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Abstract Pressure dynamics can reflect the basic characteristics of fluid flow through underground porous formation. In this research, the oil–gas two-phase flow model for a double-porosity media formation with permeability-stress sensitivity was first established for three kinds of outer boundaries. The unified governing equation was deduced by utilizing the H function. The nonlinear mathematical model in consideration of permeability-stress sensitivity was linearized by implementing the canonical perturbation transformation and then solved by using the Laplace transformation. After that, a sequence of typical log–log curves of pressure dynamics influenced by various model parameters were plotted and analyzed. These curves reflect the typical characteristic of a V shape caused by the inter-porosity fluid flow from matrix toward natural fractures. Oil saturation and permeability-stress sensitivity coefficient have much influence on the pressure dynamics. Ultimately, the established model of oil–gas two-phase flow was validated through a well-test fitting interpretation for a real condensate gas well in a sandstone formation. This research can offer insights into the pressure dynamics dominated by the oil–gas two-phase flow in naturally fractured formations and the permeability-stress sensitivity effect.

The cretaceous gas reservoir in Kelasu Gas Field of the Tarim Basin is a rare ultra-deep and ultra-high pressure fractured tight sandstone gas reservoir where multi-scale discrete fractures of matrix, fracture and fault are developed, so its development cannot be conducted just based on static and dynamic reservoir description. In order to solve this problem, this paper establishes a numerical well test model of vertical wells based on matrix, fractures and faults (large fractures and small faults) by combining the random generation of natural fracture networks with the unstructured discrete fracture modeling method to break through the traditional continuous medium well test model. In addition, the model is solved by using the finite element method with mixed element, and the typical well test type curves under different random fracture networks are obtained. And the following research results are obtained. First, based on the observed data, the fracture network distribution modes of fractured tight sandstone gas reservoirs are classified into three categories. The influence of random generation of fracture networks on typical well test type curves is discussed. The results of discrete fracture well test model are compared with those of the traditional continuous medium well test model, and the applicable conditions of the traditional continuous medium well test model is determined. Second, there are great differences between the results of discrete fracture model and those of dual porosity medium model. 1 The dual porosity medium model is a special case of the discrete fracture model, in which the fractures are evenly distributed within infinitely small spacing. Third, the characteristics of well test type curves under three fracture network distribution modes are discussed. The well test type curves that cannot be interpreted by the conventional dual/triple porosity continuous medium model are successfully interpreted by using the established well test interpretation model of random discrete fracture. The curve matching effect is ideal and the interpreted parameters are reasonable. In conclusion, the new model and the new method reveal the development mechanism of step-by-step production and coordinated gas supply between media of different scales, explain the development characteristics of large inter-well productivity difference and abnormal rapid inter-well pressure response, and provide a reference for the development of similar gas reservoirs.

This article proposes a robust control optimization design problem based on Nash game-theoretic for the marching tank bi-directional stabilization system of an all-electric actuator, which is accompanied by complex uncertainty (possibly fast time-varying but bounded). The task is to drive the barrel firing angle to adjust to a specified position under complex uncertainty while ensuring that multiple design parameters are optimally chosen in the controller. Firstly, the machine-electric coupled dynamics equations with uncertainty are created in the form of state space. Secondly, a robust controller with two design parameters to be chosen is given so that the constraint following error has uniform boundedness and uniform ultimate boundedness. Thirdly, a Nash game cost function consisting of three components: performance cost, time cost and control cost is proposed, and the Nash equilibrium (i.e., optimal control parameters) is obtained by minimizing the cost function. Finally, a co-simulation experimental platform is built to verify the robustness of the controller under complex uncertainty (modeling errors, uncertain disturbances and road excitation) and to demonstrate the global optimal performance of the system under optimal design parameters.

In real life, only partial information of samples is available everywhere, this makes Incomplete multi-view clustering (IMVC) becomes a significant research topic to handle data loss situations. Recently, several methods leverage the anchor strategy by selecting fixed anchors to handle the challenging large-scale IMVC. However, all of them ignore the guidance of prior information hidden in the bipartite graph. Therefore, we propose a novel Anchor Pseudo-supervise Large-scale Incomplete Multi-view Clustering (AP-LIMC) method by introducing a prior indicator matrix as a pseudo-supervise anchor learning paradigm. Specifically, the prior indicator matrix is first introduced to control the distribution of anchors in each cluster. Then, an anchor pseudo-supervise learning framework is designed to generate high-quality anchors and a unified bipartite graph with prior indicator supervision. In addition, we design an optimized process with linear computational and extensive experiments on multiple public datasets with recent advances to validate the effectiveness, superiority, and efficiency. For example, on the Stl10 dataset, the performance of the proposed AP-LIMC improved by 23.95%,15.71%,27.39%, and 18.24% in terms of four evaluation metrics, respectively.

