A seismic prediction method of reservoir brittleness based on mineral composition and pore structure

The Lucaogou Formation, a typical fine-grained mixed formation in the Jimusaer Sag of the Junggar Basin, exhibits considerable potential for hydrocarbon exploration. Accurate brittle prediction is a crucial factor in determining hydraulic fracturing effectiveness. However, the area features complex lithological characteristics, including carbonate rocks, clastic rocks, volcanic rocks, and gypsum interbeds, along with thin layering and sporadic sweet spots. Traditional prediction methods offer limited resolution and there is an urgent need for a seismic brittle prediction method tailored to this complex geological environment. This paper presents a multi-mineral composition equivalent model for complex lithologies that enables the accurate calculation of Vp and Vs These ratios serve as the foundation for pre-stack elastic parameter predictions, which include Poisson’s ratio and Young’s modulus. By comparing the predicted parameters with well-logging measurements, the prediction accuracy is improved to 82%, with particularly high conformity in intervals characterized by high organic matter and clay content. Additionally, a three-dimensional brittle modeling approach reveals that the brittleness of the reservoir exceeds that of the surrounding rock, showing a gradual improvement in brittleness with increasing burial depth from southeast to northwest. The central area exhibits relatively good brittleness, with a stable, blocky distribution pattern

Evolution of Near-Well Damage Caused by Fluid Injection through Perforations in Wellbores in Low-Permeability Reservoirs: A Case Study in a Shale Oil Reservoir

AbstractDuring the development of shale oil resources, fluid injection is usually involved in the process of hydraulic fracturing. Fluid injection through perforations causes near-well damage, which is closely related to the subsequent initiation and propagation of hydraulic fractures. This study is focused on the characterization of the temporal and spatial evolving patterns for near-well damage induced by fluid injection through perforations in the early stage of hydraulic fracturing. A coupled hydromechanical model is introduced in a case study in a shale oil reservoir in northwestern China. The model considers porous media flow during fluid injection. It also considers elasticity in the rock skeleton before the damage. Once the damage is initiated, a damage factor is employed to quantify the magnitude of injection-induced damage. Results show that damage evolution is highly sensitive to perforation number and injection rate in each individual perforation. Damage propagation is more favorable in the direction of the initial maximum horizontal principal stress. The propagation of damage is drastic at the beginning of fluid injection, while the damage front travels relatively slow afterward. This study provides insights into the near-well damage evolution before main fractures are initiated and can be used as a reference for the optimization of perforation parameters in the hydraulic fracturing design in this shale oil field

Crosstalk-free achromatic full Stokes imaging polarimetry metasurface enabled by polarization-dependent phase optimization

Imaging polarimetry is one of the most widely used analytical technologies for object detection and analysis. To date, most metasurface-based polarimetry techniques are severely limited by narrow operating bandwidths and inevitable crosstalk, leading to detrimental effects on imaging quality and measurement accuracy. Here, we propose a crosstalk-free broadband achromatic full Stokes imaging polarimeter consisting of polarization-sensitive dielectric metalenses, implemented by the principle of polarization-dependent phase optimization. Compared with the single-polarization optimization method, the average crosstalk has been reduced over three times under incident light with arbitrary polarization ranging from 9 μm to 12 μm, which guarantees the measurement of the polarization state more precisely. The experimental results indicate that the designed polarization-sensitive metalenses can effectively eliminate the chromatic aberration with polarization selectivity and negligible crosstalk. The measured average relative errors are 7.08%, 8.62%, 7.15%, and 7.59% at 9.3, 9.6, 10.3, and 10.6 μm, respectively. Simultaneously, the broadband full polarization imaging capability of the device is also verified. This work is expected to have potential applications in wavefront detection, remote sensing, light-field imaging, and so forth

DiDang Tang Inhibits Endoplasmic Reticulum Stress-Mediated Apoptosis Induced by Oxygen Glucose Deprivation and Intracerebral Hemorrhage Through Blockade of the GRP78-IRE1/PERK Pathways

DiDang Tang (DDT), a Chinese traditional medicine formula, contains 4 Chinese traditional medicine substances, has been widely used to treat intracerebral hemorrhage (ICH) patients. However, the molecular mechanisms of DDT for protecting neurons from oxygen and glucose deprivation (OGD)-induced endoplasmic reticulum (ER) stress and apoptosis after ICH still remains elusive. In this study, high-performance liquid chromatography fingerprint analysis was performed to learn the features of the chemical compositions of DDT. OGD-induced ER stress, Ca2+ overload, and mitochondrial apoptosis were investigated in nerve growth factor -induced PC12, primary neuronal cells, and ICH rats to evaluate the protective effect of DDT. We found that DDT treatment protected neurons against OGD-induced damage and apoptosis by increasing cell viability and reducing the release of lactate dehydrogenase. DDT decreased OGD-induced Ca2+ overload and ER stress through the blockade of the glucose-regulated protein 78 (GRP78)- inositol-requiring protein 1α (IRE1)/ protein kinase RNA-like ER kinase (PERK) pathways and also inhibited apoptosis by decreasing mitochondrial damage. Moreover, we observed similar findings when we studied DDT for inhibition of ER stress in a rat model of ICH. In addition, our experiments further confirmed the neuroprotective potential of DDT against tunicamycin (TM)-induced neural damage. Our in vitro and in vivo results indicated that the neuroprotective effect of DDT against ER stress damage and apoptosis occurred mainly by blocking the GPR78-IRE1/PERK pathways. Taken together, it provides reliable experimental evidence and explains the molecular mechanism of DDT for the treatment of patients with ICH

