Intelligent architecture modeling for multilevel fluvial reservoirs based on architecture interface and elements

At present,the architecture modeling method of fluvial reservoirs are still developing.Traditional methods usually use grids to characterize architecture interbeds within the reservoir.Due to the thin thickness of this type of the interlayers,the number of the model grids must be greatly expanded.The number of grids in the tens of millions often makes an expensive computation;however,upscaling the model will generate a misleading model.The above confusion is the major reason that restricts the largescale industrialization of fluvial reservoir architecture models in oilfield development and production.Therefore,this paper explores an intelligent architecture modeling method for multilevel fluvial reservoirs based on architecture interface and element.Based on the superpositional relationship of different architectural elements within the fluvial reservoir,this method uses a combination of multilevel interface constraints and non-uniform grid techniques to build a high-resolution 3D geological model for reservoir architecture.Through the grid upscaling technology of heterogeneous architecture elements,different upscaling densities are given to the lateral-accretion bedding and lateral-accretion bodies to simplify the model gridding.This new method greatly reduces the number of model grids while ensuring the accuracy of lateral-accretion bedding models,laying a foundation for large-scale numerical simulation of the subsequent industrialization of the architecture model.This method has been validated in A layer of X oilfield with meandering fluvial channel sands as reservoirs and B layer of Y oilfield with braided river sands as reservoirs.The simulation results show that it has a higher accuracy of production history matching and remaining oil distribution forecast of the targeted sand body.The numerical simulation results show that in the actual development process of oilfield,the injected water will not displace oil in a uniform diffusive manner as traditionally assumed,but in a more complex pattern with oil in upper part of sand body being left behind as residual oil due to the influences of different levels of architecture interfaces.This investigation is important to guiding reservoir evaluation,remaining oil analysis,profile control and potential tapping and well pattern adjustment.

基于POI数据的城市功能识别与分布特征研究——以长春市区为例

长春市是国家新型城镇化综合试点城市,识别长春市中心城区功能,针对当前存在的问题提出对策建议,对城市空间的优化与协调具有重要意义。以兴趣点(Point of Interest,POI)数据及开放街道地图(Open Street Map,OSM)数据为基础,结合核密度分析、实地调查验证等方法,识别长春市中心城区城市功能类型。结果表明:单一功能区中,商业功能区数量最多,居住功能区最少;主导—混合功能区中的商业主导功能区及交通主导功能区形成对商业聚集区与轨道交通系统的重要补充;细分—混合功能区特征显示功能混合程度从市中心向周边逐渐加大。经验证,城市功能识别结果符合长春市实际,由此提出对策建议:未来长春市中心城区应注重多中心发展格局,并加强绿地空间和公共服务设施建设。

结合载客热点和POI的出租车停车位划定方法

针对出租车随意停靠造成城市交通拥堵甚至交通事故的问题,利用成都实际区域的出租车GPS(Global Position System)数据和爬取的POI(Point of Interest)数据,使用DBSCAN(Density-Based Spatial Clustering of Application with Noise)聚类算法对上下客点进行聚类,得到出租车的载客热点,根据POI的类型划定载客热点区域的类型,对出租车不同时间的出行需求进行分析,进而划分出出租车的固定停车区域。研究结果表明,出租车固定停车区域的设定与出行者的出行需求有关,即将固定停车区域设置在出行者出行需求多的区域,可以满足出行者的不同出行需求。结合出租车载客热点和爬取POI数据划定固定停车区域的方法具有较高的实用性,可为城市交通安全方面提供理论和现实意义。

Effect of indium addition on the microstructural formation and soldered interfaces of Sn-2.5Bi-1Zn-0.3Ag lead-free solder

The microstructural formation and properties of Sn-2.5Bi-xln-lZn-0.3Ag （in wt%） alloys and the evolution of soldered interfaces on a Cu substrate were investigated. Apart from the relatively low melting point （about 195C）, which is close to that of conventional eutectic Sn-Pb solder, the investigated solder presents superior wettability, solderability, and ductility. The refined equiaxial grains enhance the me- chanical properties, and the embedded bulk intermetallic compounds （IMCs） （Cu6Sn5 and CusZns） and granular Bi particles improve the joint reliability. The addition of In reduces the solubility of Zn in the 13-Sn matrix and strongly influences the separation and growth behaviors of the IMCs. The soldered interface of Sn-2.5Bi-xln-lZn-0.3Ag/Cu consists of Cu-Zn and Cu-Sn IMC layers.

