Evolutionary-assisted reinforcement learning for reservoir real-time production optimization under uncertainty

Production optimization has gained increasing attention from the smart oilfield community because it can increase economic benefits and oil recovery substantially.While existing methods could produce high-optimality results,they cannot be applied to real-time optimization for large-scale reservoirs due to high computational demands.In addition,most methods generally assume that the reservoir model is deterministic and ignore the uncertainty of the subsurface environment,making the obtained scheme unreliable for practical deployment.In this work,an efficient and robust method,namely evolutionaryassisted reinforcement learning(EARL),is proposed to achieve real-time production optimization under uncertainty.Specifically,the production optimization problem is modeled as a Markov decision process in which a reinforcement learning agent interacts with the reservoir simulator to train a control policy that maximizes the specified goals.To deal with the problems of brittle convergence properties and lack of efficient exploration strategies of reinforcement learning approaches,a population-based evolutionary algorithm is introduced to assist the training of agents,which provides diverse exploration experiences and promotes stability and robustness due to its inherent redundancy.Compared with prior methods that only optimize a solution for a particular scenario,the proposed approach trains a policy that can adapt to uncertain environments and make real-time decisions to cope with unknown changes.The trained policy,represented by a deep convolutional neural network,can adaptively adjust the well controls based on different reservoir states.Simulation results on two reservoir models show that the proposed approach not only outperforms the RL and EA methods in terms of optimization efficiency but also has strong robustness and real-time decision capacity.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

Comparison of Two Real-time PCR Technigues for Quantification of GMO Contents in Highly Processed Products of Soybean

The RR soybean was quantitatively detected by ABI Prism 7300 sequence detector with PCR primers and fluorescence probes were designed according to the sequences of endogenous Lectin gene and exogenous CP4-EPSPS gene, and the PCR systems were based on SYBR Green I and TaqMan. The standard curve of ACt between CP4-EPSPS gene and Lectin gene of the RR soybean in standard materials was generated and a linear regression equation was obtained. Quantification methods were optimized through two different real-time PCR chemistries, i.e. SYBR Green I and TaqMan, and the RR soybean contents were quantified in five standard samples and seven highly processed products by the two assays. Both methods are proved to be specific, highly sensitive and reliable for both identification and quantification of soybean DNA. The results indicate that the two optimized PCR system can be used for the practical quantitative detection of RR soybean in highly processed products.

Application of Real-time Fluorescent Quantitative PCR in Plant

Real-time fluorescent quantitative PCR （RQ-PCR） is a detection method by adding fluorescent dye or fluorescent probe into the PCR reaction system, using fluorescent signal accumulation to monitor amplification reactions of PCR reaction process, and finally the unknown template can be quantitatively analyzed through the standard curve. So the detection level of PCR has improved from the qualitative to the quantitative. In order to provide a theoretical reference for further application, the principle, classification, advantages and disadvantages of RQ-PCR were intro- duced, and its application and progress in plants in recent years were reviewed.

大学教育监督对教师生产力的影响

大学教育监督是高等教育质量保障的必要环节,也是教师生产力的重要决定因素。为了解教师对教学监督的认知和看法,采用问卷调查和访谈方法,对一所省属高校的教师进行抽样调查。结果发现教师都非常重视自己的专业发展,但管理的教育监督形式还存在一些问题。本文从评价改革、评价方式和督导队伍建设三个方面提出对策建议,以期将教学监督作为提高教师生产力和教育高质量发展的重要推手。

Enhancing production monitoring: A back allocation methodology to estimate well flow rates and assist well test scheduling

