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Petrophysical properties are important parameters for quantitatively evaluating the production of oil and gas reservoirs. Shale reservoirs have complicated pore structures and solid compositions, w...

We present an all-optical scheme for the generation of longitudinal magnetization superoscillation based on the vectorial diffraction theory and the inverse Faraday effect. To achieve this, an azimuthally polarized high-order Laguerre–Gaussian vortex mode is firstly focused by a high numerical aperture (NA) objective and then impinges on an isotropic magneto-optical material. It is found that, by judiciously controlling the intrinsic arguments (radial mode index (p) and truncation parameter (β)) of such a configurable vectorial vortex beam, the longitudinal magnetic domain induced in the focal plane can be switched from a peak sub-wavelength magnetization (> 0.36λ/NA), via the fastest Fourier magnetization component (∼0.36λ/NA), to a super-oscillation magnetization hotspot (< 0.36λ/NA). We further examine the dependence of the transverse size, the side lobe, and the energy conversion efficiency within the focal magnetization domain on both the p and β of the initial vortex modes, confirming that the higher-order structured vortex beams are preferable alternatives to trigger robust longitudinal magnetization superoscillation. In addition, the underlying mechanisms behind the well-defined magnetization phenomena are unveiled. The ultra-small-scale longitudinal magnetization demonstrated here may hold massive potential applications in high-density all-optical magnetic recording/storage, super-resolution magnetic resonance imaging, atom trapping and spintronics.

Images and videos captured in hazy weather are often suffered from visual quality degradation. Recently many dehazing algorithms based on the dark channel prior theory have been proposed. However, these algorithms fail to achieve good performance if there are large sky regions or point light sources in the imaging scene. This paper proposes a novel dehazing algorithm based on sky region correction to overcome the problem of the dark channel prior which is not reasonable for sky regions. In order to estimate the atmospheric light, we choose the luminance value at the top 1% pixels of the sky area in the transmission map and calculate the average value of brightness by these pixels corresponding to the input image, by which the atmospheric light can be estimated more accurately. Experimental results demonstrate that the proposed algorithm has better performance in haze removing and contrast-enhancing than other methods.

Our main scheme in this study was distinguishing between fracture porosity and matrix porosity in coalbed methane reservoirs through a novel approach which is the joint usage of NMR transverse relaxation (T2) measurements and rock physics modeling based on Levenberg-Marquardt (LM) algorithm. For this purpose, NMR T2 relaxation curves of 34 water-saturated coal samples, prepared and processed in the laboratory, were measured and the pore size distribution inside them was investigated. Subsequently, matrix and fracture porosity were separated based on the threshold T2 relaxation time (90–110 ms) which was achieved through our particularly designed fracturing experiments (this is different from the common T2 cutoff). The T2 measurements were performed in the laboratory using our NMR machine. After that, a rock physics scheme based on Levenberg-Marquardt algorithm was applied to independently estimate matrix porosity and fracture porosity from the samples' statistic mechanical properties including compressional wave velocity (Vp), shear wave velocity (Vs), bulk modulus (K), shear modulus (G), Young's modulus (E), and Poisson's ratio (ν) which were all carefully measured in the laboratory. Afterward, both types of the abovementioned porosities were comprehensively characterized and the obtained achievements were listed. Once finished with this step, the 3D structure of the entire reservoir was extracted using the recorded data inside 32 drilled wells, and then the established models were upscaled and the unique and independent contour maps of fracture porosity and matrix pore porosity were drawn over the entire reservoir area. The proposed novel approach provides the kind of information about fractures of the media which is not obtainable with either of NMR or rock physics methods when they are used individually. This study established a novel discussion investigating application of rock physics relationships in order to determine fracture porosity of the coal reservoirs. The approach was used to successfully investigate and characterize pore-only porosity and fracture-only porosity of a coalbed methane reservoir. According to the obtained results, joint usage of rock physics modeling and LM algorithm would be considered as a reliable technique in quick or deeper exploration of unconventional coal reservoirs.

Detecting foot-ground contact is important for inertial motion capture systems because it can provide kinematic constraints to improve human motion capture accuracy. The popular contact detection methods based on zero-velocity detection are only applicable to applications with regular movement patterns, such as pedestrian dead reckoning and gait analysis. As for arbitrary locomotion in motion capture, reliable foot-ground contact detection for universal inertial motion capture is challenging in the presence of motion kinematics and dynamics estimation errors. This paper proposes a novel foot-ground contact detection method for inertial motion capture by the fusion of inaccurate estimations of body kinematics and dynamics with a Naive Bayes probabilistic contact model. Based on physical analysis of contact, a series of kinematic and dynamic motion features calculated from motion capture are considered as observations of contact status classification. The proposed framework consists of offline model training based on a constructed labeled multi-person foot contact dataset, real-time contact detection, and an online model adaptation mechanism for enhancing detection performance of different users and setups. Quantitative evaluations of the proposed contact detection method are presented, and the resulting average foot-ground contact detection accuracy among various locomotion is 95.8%.