Simulation of Seawater Intrusion in Coastal Confined Aquifer Using a Point Collocation Method Based Meshfree Model

Seawater intrusion caused by groundwater over-exploitation from coastal aquifers poses a severe problem in many regions. Formulation of proper pumping strategy using a simulation model can assure sustainable supply of fresh water from the coastal aquifers. The focus of the present study is on the development of a numerical model based on Meshfree (MFree) method to study the seawater intrusion problem. For the simulation of seawater intrusion problem, widely used models are based on Finite Difference (FDM) and Finite Element (FEM) Methods, which demand well defined grids/meshes and considerable pre-processing efforts. Here, MFree Point Collocation Method (PCM) based on the Radial Basis Function (RBF) is proposed for the simulation. Diffusive interface approach with density-dependent dispersion and solution of flow and solute transport is adopted. These equations are solved using PCM with appropriate boundary conditions. The developed model has been verified with Henry’s problem, and found to be satisfactory. Further the model has been applied to another established problem and an attempt is made to examine the influence of important system parameters including pumping and recharge on the seawater intrusion. The PCM based MFree model is found computationally efficient as preprocessing is avoided when compared to other numerical methods.

Giant magneto-impedance sensor with working point selfadaptation for unshielded human bio-magnetic detection

Background Compared with traditional biomagnetic field detection devices,such as superconducting quantum interference devices(SQUIDs)and atomic magnetometers,only giant magneto impedance(GMI)sensors can be applied for unshielded human brain biomagnetic detection,and they have the potential for application in next-generation wearable equipment for brain-computer interfaces(BCIs).Achieving a better GMI sensor without magnetic shielding requires the stimulation of the GMI effect to be maximized and environmental noise interference to be minimized.Moreover,the GMI effect stimulated in an amorphous filament is closely related to its working point,which is sensitive to both the external magnetic field and the drive current of the filament.Methods In this paper,we propose a new noise reducing GMI gradiometer with a dual-loop self-adapting structure.Noise reduction is realized by a direction-flexible differential probe,and the dual-loop structure optimizes and stabilizes the working point by automatically controlling the external magnetic field and drive current.This dual-loop structure is fully program controlled by a micro control unit(MCU),which not only simplifies the traditional constant parameter sensor circuit,saving the time required to adjust the circuit component parameters,but also improves the sensor performance and environmental adaptation.Results In the performance test,within 2 min of self-adaptation,our sensor showed a better sensitivity and signal-to-noise ratio(SNR)than those of the traditional designs and achieved a background noise of 12 pT/√Hz at 10 Hz and 7pT/√Hz at 200 Hz.Conclusion To the best of our knowledge,our sensor is the first to realize self-adaptation of both the external magnetic field and the drive current.

Analysis of the effect of repeated-pulse transcranial magnetic stimulation at the Guangming point on electroencephalograms

Here, we administered repeated-pulse transcranial magnetic stimulation to healthy people at the left Guangming （GB37） and a mock point, and calculated the sample entropy of electroencephalo- gram signals using nonlinear dynamics. Additionally, we compared electroencephalogram sample entropy of signals in response to visual stimulation before, during, and after repeated-pulse tran- scranial magnetic stimulation at the Guangming. Results showed that electroencephalogram sample entropy at left （F3） and right （FP2） frontal electrodes were significantly different depending on where the magnetic stimulation was administered. Additionally, compared with the mock point, electroencephalogram sample entropy was higher after stimulating the Guangming point. When visual stimulation at Guangming was given before repeated-pulse transcranial magnetic stimula- tion, significant differences in sample entropy were found at five electrodes （C3, Cz, C4, P3, T8） in parietal cortex, the central gyrus, and the right temporal region compared with when it was given after repeated-pulse transcranial magnetic stimulation, indicating that repeated-pulse transcranial magnetic stimulation at Guangming can affect visual function. Analysis of electroencephalogram revealed that when visual stimulation preceded repeated pulse transcranial magnetic stimulation, sample entropy values were higher at the C3, C4, and P3 electrodes and lower at the Cz and T8 electrodes than visual stimulation followed preceded repeated pulse transcranial magnetic stimula- tion. The findings indicate that repeated-pulse transcranial magnetic stimulation at the Guangming evokes different patterns of electroencephalogram signals than repeated-pulse transcranial mag- netic stimulation at other nearby points on the body surface, and that repeated-pulse transcranial magnetic stimulation at the Guangrning is associated with changes in the complexity of visually evoked electroencephalogram signals in parietal regions, central gyrus, and temporal regions.