Production flow rates are crucial to make operational decisions,monitor,manage,and optimize oil and gas fields.Flow rates also have a financial importance to correctly allocate production to fiscal purposes required by regulatory agencies or to allocate production in fields owned by multiple operators.Despite its significance,usually only the total field production is measured in real time,which requires an alternative way to estimate wells'production.To address these challenges,this work presents a back allocation methodology that leverages real-time instrumentation,simulations,algorithms,and mathe-matical programming modeling to enhance well monitoring and assist in well test scheduling.The methodology comprises four modules:simulation,classification,error calculation,and optimization.These modules work together to characterize the flowline,wellbore,and reservoir,verify simulation outputs,minimize errors,and calculate flow rates while honoring the total platform flow rate.The well status generated through the classification module provides valuable information about the current condition of each well(i.e.if the well is deviating from the latest well test parameters),aiding in decision-making for well testing scheduling and prioritizing.The effectiveness of the methodology is demonstrated through its application to a representative offshore oil field with 14 producing wells and two years of daily production data.The results highlight the robustness of the methodology in properly classifying the wells and obtaining flow rates that honor the total platform flow rate.Furthermore,the methodology supports well test scheduling and provides reliable indicators for well conditions.By uti-lizing real-time data and advanced modeling techniques,this methodology enhances production monitoring and facilitates informed operational decision-making in the oil and gas industry.

中国-东盟职业本科人才培养助推新质生产力发展的督导机制与实践路径

中国-东盟职业本科人才培养助推新质生产力发展是时代的新需求,而督导对中国-东盟职业本科人才培养助推新质生产力发展具有重要价值。督导机制系统包括统一培养目标的跨国协调机制、教育资源配置的动态优化机制、教学模式创新与评估的整合机制。跨国协调机制统一了培养目标,强调各国间的协作,确保区域内教育标准的统一性与规范性。动态优化机制致力于教育资源配置的合理性,通过共享优质资源,提升职业教育的整体质量。整合创新与评估机制推动教学模式的创新,结合大数据分析与反馈,确保教学效果与产业需求的紧密结合。督导机制的一体化建设、类别化运作、实体化推进,才能实现中国-东盟职业本科人才培养助推新质生产力发展。

设备状态智能采集监测系统(SCADA)在锅炉制造行业的应用

设备状态智能采集监测系统(SCADA)是以计算机和以太网通讯技术为基础的生产过程监视系统,对生产设备的相关状态及工作参数进行实时远程监测。项目规划初期,我们基于公司离散化生产、通讯协议种类多、智能设备覆盖程度低等特点采用了针对性的建设方案,有效地解决了重型制造业在从自动化向智能化升级过程中的诸多痛点。管理者可以通过该系统远程监控设备的工作状态、能耗、工艺参数、报警文本等生产过程数据,为数字化生产管理提供必要的数据支撑。

供应链金融会提升企业全要素生产率吗?

供应链金融同时具备供应链属性和金融属性,其如何促进企业高质量发展引起了学术界的关注。以2010—2022年A股上市公司为样本,分析了供应链金融对企业全要素生产率的影响。研究表明:供应链金融会提升企业全要素生产率;机制检验发现,供应链金融通过缓解融资约束和降低代理成本提高企业全要素生产率;异质性检验发现,与企业数字化程度低、地区市场化程度高、存在银企关系的企业相比,在企业数字化程度高、地区市场化程度低、非银企关系下,供应链金融对企业全要素生产率的促进作用更明显。该研究丰富了供应链金融经济后果的研究文献,也对提高企业供应链现代化水平、促进企业和经济高质量发展具有理论和实践价值。

