Experimental and numerical simulation study on the erosion behavior of the elbow of gathering pipeline in shale gas field

During the production period of shale gas, proppant particles and rock debris are produced together,which will seriously erode the elbows of gathering pipelines. In response to this problem, this paper takes the elbow of the gathering pipeline in the Changning Shale Gas Field as an example to test the erosion rate and material removal mechanism of the test piece at different angles of the elbow through experiments and compares the four erosion models with the experimental results. Through analysis, it is found that the best prediction model for quartz sand-carbon steel erosion is the Oka model. Based on the Oka model, FLUENT software was used to simulate and analyze the law of erosion of the elbow of the gas gathering pipeline under different gas flow velocities, gas gathering pressure, particle size, length of L1,and bending directions of the elbow. And a spiral pipeline structure is proposed to reduce the erosion rate of the elbow under the same working conditions. The results show that this structure can reduce erosion by 34%.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Extracting angle-domain common-image gathers in VTI media using ansiotropic-Helmholtz P/S wave-mode decomposition

Common-image gathers are extensively used in amplitude versus angle(AVA)and migration velocity analysis(MVA).The current state of methods for anisotropic angle gathers extraction use slant-stack,local Fourier transform or low-rank approximation,which requires much computation.Based on an anisotropic-Helmholtz P/S wave-mode decomposition method,we propose a novel and efficient approach to produce angle-domain common-image gathers(ADCIGs)in the elastic reverse time migration(ERTM)of VTI media.To start with,we derive an anisotropic-Helmholtz decomposition operator from the Christoffel equation in VTI media,and use this operator to derive the decomposed formulations for anisotropic P/S waves.Second,we employ the first-order Taylor expansion to calculate the normalized term of decomposed formulations and obtain the anisotropic-Helmholtz decomposition method,which generates the separated P/S wavefields with correct amplitudes and phases.Third,we develop a novel way that uses the anisotropic-Helmholtz decomposition operator to define the polari-zation angles for anisotropic P/S waves and substitute these angles to decomposing formulations.The polarization angles are then calculated directly from the separated vector P-and S-wavefields and converted to the phase angles.The ADCIGs are thusly produced by applying the phase angles to VTI ERTM.In addition,we develop a concise approximate expression of residual moveout(RMO)for PP-reflections of flat reflectors in VTI media,which avoids the complex transformations between the group angles and the phase angles.The approximate RMO curves show a good agreement with the exact solution and can be used as a tool to assess the migration velocity errors.As demonstrated by two selected examples,our ADCIGs not only produce the correct kinematic responses with regards to different velocity pertubatation,but also generate the reliable amplitude responses versus different angle.The final stacking images of ADCIGs data exhibit the identical imaging effect as that of VTI ERTM.

Slow-gathering areas of rivers, lakes, and reservoirs: Definition, estimation, and restoration

Recently,humans have been facing serious water pollution problems that aggravate water resources shortages.By 2025,two-thirds of the world's population is likely to live in countries with moderate or severe water shortages(Azizullah et al.,2011).Rivers,lakes,and reservoirs are important sources of water.Globally,there are approximately 8.5 million rivers(Linke et al.,2019),21.15 million natural lakes,and 1.427 million large reservoirs(Messager et al.,2016).Many of them have been contaminated due to urbanization,industrialization,and agricultural activities.In particular,all rivers,lakes,and reservoirs have their own slow-gathering areas(SGAs)where the input contaminants are easily stopped and deposited due to their non-open morphologies and low flow speeds.

Deep Learning Based Face Mask Detection in Religious Mass Gathering During COVID-19 Pandemic

Notwithstanding the religious intention of billions of devotees,the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Most attendees ignored preventive measures,namely maintaining physical distance,practising hand hygiene,and wearing facemasks.Wearing a face mask in public areas protects people from spreading COVID-19.Artificial intelligence(AI)based on deep learning(DL)and machine learning(ML)could assist in fighting covid-19 in several ways.This study introduces a new deep learning-based Face Mask Detection in Religious Mass Gathering(DLFMD-RMG)technique during the COVID-19 pandemic.The DLFMD-RMG technique focuses mainly on detecting face masks in a religious mass gathering.To accomplish this,the presented DLFMD-RMG technique undergoes two pre-processing levels:Bilateral Filtering(BF)and Contrast Enhancement.For face detection,the DLFMD-RMG technique uses YOLOv5 with a ResNet-50 detector.In addition,the face detection performance can be improved by the seeker optimization algorithm(SOA)for tuning the hyperparameter of the ResNet-50 module,showing the novelty of the work.At last,the faces with and without masks are classified using the Fuzzy Neural Network(FNN)model.The stimulation study of the DLFMD-RMG algorithm is examined on a benchmark dataset.The results highlighted the remarkable performance of the DLFMD-RMG model algorithm in other recent approaches.