The presence of clays in hydrocarbon reservoirs challenges the producible amount of oil and gas significantly. Therefore, this study reports a detailed quantitative characterization of clays' specific properties from two fundamental aspects which include clays' type and amount, and their impact on reservoir's fluid flow. We used Scanning Electron Microscopy (SEM) images and respectively adopted deep learning for typing and quantifying clays, and the Lattice-Boltzmann Method (LBM) for flow simulations with and without the presence of clays. The trained deep learning model of the present study was translated into a MATLAB application that is a convenient tool for clay characterization by the future user. This model was trained using 2160 images of different clay minerals based on transfer learning using AlexNet and resulted in more than 95.4% accuracy while applied on the unforeseen images. Moreover, we established the technique of depth-slicing of 2D SEM images, which provides the possibility of 3D processing of the routine SEM images. The results from this technique proved that clays could reduce reservoir porosity and permeability by more than 30% and 400 mD, respectively. The introduced approach of the present study provides new insights into the detailed impacts of clay minerals on the reservoir's quality.

As the growth of people’s awareness in health and fitness, high-level sports exercise coaching resources become scarce comparing to the fast increasing demands. In traditional sports training, coaches are responsible for scheduling training sessions and giving instructions based on the performance of the trainee. This paper proposes a general knowledge-based coaching system (KBCS) for the purpose of automatic and intelligent sports training. Through systematically modeling the interactive training process between the coach and the trainee as a sequential decision problem, we show that the knowledge-based training controller can be properly designed to help the trainee to make effective progress towards the preset training goal. Partial implementation of KBCS in the table tennis training has been realized to demonstrate and verify the effectiveness of the proposed method.

The application of evaporative cooling technique is getting more and more attention. The aim of the work is to propose a hybrid air-conditioning system. The hybrid system employs an indirect evaporative heat exchanger (IEHX) as a pre-cooling unit that is operated in tandem with conventional air handling unit. The present work has developed a numerical model by considering the pre-cooling effect of the IEHX. The IEHX is able to adopt the room exhaust air as its working air. In addition, the mathematical formulation for the conventional cooling coil has been developed to study the influence of the pre-cooling effect on the chilled water temperature. The calculated results have demonstrated the ability of the evaporative pre-cooling unit to cool and dehumidify the ambient air under humid tropical climates. The chilled water supply temperature can be also raised due the pre-cooling process. Consequently, an improvement on the coefficient of performance for the chiller is achieved. The hybrid system is able to obtain a potential energy saving as a result of the pre-cooling effect and the enhanced efficiency.

Natural gas hydrate is being considered as an alternative energy source for sustainable development and has become a focus of research throughout the world. In this paper, based on CT scanning images of hydrate reservoir rocks, combined with the microscopic distribution of hydrate, a diffusion limited aggregation (DLA) model was used to construct 3D hydrate digital rocks of different distribution types, and the finite-element method was used to simulate their electrical characteristics in order to study the influence of different hydrate distribution types, hydrate saturation and formation of water salinity on electrical properties. The results show that the hydrate digital rocks constructed using the DLA model can be used to characterize the microscopic distribution of different types of hydrates. Under the same conditions, the resistivity of the adhesive hydrate digital rock is higher than the cemented and scattered type digital rocks, and the resistivity of the scattered hydrate digital rock is the smallest among the three types. Besides, the difference in the resistivity of the different types of hydrate digital rocks increases with an increase in hydrate saturation, especially when the saturation is larger than 55%, and the rate of increase of each of the hydrate types is quite different. Similarly, the resistivity of the three hydrate types decreases with an increase in the formation of water salinity. The single distribution hydrate digital rock constructed, combined with the law of microscopic distribution and influence of saturation on the electrical properties, can effectively improve the accuracy of logging identification of hydrate reservoirs and is of great significance for the estimation of hydrate reserves.