Abstract Objective Kawasaki disease (KD) can lead to permanent damage to coronary structures, the pathogenesis of which remains unknown. This experiment was designed to investigate whether miR‐223‐3p secreted in the serum of KD patients affects the proliferation and apoptosis of HCAECs in KD by regulating FOXP3. Methods Blood samples were collected in acute febrile phase of KD, after IVIG treatment, and from healthy controls. Transfected into HCAECs cells by synthetic FOXP3 siRNA/NC. A co‐culture system was established between HCAECs cells transfected with FOXP3 siRNA/NC and THP1 cells added with three sera. Results Compared with the control group, the expressions of miR‐223‐3p, RORγt, and Th17 in serum of KD patients were significantly upregulated, and the expressions of TGF‐β1, FOXP3 and Treg were significantly downregulated. At the same time, the levels of IL‐6, IL‐17, and IL‐23 were significantly increased, and the levels of IL‐10 and FOXP3 were significantly decreased. After IVIG treatment, the patient's above results were reversed. The serum of KD patients increased the expression of miR‐223‐3p and inhibited the expression of FOXP3 in HCAECs cells. IVIG serum is the opposite. Overexpression of miR‐223‐3p also promoted the apoptosis of HCAECs. In addition, serum from KD patients promoted apoptosis, whereas serum after IVIG treatment inhibited apoptosis. KD patient serum downregulated the expression of FOXP3, Bcl2, TGF‐β1 and IL‐10 in cells, and upregulated the expression of caspase3, Bax, IL‐17, IL‐6, and IL‐23. The opposite results were obtained with IVIG‐treated sera. Conclusion miR‐223‐3p secreted in serum of KD patients can regulate the expression of FOXP3 and affect the proliferation, apoptosis, and inflammation of cells.

Due to the complex structure of the joint module and harsh working conditions of unmanned platforms, the fault information is often overwhelmed by noise. Moreover, traditional mechanical health state recognition methods usually require a large amount of labeled data in advance, which is difficult to obtain for specific fault data in engineering applications. This limited amount of fault data restricts the diagnostic performance. Additionally, the characteristics of convolutional neural networks (CNNs) limit their ability to capture the relative positional information of fault features. In order to obtain more comprehensive fault information, this paper proposes an intelligent health state recognition method for unmanned platform joint modules based on feature modal decomposition (FMD) and the enhanced capsule network. Firstly, the collected vibration signals are decomposed into a series of feature modal components using FMD. Then, time–frequency maps containing significant fault features are generated based on the continuous wavelet transform (CWT). Finally, a multi-scale feature enhancement (MLFE) module and an efficient channel attention (ECA) module are proposed to enhance the feature extraction capability of the capsule network, extracting more comprehensive global and local feature information from the time–frequency maps to achieve the intelligent state recognition of joint modules. This approach enhances fault features while reducing the impact of redundant features, significantly improving the feature extraction capability without increasing the model’s computational complexity. The effectiveness and superiority of the proposed method are validated through experiments on an unmanned platform joint-module testbed. An ablation experiment demonstrates the effectiveness of the MLFE and ECA modules, and a comparison with other advanced network models proves the superiority of the proposed method for health status recognition.

The Keshen gas field in the Kuqa Depression, the Tarim Basin, China, contains multiple ultra-deep fractured tight sandstone gas reservoirs with edge/bottom water, which are remarkably complex in geologic structure, with fracture systems at different scales. There is still a lack of a method for effectively describing the flow behaviors of such reservoirs. In this paper, the fracture system was characterized by classes using the actual static and dynamic data of the gas reservoirs, and the mathematical models of gas (single-phase) and gas-water two-phase flows in “pore–fracture–fault” multi-porosity discrete systems. A fracture network system was generated randomly by the Monte-Carlo method and then discretized by unstructured grid. The flow models were solved by the hybrid-unit finite element method. Taking Keshen-2/8 reservoirs as examples, four types of dynamic formation modes were built up. Performances of reservoir of the same category were systematically analyzed, which revealed the coupling of gas supply and water invasion mechanisms in different fracture systems. The gas single-phase flow was found with the characteristic of “fault–fracture gas produced successively and matric-fracture system coupling overlaid”, while the gas-water two-phase flow showed the characteristic of “rapid water dash in fault, drained successive in fractures and matric block divided separately”. This study reveals the development features of this unique reservoir effectively, and designs development strategies of full life cycle water control for enhancing the gas recovery. It can be expected that the recovery factor of newly commissioning reservoirs would be increased by more than 10% as compared with the Keshen-2 gas reservoir. These findings will play an important role in guiding high and stable production of Keshen gas field development in the long term.

