Production Capacity Prediction Method of Shale Oil Based on Machine Learning Combination Model

The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinear in nature,pose challenges for accurate description through physical models.While field data provides insights into real-world effects,its limited volume and quality restrict its utility.Complementing this,numerical simulation models offer effective support.To harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination model.Leveraging fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil reservoirs.Through the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well conditions.The results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

The assembly process of aerospace products such as satellites and rockets has the characteristics of single-or small-batch production,a long development period,high reliability,and frequent disturbances.How to predict and avoid quality abnormalities,quickly locate their causes,and improve product assembly quality and efficiency are urgent engineering issues.As the core technology to realize the integration of virtual and physical space,digital twin(DT)technology can make full use of the low cost,high efficiency,and predictable advantages of digital space to provide a feasible solution to such problems.Hence,a quality management method for the assembly process of aerospace products based on DT is proposed.Given that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection,the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly system.The Apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to trace.The implementation of the proposed approach is described,taking the collected centroid data of an aerospace product’s cabin,one of the key quality data in the assembly process of aerospace products,as an example.A DT-based quality management system for the assembly process of aerospace products is developed,which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

Object-Oriented Modeling of Virtual Assembly Process

Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology must be applied. Based on the idea that the virtual assembly system is an event driven system, the interactive behavior and information model is proposed to describe the dynamic process of virtual assembly. Definition of the object-oriented model of virtual assembly is put forward.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

Role Assignment and Cooperation of Ontology and Object-Oriented Principle in Construction of Digital Product Model

Powerful expressive ability of semantic information, to be easily computed and flexibility are basic features of digital product model (DPM). Using ontology and object-oriented principle (OOP) together to cope with problems in modeling is brought forward in this paper. The two are widely used and do well in modeling, but they each alone cannot cope with all issues and new challenges. Three basic requests are pointed out in DPM modeling. Status, problems, and root of current non-semantic and semantic models are introduced. Ontology, OOP, and their difference are introduced. It is found that the two are entirely complementary with each other. How to assign the roles and to cooperate for the two in coping with the three basic issues in DPM modeling are explained in detail.

A new production component method for natural gas development planning

Based on an analysis of the limitations of conventional production component methods for natural gas development planning,this study proposes a new one that uses life cycle models for the trend fitting and prediction of production.In this new method,the annual production of old and new wells is predicted by year first and then is summed up to yield the production for the planning period.It shows that the changes in the production of old wells in old blocks can be fitted and predicted using the vapor pressure model(VPM),with precision of 80%e95%,which is 6.6%e13.2%higher than that of other life cycle models.Furthermore,a new production prediction process and method for new wells have been established based on this life cycle model to predict the production of medium-to-shallow gas reservoirs in western Sichuan Basin,with predication error of production rate in 2021 and 2022 being 6%and 3%respectively.The new method can be used to guide the medium-and long-term planning or annual scheme preparation for gas development.It is also applicable to planning for large single gas blocks that require continuous infill drilling and adjustment to improve gas recovery.

Uncertain Multidisciplinary Design Optimization on Next Generation Subsea Production System by Using Surrogate Model and Interval Method

The innovative Next Generation Subsea Production System(NextGen SPS)concept is a newly proposed petroleum development solution in ultra-deep water areas.The definition of NextGen SPS involves several disciplines,which makes the design process difficult.In this paper,the definition of NextGen SPS is modeled as an uncertain multidisciplinary design optimization(MDO)problem.The deterministic optimization model is formulated,and three concerning disciplines—cost calculation,hydrodynamic analysis and global performance analysis are presented.Surrogate model technique is applied in the latter two disciplines.Collaborative optimization(CO)architecture is utilized to organize the concerning disciplines.A deterministic CO framework with two disciplinelevel optimizations is proposed firstly.Then the uncertainties of design parameters and surrogate models are incorporated by using interval method,and uncertain CO frameworks with triple loop and double loop optimization structure are established respectively.The optimization results illustrate that,although the deterministic MDO result achieves higher reduction in objective function than the uncertain MDO result,the latter is more reliable than the former.

