Mechanisms and experimental research of ion-matched waterflooding to enhance oil recovery in carbonate reservoirs: A case of Cretaceous limestone reservoirs in Halfaya Oilfield, Middle East

Based on systematically summarizing the achievements of previous ion-matched waterflooding researches,the diversity and synergy of oil recovery enhancement mechanisms and the interaction between mechanisms are examined according to two classification standards,and the influence of behaviors of different ions on different mechanisms and oil displacement efficiency are investigated.Ionic strength is proposed to characterize the behavior differences of univalent and divalent ions,the relationships between ionic strength,effective concentration,and mechanisms are established to characterize the ion behavior behind various mechanisms,and evaluate the performance of ion-matched injection water.The mechanisms of enhancing oil recovery by ion-matched waterflooding include:(1)The ion-matched water can reduce the ion strength and match the ion composition of formation water,thereby reducing the difference between the effective concentration of univalent ions and divalent ions on the surface of carbonate rocks,and improving the effective concentration of potential determining ions(especially SO42-).(2)It can improve wettability,oil-water interface properties,pore structure and physical properties of the reservoir,and finally enable the establishment of a new ionic equilibrium conducive to waterflooding while breaking the original equilibrium.In this study,experiments such as relative permeability curve,interfacial tension,and core-flooding were carried out on carbonate core samples from the Cretaceous Mishrif Formation reservoirs in Halfaya Oilfield,Middle East,a method for injection water evaluation was established and the injection water suitable for these reservoirs was selected:6 times diluted seawater.Compared with ordinary seawater,oil displacement efficiency can be increased by more than 4.60%and compared with the optimum dilution of formation water,oil displacement efficiency can be increased by 3.14%.

Failure mechanism and influencing factors of cement sheath integrity under alternating pressure

The failure of cement sheath integrity can be easily caused by alternating pressure during large-scale multistage hydraulic fracturing in shale-gas well.An elastic-plastic mechanical model of casing-cement sheath-formation(CSF)system under alternating pressure is established based on the Mohr-Coulomb criterion and thick-walled cylinder theory,and it has been solved by MATLAB programming combining global optimization algorithm with Global Search.The failure mechanism of cement sheath integrity is investigated,by which it can be seen that the formation of interface debonding is mainly related to the plastic strain accumulation,and there is a risk of interface debonding under alternating pressure,once the cement sheath enters plasticity whether in shallow or deep well sections.The matching relationship between the mechanical parameters(elastic modulus and Poisson's ratio)of cement sheath and its integrity failure under alternating pressure in whole well sections is studied,by which it has been found there is a“critical range”in the Poisson's ratio of cement sheath.When the Poisson's ratio is below the“critical range”,there is a positive correlation between the yield internal pressure of cement sheath(SYP)and its elastic modulus.However,when the Poisson's ratio is above the“critical range”,there is a negative correlation.The elastic modulus of cement sheath is closely related to its Poisson's ratio,and restricts each other.Scientific and reasonable matching between mechanical parameters of cement sheath and CSF system under different working conditions can not only reduce the cost,but also protect the cement sheath integrity.

AUTOMATIC DISPLACEMENT ANALYSIS OF PLANAR MECHANISMS WITH MATCHING BASIC KINEMATIC CHAINS METHOD

A simple, efficient, automatic and universal method to fulfill displacementanalysis of a great deal of mechanisms regenerated by Yan's mechanism creative theory has beendeveloped. For a regenerated mechanism, at first, the method identifies its type and structure andchanges it into a rigid structure by fixing the ground link and the input link. And then this rigidstructure is decomposed into a set of basic kinematic chains (BKCs). By matching the type of BKC,the displacement analysis equations can be set up, and all possible configurations, in whichpositions of all movable links are considered, can be given out.

