Dispersion of flexural waves in a borehole with a tensile fracture in an anisotropic stress environment

The effect of tensile fracture in a vertical borehole under anisotropic horizontal stress conditions is numerically investigated in terms of the dispersion of flexural wave generated in dipole sonic logging. Our three-dimensional model comprises a borehole filled with water and a tensile fracture intersecting the borehole in the borehole axial direction. Two shear waves are excited individually to produce particle displacements polarized in two orthogonal radial directions using two dipole sources aligned in the two polarized directions. A vertical array of equispaced dipole sensors is placed at the centre of the borehole along the borehole axis. We assumed that the surrounding formation possesses transversally isotropic anisotropy with the isotropy plane parallel to the borehole axis due to horizontal stress anisotropy. We examined the dispersion of flexural waves travelling along a borehole in our numerical models that include either fast or slow formation with various depths of tensile fractures. Our numerical results show that the deeper the penetration depth of a tensile fracture, the higher the slowness of shear waves polarized perpendicular to the tensile fracture for both slow and fast formation models. Our results indicate that the flexural dispersion behaviour could be used to investigate the depth of penetration of a tensile fracture that can be produced by either drilling or hydraulic fracturing

Inexact Augmented Lagrangian Method-Based Full-waveform Inversion with Randomized Singular Value Decomposition

Full Waveform Inversion (FWI) is a modeling algorithm used for seismic data processing and subsurface structure inversion. Theoretically, the main advantage of FWI is its ability to obtain useful subsurface structure information, such as velocity and density, from complex seismic data through inversion simulation. However, under complex conditions, FWI is difficult to achieve high-resolution imaging results, and most of the cases are due to random noise, initial model, or inversion parameters and so on. Therefore, we consider an effective image processing and dimension reduction tool, randomized singular value decomposition (rSVD) - weighted truncated nuclear norm regularization (WTNNR), for embedding FWI to achieve high-resolution imaging results. This algorithm obtains a truncated matrix approximating the original matrix by reducing the rank of the velocity increment matrix, thus achieving the truncation of noisy data, with the truncation range controlled by WTNNR. Subsequently, we employ an inexact augmented Lagrangian method (iALM) algorithm in the optimization to compress the solution space range, thus relaxing the dependence of FWI and rSVD-WTNNR on the initial model and accelerating the convergence rate of the objective function. We tested on two sets of synthetic data, and the results show that compared with traditional FWI, our method can more effectively suppress the impact of random noise, thus obtaining higher resolution and more accurate subsurface model information. Meanwhile, due to the introduction of iALM, our method also significantly improves the convergence rate. This work indicates that the combination of rSVD-WTNNR and FWI is an effective imaging strategy which can help to solve the challenges faced by traditional FWI.Comment: 55 Pages, 21 Figure

Improved full-waveform inversion for seismic data in the presence of noise based on the K-support norm

Full-waveform inversion (FWI) is known as a seismic data processing method that achieves high-resolution imaging. In the inversion part of the method that brings high resolution in finding a convergence point in the model space, a local numerical optimization algorithm minimizes the objective function based on the norm using the least-square form. Since the norm is sensitive to outliers and noise, the method may often lead to inaccurate imaging results. Thus, a new regulation form with a more practical relaxation form is proposed to solve the overfitting drawback caused by the use of the norm,, namely the K-support norm, which has the form of more reasonable and tighter constraints. In contrast to the least-square method that minimizes the norm, our K-support constraints combine the and the norms. Then, a quadratic penalty method is adopted to linearize the non-linear problem to lighten the computational load. This paper introduces the concept of the K-support norm and integrates this scheme with the quadratic penalty problem to improve the convergence and robustness against background noise. In the numerical example, two synthetic models are tested to clarify the effectiveness of the K-support norm by comparison to the conventional norm with noisy data set. Experimental results indicate that the modified FWI based on the new regularization form effectively improves inversion accuracy and stability, which significantly enhances the lateral resolution of depth inversion even with data with a low signal-to-noise ratio (SNR).Comment: 54 pages, 21 figure

Numerical Simulation of Hydraulic Fracturing in Enhanced Geothermal Systems Considering Thermal Stress Cracks

With the increasing attention to clean and economical energy resources, geothermal energy and enhanced geothermal systems (EGS) have gained much importance in recent years. For the efficient development of deep geothermal reservoirs, it is crucial to understand the mechanical behavior of reservoir rock and its interaction with injected fluid under high-temperature and high confining pressure environments for employing hydraulic stimulation technologies. In the present study, we develop a novel numerical scheme based on the distinct element method (DEM) to simulate the failure behavior of rock by considering the influence of thermal stress cracks and high confining pressure for EGS. The proposed methodology is validated by comparing uniaxial compression tests at various temperatures and biaxial compression tests at different confining pressures with laboratory experimental results. The numerical results indicate a good agreement in terms of failure models and stress-strain curves with those of laboratory experiments. We then apply the developed scheme to the hydraulic fracturing simulations under various temperatures, confining pressures, and injection fluid conditions. Based on our numerical results, the number of hydraulic cracks is proportional to the temperature. At a high-temperature and low confining pressure environment, a complex crack network with large crack width can be observed, whereas the generation of the micro-cracks is suppressed in high confining pressure conditions. In addition, high-viscosity injection fluid tends to induce more hydraulic cracks. Since the crack network in the geothermal reservoir is an essential factor for the efficient production of geothermal energy, the combination of the above factors should be considered in hydraulic fracturing treatment in EGS