Quality monitoring of real-time GNSS precise positioning service system

The Real-Time Global Navigation Satellite System(GNSS)Precise Positioning Service(RTPPS)is recognized as the most promising system by providing precise satellite orbit and clock correc-tions for users to achieve centimeter-level positioning with a stand-alone receiver in real-time.Although the products are available with high accuracy almost all the time,they may occasionally suffer from unexpected significant biases,which consequently degrades the positioning perfor-mance.Therefore,quality monitoring at the system-level has become more and more crucial for providing a reliable GNSS service.In this paper,we propose a method for the monitoring of realtime satellite orbit and clock products using a monitoring station network based on the Quality Control(QC)theory.The satellites with possible biases are first detected based on the outliers identified by Precise Point Positioning(PPP)in the monitoring station network.Then,the corresponding orbit and clock parameters with temporal constraints are introduced and esti-mated through the sequential Least Square(LS)estimator and the corresponding Instantaneous User Range Errors(IUREs)can be determined.A quality indicator is calculated based on the IUREs in the monitoring network and compared with a pre-defined threshold.The quality monitoring method is experimentally evaluated by monitoring the real-time orbit and clock products generated by GeoForschungsZentrum(GFZ),Potsdam.The results confirm that the problematic satellites can be detected accurately and effectively with missed detection rate 4×10^(-6) and false alarm rate 1:2×10^(-5).Considering the quality alarms,the PPP results in terms of RMS of positioning differences with respect to the International GNSS Service(IGS)weekly solution in the north,east and up directions can be improved by 12%,10%and 27%,respectively.

Biomonitoring for traditional herbal medicinal products using DNA metabarcoding and single molecule, real-time sequencing

Global concerns have been paid to the potential hazard of traditional herbal medicinal products(THMPs). Substandard and counterfeit THMPs, including traditional Chinese patent medicine, health foods, dietary supplements, etc. are potential threats to public health. Recent marketplace studies using DNA barcoding have determined that the current quality control methods are not sufficient for ensuring the presence of authentic herbal ingredients and detection of contaminants/adulterants. An efficient biomonitoring method for THMPs is of great needed. Herein, metabarcoding and single-molecule, realtime(SMRT) sequencing were used to detect the multiple ingredients in Jiuwei Qianghuo Wan(JWQHW), a classical herbal prescription widely used in China for the last 800 years. Reference experimental mixtures and commercial JWQHW products from the marketplace were used to confirm the method. Successful SMRT sequencing results recovered 5416 and 4342 circular-consensus sequencing(CCS) reads belonging to the ITS2 and psb A-trn H regions. The results suggest that with the combination of metabarcoding and SMRT sequencing, it is repeatable, reliable, and sensitive enough to detect species in the THMPs, and the error in SMRT sequencing did not affect the ability to identify multiple prescribed species and several adulterants/contaminants. It has the potential for becoming a valuable tool for the biomonitoring of multi-ingredient THMPs.

低温短保质期乳制品出厂检验国内外法规标准对比

针对低温短保质期乳制品的出厂检验现状,开展国内外相关法规标准对比分析,以期为市场监管部门提供技术参考依据,为乳制品行业的绿色健康发展提供保障。收集国际食品法典委员会(Codex Alimentarius Commission,CAC)、美国、欧盟、澳大利亚、中国、加拿大、日本等国家、地区或组织关于低温短保质期乳制品出厂检验相关法规标准,从低温短保质期乳制品的生乳质量安全控制要求、生产加工过程控制要求、终产品微生物控制要求3个角度进行综述和对比分析。研究发现,CAC、美国、欧盟、澳大利亚等国家、地区或组织更加注重低温短保质期乳制品全产业链的过程控制,从而达到产品出厂要求,而我国要求终产品检验合格方可出厂,过程控制和评价体系尚不完善。过程控制是低温短保质期乳制品质量安全控制的本质,过程控制的思路可为今后我国相关标准法规的制修订提供参考,值得学习和借鉴。

南方林区林产品运输监管系统的研发

在南方林区,林产品为凭证运输,运输数量、时间、轨迹均要求与码单吻合。传统执法方法给现代林业生产带来了许多困扰,因此研制了一套运输监管系统,通过GPS技术获得车辆实际运输起止时间、起点、轨迹、终点,并通过GPRS技术与服务器、执法车辆的语音手机连接组成了无线物联网。服务器接收到运输轨迹数据后和检尺码单数据对比可实现电子监查,指派最近的执法车追踪检查异常的运输行为。经林区环境实测证实,该设备平均延时2.7s,丢包率为1.2%,能达到监控轨迹的要求。该设备应用后能够节省执法人力资源、降低执法开支,提高管理科学化水平。