Dataset of Large Gathering Images for Person Identification and Tracking

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi,Madinah,Saudi Arabia.This dataset consists of raw and processed images reflecting a highly challenging and unconstraint environment.The methodology for building the dataset consists of four core phases;that include acquisition of videos,extraction of frames,localization of face regions,and cropping and resizing of detected face regions.The raw images in the dataset consist of a total of 4613 frames obtained fromvideo sequences.The processed images in the dataset consist of the face regions of 250 persons extracted from raw data images to ensure the authenticity of the presented data.The dataset further consists of 8 images corresponding to each of the 250 subjects(persons)for a total of 2000 images.It portrays a highly unconstrained and challenging environment with human faces of varying sizes and pixel quality(resolution).Since the face regions in video sequences are severely degraded due to various unavoidable factors,it can be used as a benchmark to test and evaluate face detection and recognition algorithms for research purposes.We have also gathered and displayed records of the presence of subjects who appear in presented frames;in a temporal context.This can also be used as a temporal benchmark for tracking,finding persons,activity monitoring,and crowd counting in large crowd scenarios.

Study on Influencing Factors and Mechanism of Scientific and Technological Innovation Talents Gathering in Zhejiang Province

This paper systematically studies the influencing factors and mechanism of the agglomeration of scientific and technological innovation talents in Zhejiang Province. The findings are as follows: Firstly, environmental factors such as marketization level, financial development, opening to the outside world, infrastructure construction, medical resources, educational resources, cultural resources and policy support have a positive impact on the agglomeration of scientific and technological talents in Zhejiang Province;Secondly, in the transmission mechanism of the influence of various environmental factors on the concentration of scientific and technological talents in Zhejiang, economic development plays an intermediary role, and the effect is obvious. Various environmental factors indirectly affect the concentration of scientific and technological talents in Zhejiang through economic development. Finally, although both the level and quality of economic development have significant effect on the total concentration of scientific and technological talents in Zhejiang, the mediating effect of economic development level is more significant. These studies are for Zhejiang Province. It provides a theoretical basis for cultivating high-end talents and realizing the agglomeration of scientific and technological innovation talents.

GSVM:一种支持Gather/Scatter的向量存储器

宽单指令多数据流(Single Instruction Multiple Data,SIMD)架构数字信号处理器一般都能高效支持地址连续或等距跨步等规则应用的向量访存,但对于科学与工程计算中广泛存在的不规则应用的数据访存则带宽利用率往往较低,从而大幅降低了其整体运算能效。为了提高不规则应用的向量访存性能,基于某SIMD数字信号处理器的体系结构,设计了一种支持Gather/Scatter访存的向量存储器GSVM。通过设计与SIMD宽度相匹配的向量地址计算单元和合适深度的冲突缓冲器阵列,实现了Gather/Scatter指令向量地址计算、仲裁与缓存的全流水访存操作。实验结果表明,相比以前不支持Gather/Scatter访存的存储器,GSVM在增加22%的硬件代价基础上,基于稀疏矩阵向量乘的测试程序集获得了2~8的性能加速比。

Environment and Human Behaviors——Taking “The Acorn Gatherer” as a Case Study

Human living environment interacts with human behaviors.Environment to some degree determines human behaviors which in return reshape and sustain the dynamic environment.Taking Richard Jefferies' The Acorn Gatherer as a case study,this paper makes an argument that the behaviors of the villagers in the story can be more adequately interpreted in view of the backward countryside environment,and the same is true with the author Richard Jefferies' non-interference in the omniscient third-person point of view in writing the story.It is Richard Jefferies' family environment that makes up his viewpoint of writing,reflecting his critical loving of the countryside,where lives boom and conventions are extremely followed.

Social Conventions and Human Tragedy—On Richard Jefferies's The Acorn Gatherer

The Acorn Gatherer by Richard Jefferies is an allegorical tragedy, in which a nameless boy, born out of wedlock, is viewed as a sort of icon of sin, and is ultimately driven to death by the rigid and unforgiving social conventions.

