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Numerical simulation of the dynamic migration mechanism and prediction of saturation of tight sandstone oil

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Science China Earth Sciences 2024年第1期67卷 179-195页

作者： Gaohui CAO mian LIN Likuan zhang Lili JI Wenbin JIANG Institute of Mechanics Chinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China Institute of Geology and Geophysics Chinese Academy of SciencesBeijing 100029China

Quantitative characterization of tight sandstone oil migration and accumulation is an emerging research frontier in the field of oil and gas *** this study,a conceptual model containing multiple basic geological elements is developed,and a nonlinear seepage numerical model for tight sandstone oil migration and accumulation is *** effects of the slip effect,overpressure driving force,buoyancy,and capillary force on the migration and accumulation of tight oil are *** results showed that(1)the differences in oil migration and accumulation between tight and conventional reservoirs are reflected in the growth mode of oil saturation,distribution characteristics of oil and water,and extent of the effect of the formation dip angle;(2)the slip effect has a significant impact when the average pore throat radius is less than 150 nm and the overpressure driving force and capillary force are the main mechanical mechanisms controlling oil migration and accumulation in tight sandstone,while the coupling effect of buoyancy,capillary force,and overpressure driving force controls the upper and lower limits of oil ***,a dimensional and dimensionless identification chart for rapidly predicting the oil saturation of tight sandstone is proposed and verified using the measured *** study provides a basis for analyzing the migration and accumulation mechanisms of tight sandstone oil and a new approach for predicting oil ***,we developed digital and visual analysis methods for the migration results,enriching the expression of the dynamics of hydrocarbon accumulation.

关键词： Tight sandstone Migration and accumulation Dynamics Oil saturation Numerical simulation

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

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Petroleum Science 2024年第2期21卷 885-902页

作者： Xin zhang Yun-Hu Lu Yan Jin mian Chen Bo Zhou State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing102249China College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China College of Artificial Intelligence China University of Petroleum(Beijing)Beijing102249China PetroChina Tarim Oilfield Company KorlaXinjiang841000China

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum *** deep learning technique has been receiving more interest due to the great potential to deal with pore pressure ***,most of the traditional deep learning models are less efficient to address generalization *** fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic ***,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss *** machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure *** CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few *** validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization *** adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

关键词： Pore pressure prediction Seismic data 1D convolution pyramid pooling Adaptive physics-informed loss function High generalization capability

P-symmetric Subharmonic Solutions for Nonlinear Hamiltonian Systems

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Acta Mathematica Sinica,English Series 2024年第6期40卷 1388-1408页

作者： Duan zhi zhang zhi Hao ZHAO School of Mathematical Sciences Nankai UniversityTianjin 300071P.R.China

In this paper,we prove that for each positive k≡1 mod m there exists a P-symmetric kmτ-periodic solution xk for asymptotically linear mτ-periodic Hamiltonian systems,which are nonautonomous and endowed with a *** the P-symmetric Hamiltonian function is semi-positive,one can prove,under a new iteration inequality of the Maslov-type P-index,that xk_(1) and xk_(2) are geometrically distinct for k_(1)/k_(2)≥(2n+1)m+1;and xk_(1),xk_(2) are geometrically distinct for k_(1)/k_(2)≥m+1 provided xk_(1) is non-degenerate.

关键词： P-symmetric subharmonic Hamiltonian systems Maslov-type index theory iteration inequality asymptotically linear

Enhanced memristor performance via coupling effect of oxygen vacancy and ferroelectric polarization

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Journal of Materials Science & Technology 2024年第4期171卷 139-146页

作者： zhi Yun Yue zhi Dong zhang Zhan Jie Wang Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Materials Science and Engineering University of Science and Technology of ChinaShenyang 110016China School of Materials Science and Engineering Shenyang University of TechnologyShenyang 110870China