区域(省级)发电公司生产实时监管系统的研发

根据区域发电公司生产管理特点,研发了1套完整的生产实时监管系统。该系统集成了生产数据的实时采集、计算分析和实用功能模块,实现了区域发电公司各部门、各电厂之间生产数据的传输和共享,使相关人员可迅速、及时、全面、详细、准确地得到区域发电公司的各发电厂生产运行情况,提高区域发电公司的技术管理水平。

管道三层PE生产过程计算机监控系统

在分析管道三层PE防腐层性能指标与工艺参数关系的基础上,选用了温度及速度恒值控制、附加速度变化及钢管初始温度变化的前馈的复合控制方案,对胶轮磨损引起的系统模型变化进行了在线数据分析修正,对系统在包覆段的快进、恒速、快出段进行了速度优化协调。利用PLC和采用等间距记时的方法实现了对钢管的轴向行进速度的在线检测;设计出了管道防腐计算机监控系统。

基于追溯的农产品质量安全监管平台设计与实现

农产品质量安全监管平台是基于已有的农产品质量追溯系统扩展开发的,解决了农产品质量监管缺乏信息化手段、系统间信息无法共享等问题。基于面向对象的程序设计思想和任务—角色的访问控制策略,综合运用数据库技术、网络技术、软件技术,为农产品质量安全在线监管、公共信息发布、用户追溯查询、农产品企业信息收集和管理,以及监管机构工作效能考核等构建了统一的平台。

料粒生产线在线监控系统

结合石油、化工企业催化剂车间的生产工艺要求 ,将计算机系统、电气系统与机械系统有机地结合起来 ,设计了一套以机械采样为基础、数据通信为载体、计算机决策为核心、自动控制为手段的料粒生产线在线监控系统 ,实现了SiO2 料粒的在线监控与分析。应用表明 ,显著提高了企业的生产效率和产品质量。

煤矿安全事故预警、监控与应急响应关键技术研究

分析了煤矿安全生产事故应急预案存在的主要问题,提出应当重视对危险源的重新评估、危险源数据库的建立和实时监控、通过计算机建立起事故应急响应平台的研究,这些研究应当是煤矿安全事故预警、监控与应急响应的关键技术。并探讨了这些关键技术的核心内容,指出通过对危险源的重新评估和建立各类危险源数据库,采取加强管理、重点防护及计算机应用等先进手段的基础上,建立重大事故应急预案救援信息管理系统,有助于最终实现应急指挥智能化,信息化,高效化,最终实现事故预防、监控、救援的一体化,发挥出应急预案的真正功效。

监控组态软件在煤矿安全综合微机监控系统集成中的应用

针对煤矿生产企业安全监测不完备和管理手段落后等现状,主要分析了煤矿分布式安全综合监测监控系统的构成思路及注意事项,着重介绍了监控组态软件在系统集成中所发挥的重要作用,对煤炭企业的安全生产、文明生产、科学生产具有重要的意义。

基于GIS和SCADA技术的油气储运生产调度系统

利用GIS空间分析功能、计算机、通信网络和SCADA系统实时数据采集与自动控制功能对整个油气储运生产运行过程的主要参数、管道信息、设备运行状况进行动态监测,实时调度和自动化控制,实现自动化信息管理。并以GIS为基础,整合管线和设备周围的地理信息、管线和设备本身的空间信息及其图形信息、维护信息、监控信息等信息于一体,将管线和设备的运行状态借助地理空间实时地提供给使用者,同时结合SCADA系统,采集生产实时数据和对各种生产工况进行自动控制,并根据经济、技术指标和实际情况,进行优化控制反馈,完成对油气储运生产各个环节的合理配置,保障油气储运生产经济、安全可靠运行。