Hydraulic Fracturing Mechanism in Reservoirs with a Linear Inclusion Fissure

Hydraulic fracturing technology is widely used in most oil-water wells to improve production. However, the mechanism of fracturing in a reservoir with inclusion fissures is still unclear. In this study, a theoretical model was developed to determine the stress distribution during hydraulic fracturing. The line inclusion fissure was regarded as a thin bar and the stress around the artificial fracture, which is affected by a single line inclusion, was determined using the Eshelby equivalent inclusion theory. Stress intensity factors at the tip of both the artificial fracture and the inclusion were achieved, and initiation of the fracture was predicted. Furthermore, to validate the theoretical model, re-fracturing experiments were performed on a large-scale tri-axial system. The results showed that the defects reduce the intensity of the rock, which introduces the possibility that more complex fractures emerge in the reservoir. The results also showed that the fracture direction is governed by far-field stress. The obtained conclusions are helpful to better understand the mechanism of hydraulic fracturing in reservoirs

Analytic solution for size-dependent behaviors of micro-beam under forced vibration

This paper focuses on the size-dependently mechanical behaviors of a micro-beam under forced vibration. Governing equations of a micro-beam under forced vibration are established by using the modified couple stress theory, Bernoulli-Euler beam theory and D’Alembert’s principle together. A simply supported micro-beam under forced vibration is solved according to the established governing equations and the method of separation of variables. The dimensionless deflection, amplitude mode and period mode are defined to investigate the size-dependently mechanical behaviors of a micro-beam under forced vibration. Results show that the performance of a micro-beams under forced vibration is distinctly size-dependent when the ratio of micro-beam height to material length-scale parameter is small enough. Both frequency ratio and loading location are the important factors that determine the size-dependent performance of a micro-beams under forced vibration

Research on the Damage of Porosityand Permeabilitydue to Perforation on Sandstone in the Compaction Zone

A perforating hole is a channel through which the oil and gas in a reservoir pass into the production well bore. During the process of perforating due to explosion, the surrounding sandstone will be damaged to a certain extent, which will increase the well bore skin and lead to the decrease of production consequently. In this work a mechanical model of perforating damage is developed to describe the influences of perforating due to explosion on the porosity and permeability of the surrounding sandstone near the compaction zone. Based on this developed model, the important data related to the damage of sandstone, such as matrix effective stress, plastic deformation, volumetric strain, and so on, can be numerically simulated. Especially the behaviors of plasticity kinematic hardening at high strain rate due to impact loads, which are the important characteristics in the sandstone, is taken into account in this developed model. Both numerical and testing results show that the damage due to perforation in the sandstone can be accurately predicted by the developed model together with the porosity and permeability evolving model of perforation in a compaction zone. As a practical application, a methodology for the analysis of damage of porosity and permeability around a perforation tunnel is supposed based on the developed model and the core flow efficiency test of interparticle pore spaced sandstone target in China Shengli Oilfield and the computed tomography test

De novo mutations in SMCHD1 cause Bosma arhinia microphthalmia syndrome and abrogate nasal development

Bosma arhinia microphthalmia syndrome (BAMS) is an extremely rare and striking condition characterized by complete absence of the nose with or without ocular defects. We report here that missense mutations in the epigenetic regulator SMCHD1 mapping to the extended ATPase domain of the encoded protein cause BAMS in all 14 cases studied. All mutations were de novo where parental DNA was available. Biochemical tests and in vivo assays in Xenopus laevis embryos suggest that these mutations may behave as gain-of-function alleles. This finding is in contrast to the loss-of-function mutations in SMCHD1 that have been associated with facioscapulohumeral muscular dystrophy (FSHD) type 2. Our results establish SMCHD1 as a key player in nasal development and provide biochemical insight into its enzymatic function that may be exploited for development of therapeutics for FSHD

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models

Diffusion Probabilistic Models (DPMs) have achieved considerable success in generation tasks. As sampling from DPMs is equivalent to solving diffusion SDE or ODE which is time-consuming, numerous fast sampling methods built upon improved differential equation solvers are proposed. The majority of such techniques consider solving the diffusion ODE due to its superior efficiency. However, stochastic sampling could offer additional advantages in generating diverse and high-quality data. In this work, we engage in a comprehensive analysis of stochastic sampling from two aspects: variance-controlled diffusion SDE and linear multi-step SDE solver. Based on our analysis, we propose SA-Solver, which is an improved efficient stochastic Adams method for solving diffusion SDE to generate data with high quality. Our experiments show that SA-Solver achieves: 1) improved or comparable performance compared with the existing state-of-the-art sampling methods for few-step sampling; 2) SOTA FID scores on substantial benchmark datasets under a suitable number of function evaluations (NFEs)

Understanding the unique mechanism of ferroptosis: a promising therapeutic target

Ferroptosis is an iron-dependent form of regulated cell death and is characterized by high concentrations of intracellular lipid peroxide and a redox imbalance in the cells. Ferroptosis shows distinct morphological and biological features compared with other prominent mechanisms of programmed cell death. The distinct characteristics of ferroptosis include the dysfunction of the lipid peroxide repair enzyme glutathione peroxidase 4, the presence of ferrous iron overload, and the lipid peroxidation of polyunsaturated fatty acids. Several other metabolic pathways (including iron, lipid, and amino acid metabolism) and ferritinophagy, as well as transcription factors, can modulate ferroptosis. However, to date, the molecular mechanism of ferroptosis has not been elucidated. This review outlines the discovery, characterization, regulatory mechanisms, and crosstalk of ferroptosis. Further, we have noted the controversial elements in the ferroptosis-related mechanisms. Our inferences may provide a partial reference for developing strategies to regulate ferroptosis

Accelerating Diffusion Sampling with Optimized Time Steps

Diffusion probabilistic models (DPMs) have shown remarkable performance in high-resolution image synthesis, but their sampling efficiency is still to be desired due to the typically large number of sampling steps. Recent advancements in high-order numerical ODE solvers for DPMs have enabled the generation of high-quality images with much fewer sampling steps. While this is a significant development, most sampling methods still employ uniform time steps, which is not optimal when using a small number of steps. To address this issue, we propose a general framework for designing an optimization problem that seeks more appropriate time steps for a specific numerical ODE solver for DPMs. This optimization problem aims to minimize the distance between the ground-truth solution to the ODE and an approximate solution corresponding to the numerical solver. It can be efficiently solved using the constrained trust region method, taking less than $15$ seconds. Our extensive experiments on both unconditional and conditional sampling using pixel- and latent-space DPMs demonstrate that, when combined with the state-of-the-art sampling method UniPC, our optimized time steps significantly improve image generation performance in terms of FID scores for datasets such as CIFAR-10 and ImageNet, compared to using uniform time steps.CVPR 202

A Nonlinear Wind Turbine Wake Expansion Model Considering Atmospheric Stability and Ground Effects

This study investigates the influence of atmospheric stability and ground effects on wind turbine wake recovery, challenging the conventional linear relationship between turbulence intensity and wake expansion coefficient. Through comprehensive field measurements and numerical simulations, we demonstrate that the linear wake expansion assumption is invalid at far-wake locations under high turbulence conditions, primarily due to ground effects. We propose a novel nonlinear wake expansion model that incorporates both atmospheric stability and ground effects by introducing a logarithmic relationship between the wake expansion coefficient and turbulence intensity. Validation results reveal the superior prediction accuracy of the proposed model compared to typical engineering wake models, with root mean square errors of wake wind speed predictions ranging from 0.04 to 0.063. The proposed model offers significant potential for optimizing wind farm layouts and enhancing overall wind energy production efficiency