Matching between mechanics and thermodynamics among 4 individual strokes in a 4-stroke engine by non-circular gear mechanism

The relationship between engine mechanics and thermo-dynamics has been investigated by means of numerical simulation.The inherent mismatching between the mechanical behaviors and the thermodynamic process in internal combustion engine is identified,which is believed to be one of the important limiting factors of energy efficiency for conventional engines available in the current market.An approach for engine efficiency improvement through optimal matching between mechanics and thermodynamics(OMBMT)is proposed.An ideal matching model is defined and the conflicts due to the constraints among the mapping strokes in a 4-stroke engine are analyzed.A novel mechanical model is built for approaching optimal matching among all 4 individual strokes in a 4-stroke spark-ignition engine,which is composed of non-circular gears(NCG)and integrated with conventional slider crank engine mechanism.By means of digital mechanical model and numerical simulation,the matching gains among all 4 strokes are defined and calculated for quantifying the NCG engine efficiency improvement by comparing with a baseline engine.The potentials with the OMBMT implemented and the enhancements made by NCG mechanism for engines in terms of overall engine efficiency are reported.Based on the results achieved,it is recommended that the feasibility studies and the experimental validations should be conducted to verify the engine matching concept and effectiveness of the NCG mechanism engine model proposed,and the engine performance and NCG design parameters should be further optimized.

Reliability analysis of the velocity matching of coal cutting and caving in fully mechanized top-coal caving face

The matching relationship between coal cutting and caving in fully mechanized top-coal caving face is analyzed in detail from the angle of reliability. The coupling equation of reliability is established correspondingly, and the mathematical equation of the coefficient of velocity matching of coal cutting and caving is obtained, which meets a certain reliability demand for making the working procedure of coal caving not influence coal cutting of coal-cutter. The results show that the relationship between the coefficient of the velocity matching and the reliability of coal cutting and caving system is linear on the whole when R <0.9. It is pointed out that different numerical value should be selected for different coal face according to different demand for reliability.

On Model of Translation Beginners' Mechanism of Mental Translation

Translation process is a process of information processing, and also a process of translators' thinking activity. During the process of translation or bilingual communication, translators or bilingual users employ mental translation. To expound how beginners communicate or translate in the bilingual environment, the model of mechanism of mental translation, i.e. match-making mechanism of mental translation, is theoretically constructed.

Trie+结构函数式建模、机械化验证及其应用

Trie结构是一种使用搜索关键字来组织信息的搜索树,可用于高效地存储和搜索字符串集合.Nipkow等人给出了实现Trie的Isabelle建模与验证,然而其Trie在存储和操作时存在大量的冗余,导致空间利用率不高,且仅考虑英文单模式下查找.为此,基于索引即键值的思想提出了Trie+结构,相较于传统的索引与键值分开存储的结构能减少50%的存储空间,大大提高了空间利用率.并且,对Trie+结构的查找、插入、删除等操作给出了函数式建模及其严格的机械化验证,保证操作的正确性和可靠性.进一步,提出一种匹配算法的通用验证规约,旨在解决一系列的匹配算法正确性验证问题.最后,基于Trie+结构与匹配算法通用验证规约,建模和验证了函数式中英文混合多模式匹配算法,发现并解决了现有研究中的基于完全哈希Trie的多模式匹配算法的模式串前缀终止的Bug.该Trie+结构以及验证规约在提高Trie结构空间利用率和验证匹配算法中,有一定的理论和应用价值.

基于注意力与密集重参数化的目标检测算法

针对目标检测任务中背景复杂、目标尺寸差异大等因素导致目标检测结果较差的问题,本文提出基于注意力和密集重参数化的目标检测算法。首先,基于CSP-DarkNet提出高效的特征提取网络,主要包括密集重参数化模块和CASA模块2个设计。前者利用密集连接保留浅层特征,又通过重参数化结构降低网络复杂度;后者CASA模块用于获取需要的目标信息。其次,特征融合在特征金字塔(FPN)和路径聚合网络(PAN)的基础上,引入内容感知特征重组(CARAFE)进行上采样,有效解决了邻近插值法等未能捕捉丰富语义信息的问题;提出更高效的C3-G模块,获取丰富的梯度信息,增强模型表达能力和感知能力;同时,引入深度可分离卷积提升运算效率。最后,检测输出采用在更大范围上跨领域正负样本匹配策略扩充正样本数量,提升检测效果。该算法在MS COCO和PASCAL VOC数据集上的mAP@0.5分别达到了57.5%和83.0%,充分说明了本文算法的先进性。