A Modified Model for Soil–Structure Interface Considering Random Damage of Mesoscopic Contact Elements

The interaction between soil and marine structures like submarine pipeline/pipe pile/suction caisson is a complicated geotechnical mechanism process.In this study,the interface is discretized into multiple mesoscopic contact elements that are damaged randomly throughout the shearing process due to the natural heterogeneity.The evolution equation of damage variable is developed based on the Weibull function,which is able to cover a rather wide range of distribution shapes by only two parameters,making it applicable for varying scenarios.Accordingly,a statistical damage model is established by incorporating Mohr–Coulomb strength criterion,in which the interfacial residual strength is considered whereby the strain softening behavior can be described.A concept of“semi-softening”characteristic point on shear stress–displacement curve is proposed for effectively modeling the evolution of strain softening.Finally,a series of ring shear tests of the interfaces between fine sea sand and smooth/rough steel surfaces are conducted.The predicted results using the proposed model are compared with experimental data of this study as well as some results from existing literature,indicating that the model has a good performance in modeling the progressive failure and strain softening behavior for various types of soil–structure interfaces.

Interest Points Analysis for Internet Forum Based on Long-Short Windows Similarity

For Internet forum Points of Interest(PoI),existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation,which lead to blindness in method selection.To address this problem,this paper proposed a PoI variation prediction framework based on similarity analysis between long and short windows.Based on the framework,this paper presented 5 PoI analysis algorithms which can be categorized into 2 types,i.e.,the traditional sequence analysis methods such as autoregressive integrated moving average model(ARIMA),support vector regressor(SVR),and the deep learning methods such as convolutional neural network(CNN),long-short term memory network(LSTM),Transformer(TRM).Specifically,this paper firstly divides observed data into long and short windows,and extracts key words as PoI of each window.Then,the PoI similarities between long and short windows are calculated for training and prediction.Finally,series of experiments is conducted based on real Internet forum datasets.The results show that,all the 5 algorithms could predict PoI variations well,which indicate effectiveness of the proposed framework.When the length of long window is small,traditional methods perform better,and SVR is the best.On the contrary,the deep learning methods show superiority,and LSTM performs best.The results could provide beneficial references for PoI variation analysis and prediction algorithms selection under different parameter configurations.

Embedding 3-D Gaze Points on a 3-D Visual Field:A Case of Transparency

2022 The paper seeks to demonstrates the likelihood of embedding a 3D gaze point on a 3D visual field,the visual field is inform of a game console where the user has to play from one level to the other by overcoming obstacles that will lead them to the next level.Complex game interface is sometimes difficult for the player to progress to next level of the game and the developers also find it difficult to regulate the game for an average player.The model serves as an analytical tool for game adaptations and also players can track their response to the game.Custom eye tracking and 3D object tracking algorithms were developed to enhance the analysis of the procedure.This is a part of the contributions to user interface design in the aspect of visual transparency.The development and testing of human computer interaction uses and application is more easily investigated than ever,part of the contribution to this is the embedding of 3-D gaze point on a 3-D visual field.This could be used in a number of applications,for instance in medical applications that includes long and short sightedness diagnosis and treatment.Experiments and Test were conducted on five different episodes of user attributes,result show that fixation points and pupil changes are the two most likely user attributes that contributes most significantly in the performance of the custom eye tracking algorithm the study.As the advancement in development of eye movement algorithm continues user attributes that showed the least likely appearance will prove to be redundant.

基于POI数据的城市功能区识别及其空间分布特征——以珠海市中心城区为例

为了探究城市功能区的空间分布特点,基于兴趣点(POI)数据构建城市功能区定量识别体系,分析珠海市中心城区城市功能区的空间分布特征.结果表明:①珠海市中心城区的功能区普遍具有明确的主导功能,且呈现“中心居住,外围工业,混合分散”的分布格局.②“单一”和“混合”功能区交错分布的地区主要集中在珠海市中心城区北部.③混合功能区多表现为居住和商业服务设施功能的混合,呈现出“商住联动”特征.