Electrical properties are important parameters to quantitatively calculate water saturation in oil and gas reservoirs by well logging interpretation. It is usual that oil layers show high resistivity responses, while water layers show low-resistivity responses. However, there are low-resistivity oil zones that exist in many oilfields around the world, leading to difficulties for reservoir evaluation. In our research, we used digital rock technology to study different internal and external factors to account for low rock resistivity responses in oil layers. We first constructed three-dimensional digital rock models with five components based on micro-computed tomography technology and x-ray diffraction experimental results, and then oil and water distributions in pores were determined by the pore morphology method. When the resistivity of each component was assigned, rock resistivities were calculated by using the finite element method. We collected 20 sandstone samples to prove the effectiveness of our numerical simulation methods. Based on the control variate method, we studied the effects of different factors on the resistivity indexes and rock resistivities. After sensitivity analyses, we found the main factors which caused low rock resistivities in oil layers. For unfractured rocks, influential factors arranged in descending order of importance were porosity, clay content, temperature, water salinity, heavy mineral, clay type and wettability. In addition, we found that the resistivity index could not provide enough information to identify a low-resistivity oil zone by using laboratory rock–electric experimental results. These results can not only expand our understandings of the electrical properties of low-resistivity rocks from oil layers, but also help identify low-resistivity oil zones better.

Although commercial motion-capture systems have been widely used in various applications, the complex setup limits their application scenarios for ordinary consumers. To overcome the drawbacks of wearability, human posture reconstruction based on a few wearable sensors have been actively studied in recent years. In this paper, we propose a deep-learning-based sparse inertial sensor human posture reconstruction method. This method uses bidirectional recurrent neural network (Bi-RNN) to build an a priori model from a large motion dataset to build human motion, thereby the low-dimensional motion measurements are mapped to whole-body posture. To improve the motion reconstruction performance for specific application scenarios, two fundamental problems in the model construction are investigated: training data selection and sparse sensor placement. The problem of deep-learning training data selection is to select independent and identically distributed (IID) data for a certain scenario from the accumulated imbalanced motion dataset with sufficient information. We formulate the data selection into an optimization problem to obtain continuous and IID data segments, which comply with a small reference dataset collected from the target scenario. A two-step heuristic algorithm is proposed to solve the data selection problem. On the other hand, the optimal sensor placement problem is studied to exploit most information from partial observation of human movement. A method for evaluating the motion information amount of any group of wearable inertial sensors based on mutual information is proposed, and a greedy searching method is adopted to obtain the approximate optimal sensor placement of a given sensor number, so that the maximum motion information and minimum redundancy is achieved. Finally, the human posture reconstruction performance is evaluated with different training data and sensor placement selection methods, and experimental results show that the proposed method takes advantages in both posture reconstruction accuracy and model training time. In the 6 sensors configuration, the posture reconstruction errors of our model for walking, running, and playing basketball are 7.25°, 8.84°, and 14.13°, respectively.

Quantitative motion analysis to evaluate the performance of athletes has been actively studied recently. Although various methods based on wearable inertial sensors have been developed for simple and repetitive movements recognition, the understanding of continuous complex movements of in-field sports is still challenging. In this paper, we propose a new motion segmentation and recognition method based on foot swing trajectory state to achieve robust and efficient recognition of motion of interest (MOI) in the lower limbs from continuous and complex movements. In order to segment complex movements in the lower limbs, a series of foot motion states are defined based on foot-ground contact status and foot trajectory during swing. The lower body motion state sequence combining the states of both feet is matched to a prior knowledge of MOI cycle sequences obtained in advance, so as to obtain a motion type candidate set. In this case, the continuous movement is segmented based on the prescreened motion types to realize adaptive time window for feature extraction. Finally, according to the prescreened motion type candidate set, corresponding trained neural network binary classifiers are used to make the classification based on the calculated kinematic features. The proposed method is verified through experiments of football movements consisting of walking, dribbling and stepover. As the result, the motion type recognition accuracy is 95%.

Some inter-salt shale reservoirs have high oil saturations but the soluble salts in their complex lithology pose considerable challenges to their production. Low-field nuclear magnetic resonance (NMR) has been widely used in evaluating physical properties, fluid characteristics, and fluid saturation of conventional oil and gas reservoirs as well as common shale reservoirs. However, the fluid distribution analysis and fluid saturation calculations in inter-salt shale based on NMR results have not been investigated because of existing technical difficulties. Herein, to explore the fluid distribution patterns and movable oil saturation of the inter-salt shale, a specific experimental scheme was designed which is based on the joint adaptation of multi-state saturation, multi-temperature heating, and NMR measurements. This novel approach was applied to the inter-salt shale core samples from the Qianjiang Sag of the Jianghan Basin in China. The experiments were conducted using two sets of inter-salt shale samples, namely cylindrical and powder samples. Additionally, by comparing the one-dimensional (1D) and two-dimensional (2D) NMR results of these samples in oil-saturated and octamethylcyclotetrasiloxane-saturated states, the distributions of free movable oil and water were obtained. Meanwhile, the distributions of the free residual oil, adsorbed oil, and kerogen in the samples were obtained by comparing the 2D NMR T1-T2 maps of the original samples with the sample heated to five different temperatures of 80, 200, 350, 450, and 600 ℃. This research puts forward a 2D NMR identification graph for fluid components in the inter-salt shale reservoirs. Our experimental scheme effectively solves the problems of fluid composition distribution and movable oil saturation calculation in the study area, which is of notable importance for subsequent exploration and production practices.