As a new type of nonvolatile memory,the resistive memristor has broad application prospects in in-formation storage and neural computing based on its excellent resistive switching(RS)*** present,it is still a great challenge to improve both ferroelectric polarization and leakage current to achieve a high RS on/offratio of ferroelectric ***,epitaxial Pb(Zr_(0.40)Ti_(0.60))O_(3)(PZT)thin films with low content Ca doping were deposited on the Nb:SrTiO_(3)substrate to prepare PCZT/NSTO het-erostructures and their RS behaviors were *** research findings show that compared with pure PZT film,the ferroelectric polarization of 1-mol%-Ca-doped PZT film is slightly improved,while the leak-age current is increased by three orders of ***,the RS on/offratio reaches 2.5×10^(5),about three orders of magnitude higher than pure PZT *** theoretical analysis reveals that the RS behavior of PCZT/NSTO heterostructures is controlled by the PCZT/NSTO interfacial barrier and the space charge-limited current *** results demonstrate that the ferroelectricity and electricity of ferroelectric thin films can be improved simultaneously by doping low-content Ca ions to increase the RS performance,which provides a good reference for the development of high-performance ferroelectric memristor devices.

关键词： Ferroelectric memristor Ca-doped PZT Ferroelectric polarization Oxygen vacancies Resistive switching

A continuous and long-term in-situ stress measuring method based on fiber optic. Part I: Theory of inverse differential strain analysis

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Petroleum Science 2024年第2期21卷 1171-1189页

作者： Kun-Peng zhang mian Chen Chang-Jun Zhao Su Wang Yong-Dong Fan State Key Laboratory of Petroleum Resources and Prospecting China University of PetroleumBeijing102249China MOE Key Laboratory of Petroleum Engineering in China University of Petroleum Beijing102249China Beijing International Center for Gas Hydrate School of Earth and Space SciencesPeking UniversityBeijing100871China

A method for in-situ stress measurement via fiber optics was proposed. The method utilizes the relationship between rock mass elastic parameters and in-situ stress. The approach offers the advantage of long-term stress measurements with high spatial resolution and frequency, significantly enhancing the ability to measure in-situ stress. The sensing casing, spirally wrapped with fiber optic, is cemented into the formation to establish a formation sensing nerve. Injecting fluid into the casing generates strain disturbance, establishing the relationship between rock mass properties and treatment ***, an optimization algorithm is established to invert the elastic parameters of formation via fiber optic strains. In the first part of this paper series, we established the theoretical basis for the inverse differential strain analysis method for in-situ stress measurement, which was subsequently verified using an analytical model. This paper is the fundamental basis for the inverse differential strain analysis method.

关键词： In-situ stress Fiber optic Orthotropic elastic Differential evolution ABAQUS

Combination of diketone and PAO to achieve macroscale oil-based superlubricity at relative high contact pressures

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Friction 2024年第5期12卷 869-883页

作者： Shaonan DU Chenhui zhang zhi LUO State Key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing100084China Beijing National Laboratory of Molecular Sciences CAS Key Laboratory of Engineering PlasticsInstitute of ChemistryChinese Academy of SciencesBeijing100190China

1-(4-ethylphenyl)-nonane-1,3-dione(0206)is an oil-soluble liquid molecule with rod-like *** this study,the chelate(0206-Fe)with octahedral structure was prepared by the reaction of ferric chloride and 1,*** experimental results show that when using 0206 and a mixed solution containing 60%0206-Fe and 40%0206(0206-Fe(60%))as lubricants of the steel friction pairs,superlubricity can be achieved(0.007,0.006).But their wear scar diameters(WSD)were very large(532µm,370µm),which resulted in the pressure of only 44.3 and 61.8 MPa in the contact areas of the friction *** 0206-Fe(60%)was mixed with PAO6,it was found that the friction coefficient(COF)decreased with increase of 0206-Fe(60%)in the *** the ratio of 0206-Fe(60%)to PAO6 was 8:2(PAO6(20%)),it exhibited better comprehensive tribological properties(232.3 MPa).Subsequent studies have shown that reducing the viscosity of the base oil in the mixed solution helped to reduce COF and increased *** the COF,contact pressure,and running-in time,it was found that the mixed lubricant(Oil3(20%))prepared by the base oil with a viscosity of 19.7 mPa·s(Oil3)and 0206-Fe(60%)exhibited the best tribological properties(0.007,161.4 MPa,3,100 s).

