. To overcome these constraints, we propose a novel binary classification physical fractal model, which provides a more robust framework for analyzing wave dispersion and attenuation in complex coal. The fractal cell was regarded as an element to re-establish the viscoelastic constitutive equation. In the new constitutive equation, three key fractional orders, $\alpha$, $\beta$, and $\gamma$, emerged. Among them, $\alpha$ mainly affects the attenuation at low frequencies; $\beta$ controls the attenuation in the middle-frequency band; and $\gamma$ dominates the attenuation in the tail-frequency band. After fitting with the measured attenuation data of partially saturated coal samples under variable confining pressures and variable temperature conditions, the results show that this model can effectively represent the attenuation characteristics of elastic wave propagation in coals with different coal structures. It provides a new theoretical model and analysis ideas for the study of elastic wave attenuation in tectonic coals and is of great significance for an in-depth understanding of the physical properties of coals and related geophysical prospecting. Full article

The Dynamic response of two cavities, an elliptical inclusion and a linear crack near anisotropic bi-material interface, was explored analytically by incident out-plane waves in the current work. Firstly, the media is divided into two half spaces (an elastic anisotropic half space with a circular cavity and a linear crack, and an elastic isotropic half space containing an elliptical cavity and an elliptical inclusion). With the help of the image principle, the complex function method is then used to derive the wave fields in each half space. Combined with Green’s functions approach, the relevant Green’s functions developed in the “crack creation” and “conjunction of two half spaces” procedures are derived sequentially. Subsequently, based on the “conjunction” technique, undetermined anti-plane forces are applied to the horizontal surfaces of two half spaces to maintain the continuity criteria of the interface. A series of Fredholm integral equations isobtained and then solved by utilizing the direct discrete technique. Dynamic stress concentration of two elliptical cavities and an elliptical inclusion is mainly considered graphically to discuss the interaction between two half spaces. Finally, a parametric study on the dynamic stress concentration factor (DSCF) was given to show the influence of different parameters on the interaction. Full article

Magneto-electro-elastic materials, a novel class of smart materials, exhibit remarkable energy conversion properties, making them highly suitable for applications in nanotechnology. This study focuses on various aspects of the fractional nonlinear longitudinal wave equation (FNLWE) that models wave propagation in a magneto-electro-elastic circular rod. Using the direct algebraic method, several new soliton solutions were derived under specific parameter constraints. In addition, Galilean transformation was employed to explore the system’s sensitivity and quasi-periodic dynamics. The study incorporates 2D, 3D, and time-series visualizations as effective tools for analyzing quasi-periodic behavior. The results contribute to a deeper understanding of the nonlinear dynamical features of such systems and demonstrate the robustness of the applied methodologies. This research not only extends existing knowledge of nonlinear wave equations but also introduces a substantial number of new solutions with broad applicability. Full article

This paper investigates the linear stability of the liquid film of Oldroyd-B fluid on an oscillating plate. The time-dependent Orr–Sommerfeld boundary-value problem is formulated through the assumption of a normal modal solution and the introduction of the stream function, which is further transformed into the Floquet system. A long-wavelength expansion analysis is performed to derive the analytical solution of the Orr–Sommerfeld equation. The results indicate that long-wave instability occurs only within specific bandwidths related to the Ohnesorge number ($Oh$). Fixing the elasticity parameter ($El$) and increasing the relaxation-to-delay time ratio ($\tilde{\lambda }$) from 2 to 4 or fixing ($\tilde{\lambda }$) and increasing ($El$) from 0.001 to 0.01 decreases the number of unstable bandwidths while enhancing the intensity of unstable modes. Increasing the surface-tension-related parameter (${\zeta }^{\ast }$) from 0 to 100 suppresses the wave growth rate, stabilizing the system. Additionally, increasing ($\tilde{\lambda }$) from 2 to 4 reduces the maximum values of the coupling of viscoelastic, gravitational, and surface-tension forces, as well as the maximum value of the Floquet exponent, further stabilizing the system. These findings provide supplements to the theoretical research on the stability of viscoelastic fluids and also offer a scientific basis for engineering applications in multiple fields. Full article

Compressional (V_P) and shear (V_S) wave velocities of polycrystalline vanadium were measured simultaneously up to 11.5 GPa at room temperature using ultrasonic interferometry in a multi-anvil press. Complex softening behavior in V_S and resulting shear moduli are discovered, possibly revealing a precursor to the reported phase transition within 30–60 GPa. The current data enables a comprehensive assessment of the elastic and mechanical properties of vanadium at high pressures, including bulk and shear moduli, Young’s modulus, Poisson’s ratio, and Pugh’s ratio. Through fitting to the 3rd-order finite strain equations, the elastic moduli and their pressure derivatives were determined to be K_S0 = 151 (2) GPa, G₀ = 46.9 (8) GPa, K’_S0 = 3.47 (5), and G’₀ = 0.62 (1). These experimental results allow us to compare with and benchmark the existing Steinberg–Guinan models for extrapolations to extreme pressure and temperature conditions. Full article