基于两阶段代价矩阵和动态注意力的双目立体匹配网络

目前大多数先进的双目立体匹配网络通过构建4D代价矩阵以保留图像的语义信息,增加了网络的计算量开销。为了解决上述问题,提出了两阶段的组合代价矩阵和多尺度动态注意力的EDNet++网络。首先从全局的、粗粒度的视差搜索范围上构建的基于相似度的代价矩阵作为引导,在局部的搜索范围上实现细粒度的组合代价矩阵,其次提出基于残差的动态注意力机制,其根据中间结果信息自适应地生成空间上的注意力分布,并且通过迁移实验证明了该方法的有效性,最后在各大公开数据集上的对比实验结果表明,相较于其他方法,EDNet++方法能够达到算法精度和实时性的良好平衡。

高海拔铁路隧道斜井机械化配套与快速施工

为解决高海拔高寒地区斜井施工存在气压低、含氧量低、温差大、严寒干燥等问题,以某高海拔铁路隧道斜井工程为背景,结合围岩等级、断面大小、海拔高度,根据斜井施工机械化配套原则,提出高海拔陡坡长斜井机械化安全快速进洞施工工法,并选配超前支护、钻爆、装运、喷锚支护、衬砌等机械化作业线的成套设备。基于高度机械化的设备配套,提出“快挖、快运、快支”的高效施工技术以及各工序快速衔接工艺。以控制围岩变形为核心,构建一套积极干预加固围岩、注重早期支护并快速闭合的主动支护体系。结果表明:与普通钻爆法施工相比,采用三臂凿岩台车高度机械化配套施工效率高,月最快进尺为180 m,较人工钻爆法施工月进尺为130 m相比提高了近30%,施工质量稳定,作业人员投入少,且拱顶沉降和周边收敛均小于规范要求值,衬砌强度可靠,可实现高海拔小断面隧道“快挖、快支、主动支、快封闭”。

基于网络药理学和大鼠体内验证的藏药红景天改善脑微循环障碍作用机制研究

目的基于文献研究、网络药理学、分子对接与实验验证的方法,探究藏药红景天改善脑微循环障碍的核心靶点、关键成分和作用机制。方法通过文献和数据库收集红景天化学成分,利用反向药效团匹配预测红景天的潜在靶点;获取脑微循环障碍靶点,并与红景天靶点映射,构建交集靶点蛋白互作网络,获取核心靶点;构建“中药-成分-核心靶点-疾病”调控网络并获取关键成分;进行GO和KEGG富集分析,构建“核心靶点-信号通路-生物过程”网络;进行分子对接验证;采用RT-qPCR和Western blot进行动物实验验证,进一步证实网络药理学分析结果。结果从红景天中筛选出76个活性成分和285个靶点,获取脑微循环障碍靶点1074个,交集靶点97个,核心靶点6个,关键成分6个。分子对接结果表明,有3个关键成分与核心靶点的结合性大于核心靶点蛋白与其原始配体结合性。RT-qPCR结果显示红景天能下调核心靶点CASP3、AKT1 mRNA水平,Western blot检测结果显示藏药红景天能降低CASP3、AKT1蛋白表达(P<0.05)。结论藏药红景天可通过多成分、多靶点、多通路协同改善脑微循环障碍,该研究为临床应用藏药红景天治疗脑微循环障碍提供实验依据。

融合梯度先验与全局聚合的立体匹配算法

现有基于学习的立体匹配算法具有一定局限性,通常特征提取部分使用的常规卷积倾向于捕捉外观信息,忽略了结构信息的提取,并且由于卷积感受野的限制,这些算法在弱纹理、重复纹理等病态区域性能较差.为此本文提出了一种融合梯度信息及全局代价聚合的立体匹配网络模型(GFGANet).首先,设计了差分卷积残差组(CDC-ResBlock-Groups),显式编码结构信息提高特征表达,然后设计全局代价聚合模块(Trans-Hourglass),有效聚合代价体并捕获全局上下文,最后采用加窗视差回归降低了视差标签不平衡的影响,此外使用StereoDRNet的后处理进行视差细化.实验表明,所提方法在重复纹理,弱纹理区域表现优异,在SceneFlow中的端点误差(EPE)仅为0.645px,KITTI 2015上的误匹配率为2.04%,与基础模型PSMNet相比,性能显著提升.