We report a new paradigm for achieving magnetization spot arrays with controllable three-dimensional (3D) orientations. Toward this aim, we subtly design a tailored incident beam containing three parts and further demonstrate that the designed incident beam is phase-modulated radial polarization. Based on the raytracing model under tight focusing condition and the inverse Faraday effect on the magneto-optic (MO) film, the magnetization field components along the y-axis and z-axis directions are generated through the focus. In particular, we are able to garner orientation-tunable 3D magnetization under different numerical apertures of the focusing objectives by adjusting the ratios between the three parts of incident beam. Apart from a single magnetization spot, magnetization spot arrays capable of dynamically controlling 3D orientation in each spot can also be achieved by multi-zone plate (MZP) phase filter. Such a robust magnetization pattern is attributed to not only the constructive interferences of three orthogonal focal field components, but also the position translation of each magnetization spot resulting from shifting phase of the MZP phase filter. It is expected that the research outcomes can be beneficial to spintronics, magnetic encryption and multi-value MO parallelized storage.

Amorphous zinc-niobium-tin-oxide (a-ZNTO), a new amorphous oxide semiconductor, was proposed for fabricating thin-film transistors (TFTs). a-ZNTO thin films were grown by magnetron sputtering and used as channel layers of TFTs. The effects of niobium content on film properties and device behaviors were investigated in detail. Nb could serve as a carrier suppressor by reducing oxygen vacancies in a-ZNTO films and lower the interfacial trap states in a-ZNTO TFTs. The enhanced performances of a-ZNTO TFTs were achieved at an optimized Nb content of $x=0.2$ for a Nb:Zn:Sn atomic ratio of $x$ :4:7. The reduced channel sizes are very effective to improve TFT performances, with an ON/OFF current ratio of $\sim 10^{8}$ and a field-effect mobility of 13.2 cm2/Vs. The indium-free a-ZNTO TFTs may have the potential for applications in next-generation displays.

A hollow fiber membrane-based semi-direct evaporative cooler (MSDEC) is proposed in this study to conduct a parametrical evaluation. The proposed direct evaporative cooling module is potentially considered as an effective strategy to eliminate the water droplet carryover issue without deteriorating the indoor air quality. A numerical model has been developed to obtain an in-depth understanding of the air treatment process. The model was compared with the experimental data to demonstrate its accuracy for predicting the air conditions in the membrane-based module. The heat and mass transfer performance of the module has been studied by employing the validated model. Simulation results indicated the capability of the proposed membrane-based module to cool and humidify the air. The performance of the membrane-based module has been studied by considering the impact of several key parameters including the inlet air velocity, the inlet air dry-bulb temperature, the inlet air relative humidity, the feed water velocity and the geometric dimensions. The wet-bulb effectiveness of the membrane-based module can be improved to 0.73 for an inlet air velocity of 0.5 m/s. The results were able to provide theoretical suggestions for the further optimized design and application of the hollow fiber membrane-based evaporative cooling module.

In this Letter, we propose a facile approach for achieving a robust focal spot bearing both super-resolution and arbitrary spin orientation. Toward this aim, we meticulously devise a structured incident light consisting of three sorts of beams, which can be produced definitely by the superposition of a radially polarized beam and an azimuthally polarized beam. Based on the vectorial diffraction integral and spin density theory, such newly configurable beams are tightly focused and isotropically interfered in a 4π microscopic configuration to create three polarized field components perpendicular to each other beyond the diffraction limit, thus enabling us to yield a super-resolved focal spot possessing spatial spin axis. By further willfully adjusting the amplitude factors of the reconstituent fields, the photonic spin direction can be freely tunable. The demonstrated results in this Letter may hold great potential for the spin photonics.