Elastic wavefield separation in anisotropic media is essential for seismic imaging but remains challenging due to complex interactions among multiple wave modes. Traditional methods often rely on solving the Christoffel equation, which is computationally expensive, particularly in heterogeneous models. This study proposes a deep learning-based approach using a cross-attention U-Net architecture to achieve efficient vector decomposition of elastic wavefields. The model employs a dual-branch encoder with cross-attention mechanisms to preserve and exploit inter-component relationships among wavefield components. The network was trained on patches extracted from the BP (British Petroleum) 2007 anisotropic benchmark model, with ground truth labels being generated via low-rank approximation methods. Quantitative evaluations show that the cross-attention U-Net outperforms a baseline U-Net, improving the peak signal-to-noise ratio(PSNR) by 1.25 dB (44.10 dB vs. 42.85 dB) and structural similarity index (SSIM) by 0.014 (0.904 vs. 0.890). The model demonstrates effective generalization to larger domains and different geological settings, validated on both the extended BP model and the Hess vertically transversely isotropic (VTI) model. Overall, this approach provides a computationally efficient alternative to traditional separation methods while maintaining physical consistency in the separated wavefields. Full article

The generalized (2 + 1)-dimensional Date–Jimbo–Kashiwara–Miwa (gDJKM) equation, which can be used to describe some phenomena in fluid mechanics, is investigated based on the multi-soliton solution. Soliton molecules of the gDJKM equation are given by the velocity resonance mechanism. A soliton molecule containing three solitons is portrayed at different times. The invariance of the relative positions of three solitons confirms that they form a soliton molecule. Multi-order lumps are obtained by applying the long-wave limit method in the multi-soliton. By analyzing the dynamics of one-order and two-order lumps, the energy concentration and localization property for lump waves are displayed. In the meanwhile, a multi-soliton can transform into multi-order breathers by the complex conjugation relations of parameters. The interaction among lumps, breathers and soliton molecules can be constructed by combining the above comprehensive analysis. The interaction between a one-order lump and a soliton molecule is an elastic collision, which can be observed through investigating evolutionary processes. The results obtained in this paper are useful for explaining certain nonlinear phenomena in fluid dynamics. Full article

Due to the complex reservoir types and strong heterogeneity of fractured–vuggy reservoirs with aquifers, evaluating such reservoirs’ dynamic reserves and aquifer size is challenging. This paper established a segmented elastic-drive material balance equation based on the material balance principle by combining the functional relationships among the crude oil volume factor, crude oil compressibility, and formation pressure. The PELT algorithm was used to segment the water invasion stages, and nonlinear least squares fitting was employed to determine the rock compressibility, dynamic reserves, and aquifer size of fractured–vuggy reservoirs. This study shows that production in fractured–vuggy reservoirs with aquifers can be divided into three stages: no water invasion, initial water invasion, and full water invasion. Rock compressibility and dynamic reserves can be calculated using production data from the no water invasion stage, while the aquifer size can be determined from data in the water invasion stage. Influenced by connectivity and production regulations, aquifers may not be fully affected by pressure waves, causing the aquifer size to increase gradually until stabilization. Compared with numerical simulation data, the method presented in this paper achieves errors of 0.34%, 0.67%, and 1.19% for rock compressibility, dynamic reserves, and aquifer size, respectively. Full article

The governing Partial Differential Equation (PDE) for wave propagation or the wave equation involves multi-scale and multi-dimensional oscillatory phenomena. Wave PDE challenges traditional computational methods due to high computational costs with rigid assumptions. The advent of scientific machine learning (SciML) presents a novel paradigm by embedding physical laws within neural network architectures, enabling efficient and accurate solutions. This study explores the evolution of SciML approaches, focusing on PINNs, and evaluates their application in modeling acoustic, elastic, and guided wave propagation. PINN is a gray-box predictive model that offers the strong predictive capabilities of data-driven models but also adheres to the physical laws. Through theoretical analysis and problem-driven examples, the findings demonstrate that PINNs address key limitations of traditional methods, including discretization errors and computational inefficiencies, while offering robust predictive capabilities. Despite current challenges, such as optimization difficulties and scalability constraints, PINNs hold transformative potential for advancing wave propagation modeling. This comprehensive study underscores the transformative potential of PINN, followed by recommendations on why and how it could advance elastic, acoustic, and guided wave propagation modeling and sets the stage for future research in the field of Structural Health Monitoring (SHM)/Nondestructive Evaluation (NDE). Full article

This study aims to investigate the behavior of viscoelastic materials exhibiting complex mechanical behavior characterized by both elastic and viscous properties. They are widely used in various engineering applications, such as structural components, transportation systems, energy storage devices, microelectromechanical systems (MEMS), and earthquake research and detection. Accurate modeling of viscoelastic behavior is crucial for predicting its performance under dynamic loading conditions. In this study, we modify the equations governing the thermoelastic resistance to describe the thermal variables of a thermoelastic micro-beam supported by a two-parameter Pasternak viscoelastic foundation by using a fractional Moore–Gibson–Thompson (MGT) model in the context of non-locality. The temperature, bending displacement, and moment were computed and graphically displayed using the Laplace transform method. Different theoretical approaches have been compared in order to explain how the phase delay affects physical phenomena. Numerical results show that the wave fluctuations of variables in thermoelastic micro-beams are slightly smaller for the studied model and that the speed of these plane waves depends on fractional and non-local parameters. Full article