Ultra-deep major gas fields are typically characterized by high and ultra-high pressure, tight matrix and developed fractures, so the reserve estimation is of higher uncertainty. In order to accurately estimate the reserves of this type of gas reservoir, this paper analyzed the correlation between the effective rock compressibility and the cumulative effective rock compressibility based on the material balance equation of high and ultra-high pressure gas reservoirs, and accordingly selected the material balance based analysis method suitable for the reserves estimation of high and ultra-high pressure gas reservoirs. Then, the starting calculation conditions of reserve estimation were determined using the non-linear regression method. In addition, a semi-logarithmic type curve matching method was established for the cases where the starting conditions could not be met. Finally, this method was applied to calculate the reserves of three ultra-high pressure gas fields (reservoirs) to verify its reliability. And the following research results were obtained. First, the cumulative effective compressibility of gas reservoir in the material balance equation of high and ultra-high pressure gas reservoir is a key parameter influencing its reserves, and it is the function of original formation pressure and current average formation pressure, but its numerical value can be hardly obtained by core experiments. Second, it is recommended to adopt the nonlinear regression method without compressibility to estimate the reserves of high and ultra-high pressure gas reservoirs. Third, the calculation starting point of reserves by the nonlinear regression method (the starting point of dimensionless apparent formation pressure-cumulative gas production curve deviating from the straight line relationship) cannot be theoretically calculated. The calculation starting point for different dimensionless linear coefficients (ωD) obtained from the statistical results by the graphic method corresponds to the dimensionless apparent pressure depletion degree of 0.06–0.38, and that obtained based on the data statistics of the example gas reservoir falls within this interval. Fourth, when the starting conditions are not satisfied, the semi-logarithmic type curve matching method can be used for reserve estimation. The ratio of the reserves to the apparent geological reserves G/Gapp is a function of ωD.The higher the ωD, the lower the G/Gapp. Fifth, for the high and ultra-high pressure gas reservoirs in the production test stage, the test production time shall be extended as long as possible to improve the reliability of reserve estimation. And for those in the middle and late stages of development, it is necessary to prepare the comprehensive treatment measures on the basis of reserves so as to improve the development effects of gas reservoirs continuously.

In order to quickly and accurately evaluate gas well deliverability, it is necessary to clarify the applicable conditions of the simplified laminar-inertial-turbulent gas well deliverability evaluation method (i.e., pressure-squared method and pressure method). In this regard, this paper analyzes the PVT data, simulation wells and field case wells of typical gas reservoirs in China by reviewing the formal evolution of the flow control equation for the real gases in porous media. Then, the applicable conditions of binomial pressure-squared method and pressure method are discussed. And the following research results were obtained. First, when the pressure is lower than 14 MPa, μZ is basically a constant; and when the pressure is higher than 42 MPa,ρμZ is basically a constant. Second, the applicable range of the pressure-squared method can be increased from 14 to 20 MPa. In this case, the relative error of absolute open flow potential calculated using the pressure-squared method is less than 5% compared with the pseudo-pressure method. If the pressure is between 20 and 30 MPa, the relative error of the absolute open flow potential calculated using the pressure-squared method is less than 10%. Third, when the pressure exceeds 80 MPa, the relative error of the absolute open flow potential calculated using the pressure method is less than 10% compared with the pseudo-pressure method. If the pressure-squared method is used in the case of high pressure, the calculated absolute open flow potential is lower and the relative error is close to 25%. Fourth, in the case of low pressure, if the pressure is constant, the higher the temperature is, the smaller the relative error between the pressure-squared method and the pseudo-pressure method is. In the case of high pressure, if the pressure is constant, the higher the temperature is, the greater the relative error between the pressure method and the pseudo-pressure method. In conclusion, it is recommended to adopt the pseudo-pressure method in laminar–inertial-turbulent gas well deliverability analysis. In the case of low pressure (below 30 MPa), the pressure-squared method can be used. In the case of high pressure (above 80 MPa), the pressure method can be applied.