In this work we discuss an efficient strategy for reducing the negative impact of non-uniform illumination to panoramic image quality by proposing an adaptive correction algorithm based on the improved Bilateral Gamma function. Firstly the illumination component is extracted by a fast image guided filter. Then an improved bilateral Gamma function fed by the distribution characteristics of illumination is modelled. Finally the non-uniform illumination panoramic image is adjusted adaptively by the devised algorithm, which can increase the intensity value at low illumination regions, and vice versa in the high illumination regions in a panoramic image. Experimental results show that the proposed algorithm can reduce the negative impact caused by the non-uniformity of illumination conditions and enhance the visual quality across different imaging scenarios.

Combining the vector diffraction theory with the inverse Faraday effect, we have theoretically studied magnetization shaping generated by tight focusing of an azimuthally polarized multi-Gaussian beam superimposed with a helical phase. By selecting optimized parameters of a multi-Gaussian beam and topological charge of a spiral phase plate, not only a super-long and sub-wavelength longitudinal magnetization needle with single/dual channels for a single-lens high numerical aperture focusing system, but also an extra-long and three-dimensional super-resolution longitudinal magnetization chain with single/dual channels for a 4π high numerical aperture focusing system is achieved in the focal region. Furthermore, by continuously changing the phase difference between two counter-propagating beams, these super-long longitudinal magnetization chains with three-dimensional super-resolution can dynamically move along the z-axis. It is expected that these results pave the path for fabricating magnetic lattices for spin wave operation, multiple atoms or magnetic particle trapping and transportation, confocal and magnetic resonance microscopy, as well as multilayer ultrahigh density magnetic storage.

In this work, we present a feasible pathway for initially constructing light-induced isotropic super-resolved magnetization along with steerable orientations and trivial side-lobe levels. Toward this end, the counter-propagating azimuthally polarized vortex Hermite–Gauss beams are tailored with angular rotators at the exit pupil planes and then focused by using high numerical aperture objective lenses in a 4π optical microscopic configuration. By wilfully regulating the rotatable azimuth angle and judiciously optimizing the scaling parameter, the spherical super-resolved (λ3/24), orientation-tunable (any direction), and sidelobe-negligible (

We propose a feasible strategy for firstly constructing diffraction-limited light-induced magnetization spot arrays capable of dynamically controlling transverse polarization orientation of each spot. To achieve this goal, we subtly design a tailored incident light comprised of two sorts of beams and sufficiently demonstrate tit's production through phase modulation of a radially polarized beam. Via tightly focusing counter-propagating composite illuminating beams in a 4π optical microscopic configuration, two orthogonally polarized focal fields with π/2 phase difference between them are formed, inducing a three-dimensional (3D) super-resolved transverse magnetization spot in the magnetic-optical (MO) film. Exploiting the ideal of the multi-zone plate (MZP) filter, we further achieve versatile magnetization spot arrays with controllable in-plane polarization direction in each spot. Such well-defined magnetization behavior is attributed to not merely the coherent interference of vectorial optical waves, but also non-overlapping superposition of localized focal fields. Our achievable outcomes pave the way for practical applications in spintronics and multi-value MO parallelized storage.

Amorphous zinc-indium-tin oxide (a-ZITO) thin-film transistors (TFTs) have been prepared using a low-temperature combustion process, with an emphasis on complete miscibility of In and Sn contents. The a-ZITO TFTs were comparatively studied in detail, especially for the working stability. The a-ZITO TFTs all exhibited acceptable and excellent behaviors from Sn-free TFTs to In-free TFTs. The obtained a-ZTO TFTs presented a field-effect mobility of 1.20 cm2 V−1 s−1, an on/off current ratio of 4.89 × 106, and a long-term stability under positive bias stress, which are comparable with those of the a-ZIO TFTs. The In-free a-ZTO TFTs are very potential for electrical applications with a low cost.

X-ray photoelectron spectroscopy (XPS) was utilized to measure the valence band offset (ΔEV) of the TiZnSnO (TZTO)/Si heterojunction. TZTO films were deposited on Si (100) substrates using magnetron sputtering at room temperature. By using the Zn 2p3/2 and Sn 3d5/2 energy levels as references, the value of ΔEV was calculated to be 2.69 ± 0.1 eV. Combining with the experimental optical energy band gap of 3.98 eV for TZTO extracted from the UV-vis transmittance spectrum, the conduction band offset (ΔEC) was deduced to be 0.17 ± 0.1 eV at the interface. Hence, the energy band alignment of the heterojunction was determined accurately, showing a type-I form. This will be beneficial for the design and application of TZTO/Si hybrid devices.