基于POI数据的郑州市文化设施的区位布局特征与影响因素研究

以服务于居民的文化设施兴趣点为研究对象,采用标准差椭圆、核密度分析等方法,定量分析了2007年和2017年郑州市文化设施空间格局的演变,并从宏观的空间形态和微观的集聚中心2个方面对比分析了博物馆、图书馆、文化馆、美术馆、影剧院5类文化设施的区位布局特征;利用地理探测器,基于大规模实地调研数据引入居民行为因素探究对文化设施空间形态的影响,并针对郑州市文化设施规划发展的方向提出相关建议。研究表明：（1）10 a来郑州市文化设施增长迅猛,由传统文化形式占优势转变为审美艺术和休闲文化占优势;（2）不同类文化设施朝着均衡的方向发展;各类文化设施的集聚特征与其自身特点和城市实际发展情况相关。（3）居民可支配时间、消费习惯、居民文化水平等居民群体因素对文化设施分布的影响是不可忽视的,且不同因素对不同类文化设施的影响大小有较大差别。针对郑州市文化设施规划发展方向的建议：（1）加强市区东北部和东南部文化设施建设;（2）多注重审美艺术和休闲文化类设施的建设,迎合居民逐渐转变的精神与价值观趋向;（3）尝试文化设施的综合性布局和多用途开发;（4）在城市规划实践中综合考量不同居民群体对文化设施的需求程度和类型。

基于时空上下文信息的POI推荐模型研究

随着基于位置的社交网络(LBSN)技术的快速发展,为移动用户提供个性化服务的兴趣点(POI)推荐成为关注重点。由于POI推荐面临着数据稀疏、影响因素多和用户偏好复杂的挑战,因此传统的POI推荐往往只考虑签到频率以及签到时间和地点对用户的影响,而忽略了签到序列中用户前后行为的关联影响。为了解决上述问题,该文通过序列的表示考虑签到数据的时间影响和空间影响,建立了时空上下文信息的POI推荐模型(STCPR),为POI推荐提供了更精准的个性化偏好。该模型基于序列到序列的框架下,将用户信息、POI信息、类别信息和时空上下文信息进行向量化后嵌入GRU网络中,同时利用了时间注意力机制、全局和局部的空间注意力机制来综合考虑用户偏好与变化趋势,从而向用户推荐感兴趣的Top-N的POI。该文通过在两个真实的数据集上实验来验证模型的性能。实验的结果表明,该文所提出的方法在召回率(Recall)和归一化折损累计增益(NDCG)方面优于几种现有的方法。

基于POI数据的西安市中心城区小学布点特征研究

在不断推进基础教育优质均衡发展,合理解决大城市学位供给矛盾的同时,如何通过有效途径判断学校空间布点是否达到规划预期,实现公众享受教育资源的公平性,是当下研究的热点之一.本研究基于2020年西安市中心城区小学315条POI数据信息,借助ArcGIS地理处理中的空间分析模块,利用平均最近邻、核密度分析和标准差椭圆等方法,分别对中心城区小学布点的宏观分布、下辖六区的中观供给、小学单元的微观覆盖三个层面进行识别和分析.研究表明:西安市中心城区小学布点呈现出整体离散的单中心格局,且“内密外疏”的沿东北—西南方向分布趋势显著;虽所辖六区中高密度人口对应高密度学校分布,但各小学单元覆盖效率不高,覆盖居住单元数量不均,实际学位供给仍存缺口等问题较为突出.