Complexation of F⁻ by Li⁺ and Mg²⁺ Ions as Inorganic Anion Acceptors in Lactone-Based Li⁺/F⁻ and Mg²⁺/F⁻ Hybrid Electrolytes for Fluoride Shuttle Batteries

The development of high-quality fluoride-ion transporting electrolytes is a crucial demand for fluoride shuttle batteries (FSBs). However, the uncontrolled chemical and electrochemical activities of fluoride ions narrow the available potential window, hindering the development of high-voltage FSB cells. We present a method for upgrading recently developed lactone-based liquid fluoride electrolytes by complexation of F⁻ with Li⁺ and Mg²⁺ ions. In the resultant Li⁺/F⁻ and Mg²⁺/F⁻ hybrid electrolytes, Li2F+ and MgF+ were the most probable soluble complexes, and the effective fluoride concentrations could reach ∼0.15 M along with excess Li⁺(Mg²⁺) ions. Unique interactions between F⁻ and Li⁺(Mg²⁺) were observed using ¹⁹F nuclear magnetic resonance spectroscopy. Li⁺(Mg²⁺) ions thus served as inorganic anion acceptors with ultimate redox stabilities to expand the negative potential window of the electrolytes to near −3 V vs SHE. The proposed complex formation was also supported by a conductometric titration method. We demonstrated the superior and versatile electrochemical performances of the Li⁺/F⁻ hybrid electrolyte, which enabled reversible charge/discharge reactions of various metal electrodes and composite electrodes in a wide range of redox series. Further, the Li⁺/F⁻ hybrid electrolyte opened valid new reaction paths for aluminum, making it a promising negative electrode in high-voltage FSB cells

Orchestrated ensemble activities constitute a hippocampal memory engram

The brain stores and recalls memories through a set of neurons, termed engram cells. However, it is unclear how these cells are organized to constitute a corresponding memory trace. We established a unique imaging system that combines Ca2+ imaging and engram identification to extract the characteristics of engram activity by visualizing and discriminating between engram and non-engram cells. Here, we show that engram cells detected in the hippocampus display higher repetitive activity than non-engram cells during novel context learning. The total activity pattern of the engram cells during learning is stable across post-learning memory processing. Within a single engram population, we detected several sub-ensembles composed of neurons collectively activated during learning. Some sub-ensembles preferentially reappear during post-learning sleep, and these replayed sub-ensembles are more likely to be reactivated during retrieval. These results indicate that sub-ensembles represent distinct pieces of information, which are then orchestrated to constitute an entire memory

Coupled Simulation of Seismic Wave Propagation and Failure Phenomena by Use of an MPS Method

The failure of brittle materials, for example glasses and rock masses, is commonly observed to be discontinuous. It is, however, difficult to simulate these phenomena by use of conventional numerical simulation methods, for example the finite difference method or the finite element method, because of the presence of computational grids or elements artificially introduced before the simulation. It is, therefore, important for research on such discontinuous failures in science and engineering to analyze the phenomena seamlessly. This study deals with the coupled simulation of elastic wave propagation and failure phenomena by use of a moving particle semi-implicit (MPS) method. It is simple to model the objects of analysis because no grid or lattice structure is necessary. In addition, lack of a grid or lattice structure makes it simple to simulate large deformations and failure phenomena at the same time. We first compare analytical and MPS solutions by use of Lamb’s problem with different offset distances, material properties, and source frequencies. Our results show that analytical and numerical seismograms are in good agreement with each other for 20 particles in a minimum wavelength. Finally, we focus our attention on the Hopkinson effect as an example of failure induced by elastic wave propagation. In the application of the MPS, the algorithm is basically the same as in the previous calculation except for the introduction of a failure criterion. The failure criterion applied in this study is that particle connectivity must be disconnected when the distance between the particles exceeds a failure threshold. We applied the developed algorithm to a suspended specimen that was modeled as a long bar consisting of thousands of particles. A compressional wave in the bar is generated by an abrupt pressure change on one edge. The compressional wave propagates along the interior of the specimen and is visualized clearly. At the other end of the bar, the spalling of the bar is reproduced numerically, and a broken piece of the bar is formed and falls away from the main body of the bar. Consequently, these results show that the MPS method effectively reproduces wave propagation and failure phenomena at the same time