Development and Application of a Production Data Analysis Model for a Shale Gas Production Well

This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the study were based on the analytical and empirical approaches.Its reliability has been confirmed through comparisons with a commercial software.Using transient data relating to multi-stage hydraulic fractured horizontal wells,it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4%compared to the actual estimated ultimate recovery(EUR).On the basis of the developed model,reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada.The EUR was computed as 9.6 Bcf using the modified hyperbolic method.Employing the Pow Law Exponential method,the EUR would be 9.4 Bcf.The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.

Development of Safety Factors for the UT Data Analysis Method in Plant Piping

There are several thousand piping components in a nuclear power plant. These components are affected by degradation mechanisms such as FAC (Flow-Accelerated Corrosion), cavitation, flashing, and LDI (Liquid Droplet Impingement). Therefore, nuclear power plants implement inspection programs to detect and control damages caused by such mechanisms. UT (Ultrasonic Test), one of the non-destructive tests, is the most commonly used method for inspecting the integrity of piping components. According to the management plan, several hundred components, being composed of as many as 100 to 300 inspection data points, are inspected during every RFO (Re-Fueling Outage). To acquire UT data of components, a large amount of expense is incurred. It is, however, difficult to find a proper method capable of verifying the reliability of UT data prior to the wear rate evaluation. This study describes the review of UT evaluation process and the influence of UT measurement error. It is explored that SAM (Square Average Method), which was suggested as a method for reliability analysis in the previous study, is found to be suitable for the determination whether the measured thickness is acceptable or not. And, safety factors are proposed herein through the statistical analysis taking into account the components’ type.

Understanding Human Development Potentials and Demands for Greenhouse Gas Emissions:with Empirical Analysis using time series and cross-sectional data

Based on an investigation of the meaning of development, the neo-classical economic approach to development, and the post-welfarist theory of development, this paper proposes a conceptual framework for understanding human development potentials, while undertaking empirical analysis using cross-sectional and time series data on human development. Human development is associated with basic necessities for subsistence, the quality of life, and political and civil rights, in addition to income indicators. Our analysis suggests that the concept of human development potentials has two dimensions: the rights of development and limits to human development. Both are largely ignored in the neoclassical theory of development. However, human development is not unbounded, which approaches to a relatively fixed constant at given economic, technological and institutional conditions. This conceptual understanding is supported by results from the empirical examination of the relationships between demands for carbon

Assessment of rural sustainable development and analysis and prediction of obstacles and coupled coordinated development:A case study of Zaozhuang City

In China,the Innovation Demonstration Zone for the National Sustainable Development Agenda is a key initiative for executing the United Nations(UN)2030 Agenda for Sustainable Development.The Zone also plays critical roles in addressing the developmental bottlenecks that China faces and sharing Chinese insights into global sustainable development efforts.On July 15,2022,the State Council endorsed the Zone’s establishment in Zaozhuang City,Shandong Province,where it focuses on innovation-led sustainable development in rural areas.Research into the levels,impediments,interdependencies,and evolutionary trends of rural sustainable development is crucial.Therefore,this research aimed to assist in comprehensively assessing developmental challenges and facilitating the harmonious advancement of social,economic,and environmental aspects in rural areas.In pursuit of the three fundamental dimensions of the UN’s Sustainable Development Goals(SDGs),namely development’s drivers,quality,and equity,this study was grounded in China’s national Rural Revitalization Strategy and the demands of sustainable development strategies.It also aligns with the UN 2030 Agenda for Sustainable Development and the associated SDG indicators.Focusing on four key areas,namely production elements,natural elements,social elements,and rural governance,this study developed an evaluation index system for assessing the level of rural sustainable development.It employed a range of analytical models,including the game theory-based combination empowerment method,barrier degree model,coupling degree model,coupling coordination degree model,and gray prediction GM(1,1)model,to analyze the status and evolving trends of rural sustainable development in Zaozhuang City from 2015 to 2022.The key findings were as follows:①Relative to the baseline year 2015,the sustainable development level in Zaozhuang’s rural areas has shifted toward an improved state overall.②The primary barrier to achieving rural sustainable development in Zaozhuang is the city’s rural governance system.③While the components of rural sustainable development in Zaozhuang are in the early stages of both basic and moderate coordination,an overall enhancement has occurred in their integrative coordination.④Between 2023 and 2025,the level of integrative coordination in Zaozhuang is expected to rise steadily.However,reaching a state of advanced coordination will require additional time for development.