Local events-based fast RTM surface-offset gathers via dip-guided interpolation

Reverse Time Migration(RTM)Surface Ofset Gathers(SOGs)are demonstrated to deliver more superior residual dip information than ray-based approaches.It appears more powerful in complex geological settings,such as salt areas.Still,the computational cost of constructing RTM SOGs is a big challenge in applying it to 3D feld data.To tackle this challenge,we propose a novel method using dips of local events as a guide for RTM gather interpolation.The residual-dip information of the SOGs is created by connecting local events from depth-domain to time-domain via ray tracing.The proposed method is validated by a synthetic experiment and a feld example.It mitigates the computational cost by an order of magnitude while producing comparable results as fully computed RTM SOGs.

An optimization method for shale gas gathering system-Consideration of reliability enhancement under earthquake-related uncertainties

Shale gas gathering systems are of great importance in gas fields for the efficient and reliable transportation of gas.In traditional design methods,pipeline layouts are optimized only from an economic point of view,where reliability is evaluated after optimization.However,reliability can be enhanced by spare pipelines so that both economic and reliable aspects are evaluated simultaneously.Based on the idea of enhancing reliability,this research proposes a methodology for optimizing the pipeline layout problem including well clustering,stations site selecting,and piping.Different topology arrangements and spare pipelines are investigated to enhance the production efficiency and reliability of the pipeline network under earthquake-related uncertainties.Reliability evaluation is converted into an economic one so that the objective of this work is to minimize the total annual cost.To solve such a complex problem,genetic algorithm,K-means algorithm,Geo Steiner algorithm,Kruskal algorithm,linear programming and Monte Carlo simulations are combined.A real-world case study illustrates the effectiveness of the proposed methodology and shows a 36.53%reduction in the total annual cost compared with the initial scheme.

Data Gathering in Wireless Sensor Networks Via Regular Low Density Parity Check Matrix

A great challenge faced by wireless sensor networks(WSNs) is to reduce energy consumption of sensor nodes. Fortunately, the data gathering via random sensing can save energy of sensor nodes. Nevertheless, its randomness and density usually result in difficult implementations, high computation complexity and large storage spaces in practical settings. So the deterministic sparse sensing matrices are desired in some situations. However,it is difficult to guarantee the performance of deterministic sensing matrix by the acknowledged metrics. In this paper, we construct a class of deterministic sparse sensing matrices with statistical versions of restricted isometry property(St RIP) via regular low density parity check(RLDPC) matrices. The key idea of our construction is to achieve small mutual coherence of the matrices by confining the column weights of RLDPC matrices such that St RIP is satisfied. Besides, we prove that the constructed sensing matrices have the same scale of measurement numbers as the dense measurements. We also propose a data gathering method based on RLDPC matrix. Experimental results verify that the constructed sensing matrices have better reconstruction performance, compared to the Gaussian, Bernoulli, and CSLDPC matrices. And we also verify that the data gathering via RLDPC matrix can reduce energy consumption of WSNs.

Single Mobile Sink Based Energy Efficiency and Fast Data Gathering Protocol for Wireless Sensor Networks

Recently, the exponential rise in communication system demands has motivated global academia-industry to develop efficient communication technologies to fulfill energy efficiency and Quality of Service (QoS) demands. Wireless Sensor Network (WSN) being one of the most efficient technologies possesses immense potential to serve major communication purposes including civil, defense and industrial purposes etc. The inclusion of sensor-mobility with WSN has broadened application horizon. The effectiveness of WSNs can be characterized by its ability to perform efficient data gathering and transmission to the base station for decision process. Clustering based routing scheme has been one of the dominating techniques for WSN systems;however key issues like, cluster formation, selection of the number of clusters and cluster heads, and data transmission decision from sensors to the mobile sink have always been an open research area. In this paper, a robust and energy efficient single mobile sink based WSN data gathering protocol is proposed. Unlike existing approaches, an enhanced centralized clustering model is developed on the basis of expectation-maximization (EEM) concept. Further, it is strengthened by using an optimal cluster count estimation technique that ensures that the number of clusters in the network region doesn’t introduce unwanted energy exhaustion. Meanwhile, the relative distance between sensor node and cluster head as well as mobile sink is used to make transmission (path) decision. Results exhibit that the proposed EEM based clustering with optimal cluster selection and optimal dynamic transmission decision enables higher throughput, fast data gathering, minima delay and energy consumption, and higher

Flow Characteristics of Crude Oil with High Water Fraction during Non-heating Gathering and Transportation