数智时代科技成果供需对接机制

为探究我国数智时代科技成果供需对接影响因素和机制作用,梳理我国科技成果供需对接模式及演变历程,构建科技成果供需对接影响因素概念模型,运用扎根理论和文献分析方法归纳出供方、需方、平台、政策、资金和技术因素等影响因素,运用DEMATEL方法分析影响因素之间的影响度。基于分析结果,提出我国科技成果供需对接机制为从应需引供模式转变为掘需育供模式,从上下游关系转变为共同体关系,从局域平台转变为广域平台,从信息化转变为智慧化,从单点服务转变为全链条服务,从技术发展转变为多要素融合发展。

双目视觉下钻杆接口定位的实现

智能机器人技术的快速发展推动了石油钻机装备自动化和智能化的提升。针对目前石油钻机上卸扣作业中,传统的钻杆接口定位存在困难,无法实现完全自动化的问题,提出了一种基于改进YOLOv5x算法的智能钻杆接口检测方法,并在双目视觉下建立了钻杆接口定位模型。模型基于卷积神经网络提取钻杆接口的图像特征,从而实现自动识别;融合CBAM(Convolution Block Attention Module)注意力机制以提高模型的特征提取与表达能力,引入更大尺度特征图作为小目标检测层,减少了钻杆接口图像中小目标的误检和漏检情况;结合SGBM(Semi-Global Block Matching)算法,实现双目视觉下钻杆接口的精准定位;通过网络训练检验改进算法的性能,并在模拟试验环境下开展了钻杆接口的定位试验。试验结果表明:改进YOLOv5x算法平均精度达到98.6%,比原始YOLOv5x算法提高了3.0%;上下接口平均定位误差分别为7.64和6.56 mm,符合工程误差要求,具有一定的工程应用价值。所得结论可为钻杆接口的准确检测和精准定位提供技术参考。

利用BERT和覆盖率机制改进的HiNT文本检索模型

为有效提升文本语义检索的准确度,本文针对当前文本检索模型衡量查询和文档的相关性时不能很好地解决文本歧义和一词多义等问题,提出一种基于改进的分层神经匹配模型(hierarchical neural matching model,HiNT)。该模型先对文档的各个段提取关键主题词,然后用基于变换器的双向编码器(bidirectional encoder representations from transformers,BERT)模型将其编码为多个稠密的语义向量,再利用引入覆盖率机制的局部匹配层进行处理,使模型可以根据文档的局部段级别粒度和全局文档级别粒度进行相关性计算,提高检索的准确率。本文提出的模型在MS MARCO和webtext2019zh数据集上与多个检索模型进行对比,取得了最优结果,验证了本文提出模型的有效性。

基于特征增强和语义相关性匹配的图像文本检索方法

为实现图像文本检索中图像与文本的精确语义连接,提出一种基于特征增强和语义相关性匹配(FESCM)的图像文本检索方法。首先,通过特征增强表示模块,引入多头自注意力机制增强图像区域特征和文本单词特征,以减少冗余信息对图像区域和文本单词对齐的干扰;其次,通过语义相关性匹配模块,不仅利用局部匹配捕获局部显著对象之间的对应相关性,还把图像背景信息融入图像全局特征,利用全局匹配实现精确的全局语义相关性;最后,通过局部匹配分数和全局匹配分数获取图像和文本的最终匹配分数。实验结果表明,基于FESCM的图像文本检索方法在Flickr8k和Flickr30k基准数据集上的召回率总值比扩展的视觉语义嵌入方法分别提升了5.7和7.5个百分点,在MS-COCO数据集比双流层次相似度推理方法提升了3.7个百分点。因此该方法可以有效提高图像文本检索的准确度,实现图像与文本的语义连接。