It is difficult to determine the effective reservoir rock compressibility, aquifer volume and water influx of high pressure and ultra-high pressure gas reservoirs, so when the traditional apparent reservoir pressure and cumulative gas production curve extrapolation method and its modified version are used to calculate the initial gas in-place of such gas reservoirs, the calculation accuracy is lower. The material balance equation in the form of power function for such gas reservoirs was established based on Gonzalez method to improve the accuracy and reliability of reserve evaluation. Then, based on 20 high pressure and ultra-high pressure reservoirs that had been developed abroad, the empirical value of the power exponent was defined, and the influences of the depletion degree of apparent reservoir pressure and the degree of reserve recovery on the reliability of reserve calculation were analyzed. Besides, the critical value of the key parameter affecting the reliability of reserve evaluation (depletion degree of apparent reservoir pressure) was determined and compared with the critical value of the two-linear trends. Finally, an example calculation was carried out. And the following research results were obtained. First, the empirical value of the power exponent calculated using the material balance method in the form of power function is 1.02847, with an upper limit of 1.11567. Second, the depletion degree of apparent reservoir pressure corresponding to the inflection point of the classical two-linear trends ranges from 0.14 to 0.38 with an average of 0.23, while that corresponding to the extrapolation point of the second straight line is between 0.23 and 0.50 with an average of 0.33, and the corresponding degree of reserve recovery is in the range of 33%–65% with an average of 45%. Third, the reserves of such high pressure gas reservoirs calculated with this new method has an error rate less than 10% if the depletion degree of apparent reservoir pressure is greater than 0.33. In conclusion, for such high pressure gas reservoirs and the stress-sensitive fractured gas reservoirs, the material balance method in the form of power function proposed in this paper can avoid the uncertainty parameters (e.g. effective reservoir rock compressibility, aquifer volume and water influx) and it is advantageous with simple calculation process, better practicability and small error. Keywords: High pressure and ultra-high pressure gas reservoir, Reservoir, Effective rock compressibility, Depletion degree of apparent reservoir pressure, Cumulative gas production, Material balance method in the form of power function, Initial gas in-place

There is high uncertainty in reserve estimation during the early development of deep ultrahigh pressure gas reservoirs, largely because it remains challenging in accurately determining the formation compressibility. To overcome this, starting from the definition of compressibility, a novel gas production of cumulative unit pressure drop analysis method was established, of which the effectiveness was proven by applications in calculating the reserves of three gas reservoirs. It has been found that, in the limiting case, i.e., when the formation pressure dropped to the normal atmospheric pressure, the dimensionless gas production of the cumulative unit pressure drop was the reciprocal of the initial formation pressure. Besides, the relationship curve of the dimensionless gas production of the cumulative unit pressure drop and pressure drop was a straight line in the medium term, extending the straight line and intersecting the vertical line passing through the original formation pressure point, and the reserves can be determined according to the intersection point and the initial formation pressure. However, due to the influence of natural gas properties, the value needs further correction, and the correction coefficient depends on the pseudocritical temperature of natural gas. Specifically, when the pseudocritical temperature is given, the correction coefficient would be close to the minimum value of the natural gas deviation factor. When the pseudocritical temperature is more than 1.9 and less than 3.0, the minimum deviation factor would be between 0.90 and 1.0, and the higher the pseudocritical temperature, the closer the ratio is to 1.0.

Juvenile idiopathic arthritis (JIA) is a heterogeneous autoimmune disease characterized by arthritis of unknown etiology. JNK pathway-associated phosphatase (JKAP) is reported to be a negative regulator of T-cell activation, but its clinical role in JIA is unknown. This study aimed to investigate the correlation of JKAP with disease activity and treatment response to a tumor necrosis factor (TNF) inhibitor, etanercept (ETN), in JIA patients. Totally, 104 JIA patients (6.9 ± 2.7 years old) and 100 age- and sex-matched healthy controls (HCs) (7.2 ± 2.4 years old) were enrolled, and their serum samples were collected for measuring JKAP by enzyme-linked immunoassay. In JIA patients, after 24-week ETN treatment, clinical response was assessed based on the American College of Rheumatology pediatric criteria (ACRpedi) 50 criteria. Results showed that JKAP levels were significantly lower in JIA patients compared with HCs, and of good value in differentiating JIA patients from HCs. Among JIA patients, higher JKAP levels were associated with lower disease activity indexes, including C-reactive protein, number of joints with active arthritis, physician's global assessment of disease activity, and the present history of disease-modifying antirheumatic drugs; higher baseline JKAP levels were correlated with worse ACRpedi 50 response to ETN at week 24, and was also an independent predictive factor for worse ACRpedi 50 response to ETN. Thus, it may be inappropriate to use ETN for JIA patients with higher JKAP levels. In conclusion, serum JKAP is a potential biomarker for JIA activity and treatment response to a TNF inhibitor. [ABSTRACT FROM AUTHOR]