This study models the dynamic response of a damped heterogeneous coating layer over a homogeneous elastic half-space via the shear horizontal equation of motion. The so-called partial nonhomogeneous has been considered in the coating, where only the density of the material features the inhomogeneity parameter. This unusual consideration, motivated by the viscoelasticity setting, gives rise to the realization of Airy’s differential equation in the coating layer that poses Airy’s functions of the first and the second kinds, respectively. Moreover, the resulting dispersion relation has been utilized and analyzed, assessing the impact of the involved parameters. The study realized that an increase in both the damping coefficient and the inhomogeneity parameter accelerates the dispersion of waves in the media. Additionally, once the case of the doubly coated half-space is analyzed, as an extension of the earlier setup, it is noted that the case of a doubly coated half-space is more responsive to the excitations, which is pretty geared by the composition of different layers. In addition, more modes are noted when more coatings are wrapped over the half-space. Full article

Buried pipes are widely used for submarine water transportation, but the complex operating conditions in the seabed pose challenges for the modeling of buried pipes. In order to more accurately capture the dynamic behavior of the buried pipes in the seabed, in this study, considering the pipeline and soil as a systematic structure is proposed, improving the fluid–structure interaction four-equation model to make it applicable for the calculation of buried pipe system modes. After verifying the practicality of the model, considering the external seawater as uniform pressure, the coupling at the joints, and the Poisson coupling of submarine pipelines during transient processes are discussed, revealing that structural vibrations under both forms of coupling will cause greater hydraulic oscillations. The impact of soil elastic modulus on the system’s response is further discussed, revealing that increasing the modulus from 0 to 10¹⁵ Pa raises the wave speed from 498 m/s to 1483 m/s, causing a 40% increase in the amplitude of pressure oscillations. Finally, the vibration modes of the combined structure of pipe wall and soil are discussed, revealing that the vibration modes are mainly dominated by water hammer pressure, with the superposition of pipeline stress waves and soil stress waves. In this study, the dynamic behavior of submarine pipelines is elucidated, providing a robust foundation for regulating and mitigating fatigue failures in such systems. Full article

This work aims to improve the characterization of petrophysical properties by accurately estimating subsurface porosity using seismic and well data. The study includes Bayesian Linearized Inversion to obtain elastic parameters (e.g., compressional e shear wave velocities and densities). This reduces processing uncertainty and provides a reliable substitute for the standard Amplitude versus Offset inversion method. Furthermore, incorporating sparse spike wavelets with Bayesian Linearized Inversion refines the inversion output, facilitating the extraction of petrophysical properties. Combined with log data from seventeen wells, these inverted parameters serve as inputs for two porosity prediction models: the empirical Han’s equation and a more adaptable Support Vector Regression model, the latter demonstrating superior precision in most cases due to its flexible fitting and calibration capabilities. Results from the Norne field in the North Sea confirm the approach’s viability, with the Support Vector Regression model achieving a significant Pearson correlation coefficient of 90% in porosity prediction, underscoring the potential of machine learning techniques in improving subsurface exploration results. Full article

In this paper, we demonstrate that torsional surface elastic waves can propagate along the curved surface of a metamaterial elastic rod (cylinder) embedded in a conventional elastic medium. The crucial parameter of the metamaterial rod is its elastic compliance $s_{44}^{\left(1\right)}\left(\omega \right),$ which varies as a function of frequency $\omega$ analogously to the dielectric function $\epsilon \left(\omega \right)$ in Drude’s model of metals. As a consequence, the elastic compliance $s_{44}^{\left(1\right)}\left(\omega \right)$ can take negative values $s_{44}^{\left(1\right)}\left(\omega \right)<0$ as a function of frequency $\omega$. Negative elastic compliance ($s_{44}^{\left(1\right)}\left(\omega \right)<0$) enables the emergence of new surface states, i.e., new types of surface elastic waves. In fact, the proposed torsional elastic surface waves can be considered as an elastic analog of Surface Plasmon Polariton (SPP) electromagnetic (optical) waves propagating along a metallic rod (cylinder) embedded in a dielectric medium. Consequently, we developed the corresponding analytical equations, for the dispersion relation and group velocity of the new torsional elastic surface wave. The newly discovered torsional elastic surface waves exhibit virtually all extraordinary properties of their electromagnetic SPP counterparts, such as strong subwavelength concentration of the wave energy in the vicinity of the cylindrical surface $(r=a$) of the guiding rod, very low phase and group velocities, etc. Therefore, the new torsional elastic surface waves can be used in: (a) near-field subwavelength acoustic imaging (super-resolution), (b) acoustic wave trapping (zero group and phase velocity), etc. Importantly, the newly discovered torsional elastic surface waves can form a basis for the development of a new generation of ultrasonic sensors (e.g., viscosity sensors), biosensors, and chemosensors with a very high mass sensitivity. Full article