Study of inter-well interference in shale gas reservoirs by a robust production data analysis method based on deconvolution

In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering,this study proposes a robust production data analysis method based on deconvolution,which is used for multi-well inter-well interference research.In this study,a multi-well conceptual trilinear seepage model for multi-stage fractured horizontal wells was established,and its Laplace solutions under two different outer boundary conditions were obtained.Then,an improved pressure deconvolution algorithm was used to normalize the scattered production data.Furthermore,the typical curve fitting was carried out using the production data and the seepage model solution.Finally,some reservoir parameters and fracturing parameters were interpreted,and the intensity of inter-well interference was compared.The effectiveness of the method was verified by analyzing the production dynamic data of six shale gas wells in Duvernay area.The results showed that the fitting effect of typical curves was greatly improved due to the mutual restriction between deconvolution calculation parameter debugging and seepage model parameter debugging.Besides,by using the morphological characteristics of the log-log typical curves and the time corresponding to the intersection point of the log-log typical curves of two models under different outer boundary conditions,the strength of the interference between wells on the same well platform was well judged.This work can provide a reference for the optimization of well spacing and hydraulic fracturing measures for shale gas wells.

A Statistical Analysis of China＇s Traffic Tunnel Development Data

Traffic tunnels include tunnel works for traffic and transport in the areas of railway, highway, and rail transit. With many mountains and nearly one fifth of the global population, China possesses numerous large cities and megapolises with rapidly growing economies and huge traffic demands. As a result, a great deal of railway, highway, and rail transit facilities are required in this country. In the past, the construction of these facilities mainly involved subgrade and bridge works; in recent years.

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

Mapping the Research Landscape of Language Development in Autistic Children: A Preliminary Scientometric Analysis

Children with autism spectrum disorder(ASD)often encounter difficulties in language learning and utilization,a concern that has gained significant academic attention,particularly given the widespread occurrence of ASD globally.Previous reviews,however,have relied on empirical observations rather than a more rigorous selection criterion.This preliminary study seeks to systematize the scientific knowledge base regarding language development in autistic children by utilizing the analysis tool Citespace 6.2.R5.We visualized and analyzed research patterns and trends regarding autism by drawing data from the Web of Science.Through document citation and emerging trend analyses,seven key research clusters and their chronological associations are identified,along with research hotspots such as language disorder diagnosis and intervention,social communication,language acquisition,and multilingual and multicultural influences.Research findings show that there exist some issues with the current research,including small sample sizes,the need for further investigation into receptive language development,and a lack of cross-cultural comparative studies.Meanwhile,the scope and depth of interdisciplinary research on language development in autistic children also need to be further enhanced.The research contributes to the extant literature by providing valuable references for autism researchers and practitioners.

Data-Empowered High-Quality Economic Development: Mechanisms and Pathways

To achieve high-quality economic development,it is imperative to prioritize the real economy and foster new factors for economic growth.Data,as a new factor of production,plays a pivotal role in facilitating the seamless integration between digital technology and the real economy.It possesses inherent attributes and techno-economic characteristics that enable the extraction of value across various processes,including production,transaction,consumption,and regulatory supervision.The integration with digital technology enhances the productivity and efficiency of the real economy by facilitating service sector digitalization,accelerating the growth of the new real economy,and supporting the virtual economy in its role of serving the real economy.At present,unleashing the value of data is hindered by inadequate fundamental systems for the data,a lack of activity in the transaction market,and the underutilization of the data as a factor of production by enterprises in the real economy.Therefore,it is advised that data be fully utilized to develop the real economy through the four-pronged approach of“enhancing support for the high-quality provision of the data,expediting the integration of the data into the real economy,promoting the high-quality development of the real economy,and enhancing public service and governance systems”.