In order to ensure the safety of the non-heating gathering and transportation processes for high water fraction crude oil,the effect of temperature,water fraction,and flow rate on the flow characteristics of crude oil with high water fraction was studied in a flow experimental system of the X Oilfield.Four distinct flow patterns were identified by the photographic and local sampling techniques.Especially,three new flow patterns were found to occur below the pour point of crude oil,including EW/O&W stratified flow with gel deposition,EW/O&W intermittent flow with gel deposition,and water single-phase flow with gel deposition.Moreover,two characteristic temperatures,at which the change rate of pressure drop had changed obviously,were found during the change of pressure drop.The characteristic temperature of the first congestion of gel deposition in the pipeline was determined to be the safe temperature for the non-heating gathering and transportation of high water cut crude oil,while the pressure drop reached the peak at this temperature.An empirical formula for the safe temperature was established for oil-water flow with high water fraction/low fluid production rate.The results can serve as a guide for the safe operation of the non-heating gathering and transportation of crude oil in high water fraction oilfields.

Method for extracting angle-domain common image gathers in Kirchhoff beam migration

Kirchhoff beam migration is a simplified Gaussian beam migration,which omits the dynamic information and can calculate multi-arrival traveltime,so it is a high-precision and fast seismic imaging method.In the imaging process,extracting common image gathers can be used for velocity analysis,improving the accuracy of modeling and imaging quality.Compared with the conventional common image gathers extracting methods,the angle-domain common image gathers extracting method can avoid the artifacts caused by multi-arrival seismic waves.The authors present a new method of extracting common image gathers in angle-domain from Kirchhoff beam migration and verify the method by numerical calculations.

FAILURE ASSESSMENT OF DEFECTIVE GATHERING TUBE UNDER HIGH PRESSURE

A numerical model on stress assessment of a defective elliptic gathering tubeused in the heat recovery boiler of a pyrolyzer is built up. The effect of local defects on thecarrying capacity of the tube is analyzed by using the MSC/NASTRAN finite element code, and thecritical size of defects is obtained. Then, two numerical models of damaged tube with local andintegral reinforcements, respectively, are also calculated. Stress classification and assessmentsare provided by applying the ASME and JB4732-1995 standard. Some guidance and suggestions about thetube reinforcements and the prediction of the remaining life of the structure for engineeringpractice are discussed.

A Power Graded Data Gathering Mechanism for Wireless Sensor Networks

The data gathering manner of wireless sensor networks, in which data is forwarded towards the sink node, would cause the nodes near the sink node to transmit more data than those far from it. Most data gathering mechanisms nowdo not do well in balancing the energy consumption among nodes with different distances to the sink, thus they can hardly avoid the problem that nodes near the sink consume energy more quickly, which may cause the network rupture from the sink node. This paper presents a data gathering mechanism called PODA, which grades the output power of nodes according to their distances from the sink node. PODA balances energy consumption by setting the nodes near the sink with lower output power and the nodes far from the sink with higher output power. Simulation results show that the PODA mechanism can achieve even energy consumption in the entire network, improve energy efficiency and prolong the network lifetime.

Migration velocity modeling based on common reflection surface gather

The common-reflection-surface (CRS) stacking is a new seismic imaging method, which only depends on seismic three parameters and near-surface velocity instead of macro-velocity model. According to optimized three parameters obtained by CRS stacking, we derived an analytical relationship between three parameters and migration velocity field, and put forward CRS gather migration velocity modeling method, which realize velocity estimation by optimizing three parameters in CRS gather. The test of a sag model proved that this method is more effective and adaptable for velocity modeling of a complex geological body, and the accuracy of velocity analysis depends on the precision of optimized three parameters.

A computational method for wide-azimuth 3D dip-angle gathers using Gaussian beam migration

The dip-angle-domain common-image gather(DDCIG)is a key tool to separate the diffraction and reflection imaging results.Reflectors with different spatial geometries produce different responses in DDCIGs.Compared with Kirchhoff migration,Gaussian beam migration(GBM)is more effective and robust to overcome the multipathing problem.As a ray-based method,it has explicit angle information naturally during the propagation.We have developed a 3D DDCIG computational method using GBM,which obtain both the imaging result and angle-domain gathers with only one pass of calculation.The angle-gather computation is based on geometrical optics,and multiple angle conversions are implemented under the rules of space geometry,which helps to avoid rounding errors and improve accuracy.Additionally,the multi-azimuth joint presentation strategy is proposed to describe the characteristic of omnidirectional dip angles using a finite number of gathers.After using a 2D model to illustrate application advantages of DDCIG,we apply the proposed method to two 3D models to test its feasibility and accuracy.A field data example further demonstrates the adaptability of our method to seismic imaging for a land survey.