Susceptibilities of Yersinia pestis to Twelve Antimicrobial Agents in China

Streptomycin is the preferred choice for therapy of plague in China and other countries. However, Yersinia pestis exhibiting plasmid-mediated antimicrobial agent–resistant traits had been reported in Madagascar. In this study, we evaluated the susceptibility of traditional or newer antimicrobial agents used for treatment and/or prophylaxis of plague. Following Clinical and Laboratory Standards Institute (CLSI) recommendations, the susceptibility of 12 antimicrobial agents was evaluated by the agar microdilution method in 1,012 strains of Y. pestis isolated from 1943 to 2017 in 12 natural plague foci in China. One clinical Y. pestis isolate (S19960127) was found to be highly resistant to streptomycin, while the strain was still sensitive to other 11 antibiotics, that is, ciprofloxacin, ofloxacin, kanamycin, chloramphenicol, ampicillin, ceftriaxone, cefuroxime, trimethoprim-sulfamethoxazole, tetracycline, spectinomycin and moxifloxacin. The remaining 1,011 Y. pestis strains in this study demonstrated susceptibility to the above-mentioned 12 antimicrobial agents. Antimicrobial sensitivity surveillance of Y. pestis isolates, including dynamic monitoring of streptomycin resistance during various clinical plague treatments, should be carried out routinely

Cell tracking using deep neural networks with multi-task learning

Cell tracking plays crucial role in biomedical and computer vision areas. As cells generally have frequent deformation activities and small sizes in microscope image, tracking the non-rigid and non-significant cells is quite difficult in practice. Traditional visual tracking methods have good performances on tracking rigid and significant visual objects, however, they are not suitable for cell tracking problem. In this paper, a novel cell tracking method is proposed by using Convolutional Neural Networks (CNNs) as well as multi-task learning (MTL) techniques. The CNNs learn robust cell features and MTL improves the generalization performance of the tracking. The proposed cell tracking method consists of a particle filter motion model, a multi-task learning observation model, and an optimized model update strategy. In the training procedure, the cell tracking is divided into an online tracking task and an accompanying classification task using the MTL technique. The observation model is trained by building a CNN to learn robust cell features. The tracking procedure is started by assigning the cell position in the first frame of a microscope image sequence. Then, the particle filter model is applied to produce a set of candidate bounding boxes in the subsequent frames. The trained observation model provides the confidence probabilities corresponding to all of the candidates and selects the candidate with the highest probability as the final prediction. Finally, an optimized model update strategy is proposed to enable the multi-task observation model for the variation of the tracked cell over the entire tracking procedure. The performance and robustness of the proposed method are analyzed by comparing with other commonly-used methods. Experimental results demonstrate that the proposed method has good performance to the cell tracking problem

Application of homotopy perturbation method to the Bratu-type equations

A new algorithm is presented for solving the Bratu-type equations. The numerical scheme based on the homotopy perturbation method is deduced. Two boundary value problems and an initial value problem are given to illustrate effectiveness and convenience of the proposed scheme. Our results agree very well with the numerical solutions showing that the homotopy perturbation method is a promising method

Identification of Efficient Experimental Design(s) by Comparing Different Commonly Used Designs for Large Data Sets

Following basic principles of experimental design and using appropriate filed design usually play a significant role in successful plant breeding program. Breeders usually seek suitable field designs and use them for their experiments to minimize the experimental error. Finding out the most appropriate design for the experiment may greatly improve the data analysis and help breeders to take right decision. For the current study, 64 corn hybrids (genotypes) were evaluated in six counties in North Carolina. The main objective of our study is to analyze and compare results using different models or experimental designs (CR, RCBD, Sub-block, and Rectangular) and finally determine which design(s) is the most suitable for each county. Linear mixed model (LMM) with jackknife resampling technique was used for data analysis. Among all the tested designs, we found that Rectangular design is more suitable for handling large data sets and CR design was least effective. Rectangular design was well over 2 times and close to 2 times better than CR and RCB design respectively in terms of Relative Efficiency (RE) for most of the counties

Numerical Investigation of Heat Transfer Characteristics of scCO₂ Flowing in a Vertically-Upward Tube with High Mass Flux

In this work, the heat transfer characteristics of supercritical pressure CO2 in vertical heating tube with 10 mm inner diameter under high mass flux were investigated by using an SST k-ω turbulent model. The influences of inlet temperature, heat flux, mass flux, buoyancy and flow acceleration on the heat transfer of supercritical pressure CO2 were discussed. Our results show that the buoyancy and flow acceleration effect based on single phase fluid assumption fail to explain the current simulation results. Here, supercritical pseudo-boiling theory is introduced to deal with heat transfer of scCO2. scCO2 is treated to have a heterogeneous structure consisting of vapor-like fluid and liquid-like fluid. A physical model of scCO2 heat transfer in vertical heating tube was established containing a gas-like layer near the wall and a liquid-like fluid layer. Detailed distribution of thermophysical properties and turbulence in radial direction show that scCO2 heat transfer is greatly affected by the thickness of gas-like film, thermal properties of gas-like film and turbulent kinetic energy in the near-wall region. Buoyancy parameters Bu −5, Bu* −7 and flow acceleration parameter Kv −6 in this paper, which indicate that buoyancy effect and flow acceleration effect has no influence on heat transfer of scCO2 under high mass fluxes. This work successfully explains the heat transfer mechanism of supercritical fluid under high mass flux