Analysis on the Development Model of Relic and Museum Tourism Products Based on ERP Analysis:A Case Study on Shandong Province

In recent years, the trend of people choosing relic and museum tourism during their vacationand leisure time is growing day by day, mainly because it touches people's feelings about historical relicsand cultural heritage. The development of relic and museum tourism products is not only the inheritanceof culture and the protection of cultural relics, but also the promotion of tourism consumption under thebackground of cultural tourism integration, which has promoted the development of regional economy.With the relic and museum tourism resources in Shandong Province as the research object, through theanalysis of its resources, market and products, this paper put forward three applicable modes of relic andmuseum tourism product development, including independent development, joint development, and artauthorization, and proposed specific suggestions around the three modes.

Utilization of Real-World Data in Drug Development

With the rapid development of modern science and technology, traditional randomized controlled trials have become insufficient to meet current scientific research needs, particularly in the field of clinical research. The emergence of real-world data studies, which align more closely with actual clinical evidence, has garnered significant attention in recent years. The following is a brief overview of the specific utilization of real-world data in drug development, which often involves large sample sizes and analyses covering a relatively diverse population without strict inclusion and exclusion criteria. Real-world data often reflects real clinical practice: treatment options are chosen according to the actual conditions and willingness of patients rather than through random assignment. Analysis based on real-world data also focuses on endpoints highly relevant to clinical benefits and the quality of life of patients. The booming big data technology supports the utilization of real-world data to accelerate new drug development, serving as an important supplement to traditional clinical trials.

Analysis on the Development Trend of Enterprise Information Management under the Background of Data and Internet

Informatization involves the development and change of various fields of modern society, especially for the development of the national economy has a profound impact. In other words, the enterprise and general management, but not necessarily be governance. Further extended the policy implication is that： the establishment of the basic corporate governance structure is the form of the restrictions, not all companies need to establish the corporate governance structure. Only with the direction of general enterprise development in line, can really play a role in guiding the enterprise information, so as to further promote the overall development of enterprises as information planning and development needs accuracy only in the establishment of accurate information. Guided by this perspective, this paper proposes the novel enterprise information management paradigm under the background of data and lnternet, the proposed methodology solves the related challenges well.

Comparison of R and Excel in the Field of Data Analysis

This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.

Research on the Development Strategy of Smart Tourism in Hainan Under the Background of Big Data

Hainan is a major tourist province.It is urgent to promote the transformation and upgrading of Hainan’s tourism industry from a traditional service industry to a modern service industry by means of informatization.Smart tourism is a brand-new tourism form and operation mode of tourism transformation and upgrading.Integrating big data technology will make smart tourism more accurate in three aspects:tourism management,tourism service,and tourism marketing,and further enhance the satisfaction of the tourism experience.This paper studies the development status of smart tourism in Hainan,deeply summarizes its existing problems and causes,and puts forward the development strategy of smart tourism in Hainan to promote the healthy development of the tourism industry in Hainan.

Exploration of University English Teachers’Acceptance and Willingness to Use Learning Management System Data Analysis Tools

This study investigates university English teachers’acceptance and willingness to use learning management system(LMS)data analysis tools in their teaching practices.The research employs a mixed-method approach,combining quantitative surveys and qualitative interviews to understand teachers’perceptions and attitudes,and the factors influencing their adoption of LMS data analysis tools.The findings reveal that perceived usefulness,perceived ease of use,technical literacy,organizational support,and data privacy concerns significantly impact teachers’willingness to use these tools.Based on these insights,the study offers practical recommendations for educational institutions to enhance the effective adoption of LMS data analysis tools in English language teaching.