关键词： diketone oil-based lubricants chelate superlubricity

Gene therapy for monogenic disorders: challenges, strategies, and perspectives

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Journal of Genetics and Genomics 2024年第2期51卷 133-143页

作者： Yi zhang zhi-Ying Wu Department of Medical Genetics and Center for Rare Diseases Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310009China Department of Neurology Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310009China Key Laboratory of Medical Neurobiology of Zhejiang Province HangzhouZhejiang 310009China

Monogenic disorders refer to a group of human diseases caused by mutations in single genes. While disease-modifying therapies have offered some relief from symptoms and delayed progression for some monogenic diseases, most of these diseases still lack effective treatments. In recent decades, gene therapy has emerged as a promising therapeutic strategy for genetic disorders. Researchers have developed various gene manipulation tools and gene delivery systems to treat monogenic diseases. Despite this progress, concerns about inefficient delivery, persistent expression, immunogenicity, toxicity, capacity limitation, genomic integration, and limited tissue specificity still need to be addressed. This review gives an overview of commonly used gene therapy and delivery tools, along with the challenges they face and potential strategies to counter them.

关键词： Gene therapy Monogenic diseases Geneediting Genedelivery Challenges

Study on the tribological properties of metal rolling bearing under lubrication with diketone lubricants

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Science China(Technological Sciences) 2024年第7期67卷 2003-2017页

作者： DU ShaoNan zhang ChenHui LUO zhi State Key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing 100084China Beijing National Laboratory of Molecular Sciences CAS Key Laboratory of Engineering PlasticsInstitute of ChemistryChinese Academy of SciencesBeijing 100190China

In this article, 1-(4-ethylphenyl)-nonane-1,3-dione(0206) was prepared by Claisen condensation. By mixing 0206, chelate, and base oil in a ratio of 3.2:4.8:2, a diketone lubricant(PAO=14(20%)) that can achieve superlubricity was prepared and applied to bearing lubrication experiments. The experimental results show that when the bearing was lubricated by base oil, the friction coefficient(COF) and temperature rise decreased with the decrease of the viscosity of PAO. When PAO=14(20%) was used as the lubricant, the COF of the bearing was the lowest(0.001), and the wear morphology was comparable to that of the bearing lubricated with commercial lubricant. Compared with the base oil with the same viscosity, it is found that the COF and temperature rise of the bearing lubricated by PAO=14(20%) were lower under any experimental conditions. And when the amount of lubricant added was 10 μL, the COF of the bearing lubricated by PAO=14(20%) reached a very low value(0.0004).Bearing ball surface analysis identified the formation of diketone adsorption films. Combined with the previous PAO=14(20%)superlubricity mechanism, it was considered that the occurrence of tribochemical reaction and the bearing effect of chelates were the main reasons for the existence of ultra-low friction coefficient and low wear. In addition, when there were polar molecules in the lubricant, they were adsorbed on the metal surface through tribochemical reactions, resulting in many irregular pits on the surface.

关键词： superlubricity diketone chelate tribochemical recations bearing lubrication

Deciphering and integrating invariants for neural operator learning with various physical mechanisms

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National Science Review 2024年第4期11卷 111-122页

作者： Rui zhang Qi Meng zhi-Ming Ma Academy of Mathematics and Systems Science Chinese Academy of Sciences(CAS) Microsoft Research

Neural operators have been explored as surrogate models for simulating physical systems to overcome the limitations of traditional partial differential equation(PDE) solvers. However, most existing operator learning methods assume that the data originate from a single physical mechanism, limiting their applicability and performance in more realistic scenarios. To this end, we propose the physical invariant attention neural operator(PIANO) to decipher and integrate the physical invariants for operator learning from the PDE series with various physical mechanisms. PIANO employs self-supervised learning to extract physical knowledge and attention mechanisms to integrate them into dynamic convolutional *** to existing techniques, PIANO can reduce the relative error by 13.6%–82.2% on PDE forecasting tasks across varying coefficients, forces or boundary conditions. Additionally, varied downstream tasks reveal that the PI embeddings deciphered by PIANO align well with the underlying invariants in the PDE systems, verifying the physical significance of PIANO.

关键词： neural operator PDE solver contrastive learning physical invariants