基于教师-学生模型的点云目标检测算法

针对现有点云目标检测算法对室外自动驾驶场景中遮挡物体检测精度低的问题,提出一种基于知识蒸馏和注意力增强的点云目标检测算法。以CIA-SSD模型为基础,设计了一种基于教师-学生模型的密集特征生成模块,提出基于交并比匹配策略的密集数据生成方法,将稀疏特征转换为密集特征。密集特征生成模块位于学生模型中,学生模型在教师模型生成的软目标监督训练下,推断出完整的密集目标特征,实现目标特征的补全;在教师模型中设计空间注意力和通道注意力机制,增强密集目标点云,提升特征图的质量。在KITTI数据集上的验证实验结果表明:与SE-SSD模型和CIA-SSD模型相比,本文提出的算法保持了单阶段目标检测速度的优势,同时明显提升了检测精度。

结合注意力机制的卫星遥感影像立体匹配

采用立体匹配技术对多视卫星遥感影像进行三维场景重建一直是摄影测量与遥感领域的核心问题。基于卷积神经网络的深度学习方法极大地促进了立体匹配技术的发展,然而其中涉及匹配困难和误匹配问题的相关研究仍然不足。为了提升卫星遥感影像不适定区域中视差估计的精度,本研究提出了一种结合注意力机制的立体匹配深度学习网络,在特征提取模块中加入注意力机制,分别从通道和空间两个维度捕获全局信息,对特征进行优化;在代价体的构建模块中构建新的代价体积,并重新设置视差的回归范围。为了验证本文方法的有效性,在US3D、WHU-Stereo两个数据集上分别与已有方法Stereo-Net、PSM-Net进行了比较分析。结果表明,本文方法在EPE(endpointerror)和D_1两个指标上均能达到最优,取得了较好的性能,提高了立体匹配的精度,尤其在无纹理、重复纹理、遮挡及视差不连续区域表现出良好的鲁棒性。

具有跨尺度Transformer的高效多视图立体网络

现有深度多视图立体(MVS)方法将Transformer引入级联网络,以实现高分辨率深度估计,从而实现高精确度和完整度的三维重建结果。然而,基于Transformer的方法受计算成本的限制,无法扩展到更精细的阶段。为此,提出一种新颖的跨尺度Transformer的MVS网络,在不增加额外计算的情况下处理不同阶段的特征表示。引入一种自适应匹配感知Transformer(AMT),在多个尺度上使用不同的交互式注意力组合。这种组合策略使所提网络能够捕捉图像内部的上下文信息,并增强图像之间的特征关系。此外,设计双特征引导聚合(DFGA),将粗糙的全局语义信息嵌入到更精细的代价体构建中,以进一步增强全局和局部特征的感知。同时,通过设计一种特征度量损失,用于评估变换前后的特征偏差,以减少特征错误匹配对深度估计的影响。实验结果表明,在DTU数据集中,所提网络的完整度和整体度量达到0.264、0.302,在Tanks and temples 2个大场景的重建平均值分别达到64.28、38.03。

GO/SCI/EP双机制吸波性能复合材料的制备及其吸波性能研究

以具有电损耗性能的石墨烯(GO)和磁损耗性能的羰基铁(SCI)为吸波剂,以环氧树脂(EP)为基体,制备出具有双机制吸波性能的GO/SCI/EP复合材料,并通过SEM、XRD、TG、电阻率测试复合材料的形貌、结构、热稳定性、导电性,借助微波暗室及矢量网络分析仪分析材料的吸波性能并探究其吸波机理。结果表明,石墨烯、羰基铁的加入提高了复合材料的导电性和热稳定性。当石墨烯质量分数为10%、羰基铁质量分数为90%时,复合材料吸波性能最好,增大了阻抗匹配的性能,反射损耗最高可达-23.32 dB。