Path Analysis of High-Quality Development of Regional Economy The Role and Impact of Industrial Policies

With China’s economic development entering a new normal,high-quality regional economic development has become an important goal of current economic development.As one of the important means to promote high-quality development of the regional economy,industrial policies are increasingly receiving attention in terms of their role and impact.This article mainly conducts an in-depth analysis of the mechanism and impact path of industrial policies,exploring the role and impact of industrial policies in promoting high-quality regional economic development.Firstly,industrial policies play an important role in promoting high-quality regional economic development.Secondly,the impact path of industrial policies on the high-quality development of the regional economy mainly includes promoting industrial structure upgrading,promoting technological innovation,guiding resource allocation,and enhancing enterprise competitiveness.Therefore,it is necessary to increase research and practice on industrial policies,continuously optimize policy measures,and promote high-quality development of the regional economy.

Research on the prediction method for fluvial-phase sandbody connectivity based on big data analysis--a case study of Bohai a oilfield

The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield.Conventional connectivity studies often use methods such as seismic attribute fusion,while the development of contiguous composite sandbodies in this area makes it challenging to characterize connectivity changes with conventional seismic attributes.Aiming at the above problem in the Bohai A Oilfield,this study proposes a big data analysis method based on the Deep Forest algorithm to predict the sandbody connectivity.Firstly,by compiling the abundant exploration and development sandbodies data in the study area,typical sandbodies with reliable connectivity were selected.Then,sensitive seismic attribute were extracted to obtain training samples.Finally,based on the Deep Forest algorithm,mapping model between attribute combinations and sandbody connectivity was established through machine learning.This method achieves the first quantitative determination of the connectivity for continuous composite sandbodies in the Bohai Oilfield.Compared with conventional connectivity discrimination methods such as high-resolution processing and seismic attribute analysis,this method can combine the sandbody characteristics of the study area in the process of machine learning,and jointly judge connectivity by combining multiple seismic attributes.The study results show that this method has high accuracy and timeliness in predicting connectivity for continuous composite sandbodies.Applied to the Bohai A Oilfield,it successfully identified multiple sandbody connectivity relationships and provided strong support for the subsequent exploration potential assessment and well placement optimization.This method also provides a new idea and method for studying sandbody connectivity under similar complex geological conditions.

Digital Application Objectives and Benefit Analysis of BIM Technology in Large-Scale Comprehensive Development Projects

This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a total area of 92,100 square meters,with a total construction area of 379,700 square meters,including a variety of architectural forms.Through three-dimensional modeling and simulation analysis,BIM technology significantly enhances the design quality and efficiency,shortens the design cycle by about 20%,and promotes the collaboration and integration of project management,improving the management efficiency by about 25%.During the construction phase,the collision detection and four-dimensional visual management functions of BIM technology have improved construction efficiency by about 15%and saved the cost by about 10%.In addition,BIM technology has promoted green building and sustainable development,achieved the dual improvement of technical and economic indicators and social and economic benefits,set an example for enterprises in digital transformation,and opened up new market businesses.

DEVELOPMENT AND ERROR ANALYSIS OF AN INSPECTING SYSTEM FOR MEASURING THE ROTATIONAL INERTIA OF BULLETS

介绍了一种用于测量弹丸转动惯量的高精度测量仪器，该仪器利用双悬丝扭摆机构、光电计时系统提取摆动周期信息，由MCS-51系列单片机组成的测量系统进行数据处理，并由LED显示器测量结果。文中阐述了仪器的工作原理， 推导了所需的计算公式，分析了产生测量误差的因素，进行了定量精度分析，给出了实验结果与测量精度。

Seismic data analysis based on spatial subsets

There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from common shot gathers or other datasets located at certain points or along lines. We propose a novel method in this paper to observe seismic data on time slices from spatial subsets. The composition of a spatial subset and the unique character of orthogonal or oblique subsets are described and pre-stack subsets are shown by 3D visualization. In seismic data processing, spatial subsets can be used for the following aspects： （1） to check the trace distribution uniformity and regularity; （2） to observe the main features of ground-roll and linear noise; （3） to find abnormal traces from slices of datasets; and （4） to QC the results of pre-stack noise attenuation. The field data application shows that seismic data analysis in spatial subsets is an effective method that may lead to a better discrimination among various wavefields and help us obtain more information.