基于POI的城市空间结构分析——以北京市为例

以兴趣点数据为切入点研究中、微观尺度下城市空间结构,包括城市空间功能构成、空间分布特征及其聚散规律。中观尺度下,研究兴趣点点密度分布、城市功能聚合和扩散的演化行为以及区县中心的定位方法,并通过兴趣点分类聚集识别行业聚集子区。微观尺度下,地理位置优势使得街角具有较强的局部聚集效应和中心引力,街角的兴趣点分类分布体现出了明显的行业空间分布特征,优势街角的定位也为识别核心街区提供了可行的方法。以北京为例,不同层面的城市兴趣点结构空间分析证实,兴趣点有良好的城市形态表征能力,是探索城市功能结构的聚散规律和空间特征的有力工具。

基于POI的西安市轨道交通站域生产性服务业空间分布特征

利用兴趣点(point of interest,POI)数据对小尺度经济活动的有效描述功能,以西安市为例,探究轨道交通站域生产性服务业的空间分布特征。在提出站域范围确定方法并整合城市内部生产性服务业业态类型的基础上,通过区位商测度揭示6类业态的站域空间分布整体特征及局域特征,借助二阶偏相关分析研判站域物质空间环境对各类业态分布强度的影响,并解译蕴含的空间分布影响机制。结果表明:(1)生产性服务业业态的站域空间分布大都呈现相对全市总体占优的特征,而各类业态的局域空间分布特征又可细分为向心型、离心型和过渡型;(2)在轨道交通站域内,职住空间的多样性促进大部分业态的站域集中分布,开敞空间的开敞度抑制大部分业态的站域集中分布,道路空间的路网密度则仅对部分业态的空间分布产生较弱的正向影响;(3)西安市轨道交通站域生产性服务业空间分布的影响机制有基于强烈实体产业关联的互补性机制、基于空间资源博弈的竞争性机制、基于特定部门非典型需求的有选择支持性机制。

基于POI数据的广州市公共服务设施空间布局分析

城市的公共服务设施是一个城市提供服务能力的重要体现。本文以广州市为例,利用高德地图采集的公共服务设施POI数据,通过核密度分析、方向分布分析、相关性分析以及综合配置水平评价等空间分析方法,探究研究区公共服务设施的空间布局。得出结果如下:第一、广州市公共服务设施分布不均衡,市中心聚集性明显,总体呈现单中心或多种的模式存在。第二、各类设施间分布方向基本一致,往南北方向发展。第三、设施间相关性较强,城市发展功能分区明显,职住分离。第四、公共服务设施综合配置水平较高,区域差异明显,医疗卫生设施综合水平较低。本文的研究结果,可为广州市公共服务设施的规划提供决策参考,为POI数据在城市规划中的应用做进一步的探索。

基于POI数据的山西省旅游景区分类及空间分布特征

运用大数据与传统地理信息系统相结合的方式,以山西旅游景区POI(Point of Interest)数据为研究对象,对其进行分类后,研究其总体空间分布格局、分布方向以及具体地市空间分布特征。结果表明:山西旅游景区总体分布格局呈现晋中地区集聚特征,具体各类旅游景区的集聚形态与程度有所差异。其中,地文景观类旅游景区集聚于晋中、晋东南和晋北东部地区;水域风光类旅游景区以晋中、晋南和晋北东部地区为轴呈条带状分布;生物景观类旅游景区在空间上呈"菱形"状集聚形态;遗址遗迹类旅游景区集聚于晋北和晋东南地区;建筑与设施类旅游景区呈"三角形"状集聚特征;娱乐购物类旅游景区在全省范围内分布较为均匀。旅游景区空间分布方向与山西省区域形状吻合,除娱乐购物类旅游景区分布方向性和向心性不明显之外,其他类别旅游景区均有不同程度的集聚特征;各地市旅游景区分布情况中,水域风光类旅游景区在各市域间分布较为均匀,地文景观类和建筑设施类旅游景区热点区域出现在阳泉市,冷点区域出现在晋城市,但其集聚程度均较低;生物景观类旅游景区热点区域位于长治市,冷点区域位于临汾市和运城市,其集聚程度较高。最后,从自然地理和人文社会两方面对旅游景区空间分布的影响因素进行了定性分析。

基于POI数据的模糊地名空间范围估计

在信息检索中常用地名作为空间参照,因此确定模糊地名的空间范围备受关注。由于模糊地名不存在确切的边界,评估模糊地名空间范围十分困难,但人们对模糊地名的认知区域可以提供参考。本文分析了模糊地名空间的基本特征;以案例形式,讨论了利用POI数据和认知实验确定模糊地名空间范围的基本方法和特点,并分析这些案例地名空间的特性。从这些案例研究可以得出以下结论:影响模糊地名空间范围的因素有道路、熟悉程度和地名借用;用POI数据对模糊地名估计出的空间范围符合人们认知的空间范围。