RESEARCH OF THE PARAMETRIC ASSEMBLY METHOD

The parametric part assembly generation method is presented. Based on the parametric part generated by means of constructive-element, through interactively inputting the relationships of the location and the assembly, and by compiling operations like movement and rotation, the assembly drawing is created so as to implement the occurrence of the parameterizations of the assembly and the part drawing. The data structure of the assembly part and the key technologies of hidden line removal in the implementation of assembly process, etc. , are described in detail.

Extended Object Model for Product Configuration Design

This paper presents an extended object model for case-based reasoning （CBR） in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in ease retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.

Multi-objectives and Simulation Models for Develop Production Line in Automobiles Manufacturing System

Automotive manufacturing is complex and includes the coordination of design in the manufacturing system. The manufacturing approaches over the past few years, disassembly have been a key issue, and it seems that simulation models are usually tailored to address a narrow set of industrial issues. This paper describes the development of the production line in the automobile manufacturing system through design, operation, and maintenance, based on multi-objectives of Algorithm and Simulation Model called MOA-SM. The both models are being developed at three different levels： the production line in the body and assembly shop, supply chain, and the production plan. The optimization tries to involve more objectives to solve the issues in manufacturing system. A solution that may optimize one performance measure may deteriorate since other performance solutions are difficult. The resulting algorithms are comparable to the simulation and multi-object in terms of success rate, assembly times, peak forces, moments, and have assembly times superior to those of a benchmark blind search algorithm.

A STEP Based Integrated System for Assembly Planning and Design

An integrated system for assembly planning and design (INSAPS) is presented in which product data can be exchanged between assembly planning and assembly design on the basis of standard for exchange of product data model (STEP). The system consists of CAD system, product modeling system, assembly planning system. The product model is organized according to the STEP, uses mostly the entities of IR (integrated resources) and partly self defined entities which is necessary for assembly planning. A simple method of assembly sequence generation is presented which is suitable for complex assembly planning. The generated assembly sequences are evaluated considering the optimization of total assembly time. The results of assembly planning are feedback to the stage of assembly design to improve design.

Top-down assembly design using assembly features

The primary task of top-down assembly design is to define a product抯 detailed physical description satisfying its functional requirements identified during the functional design phase. The implementation of this design process requires two things, that is, product functional representation and a general assembly model. Product functions are not only the formulation of a customer抯 needs, but also the input data of assembly design. A general assembly model is to support the evolving process of the elaboration of a product structure. The assembly feature of extended concept is taken as a functional carrier, which is a generic relation among assembly-modeled entities. The model of assembly features describes the link between product functions and form features of parts. On the basis of this link, the propagation of design modifications is discussed so as to preserve the functionality and the coherence of the assembly model. The formal model of assembly design process describes the top-down process of creating an assembly model. This formal model is represented by the combination of assembly feature operations, the assembly model and the evaluation process. A design case study is conducted to verify the applicability of the presented approaches.

A New Software Reliability Framework —— A Extended Cleanroom Model

Cleanroom software engineering has been proven effective in improving software development quality while at the same time increasing reliability. To adapt to large software system development, the paper presents an extended the Cleanroom model, which integrates object-oriented method based on stimulus history, reversed engineering idea, automatic testing and reliability assessment into software development. The paper discusses the architecture and realizing technology of ECM.

The Interaction Effects of the Parameters on Optimization Design in Paper Production Waste Usage on Alkali-Activated Slag with Taguchi Method

The paper investigates the second-order interactions of parameters in an alkali-activated mixture of paper production waste(PPW)and blast furnace slag(BFS)in Taguchi method.The PPW including lime mud(LM)and paper sludge(PS).This paper provides the experimental models to assess the compressive and flexural strength of them at 7-day and 28-day.The results have shown that the second-order interactions between PPW and alkali-activated activator exists in each experimental model,and the significant interactions affect the selection of optimal compositions.Compared with the interactions between the PPW themselves,the interactions between PPW and alkali-activated parameters are the main significant factors affecting its physical properties.In each experimental model,the maximum compressive strength was 47.41 MPa in 7-day and 65.64 MPa in 28-day.Compared with the confirmatory experiments,the deviation of prediction calculated by experimental models was 3.08%and 0.56%,respectively.The maximum flexural strength was 5.74 MPa in 7-day and 5.96 MPa in 28-day;compared with the confirmatory experiments,the deviation of prediction calculated by experimental models was 5.40%and 0.17%.Considering the influence of circular materials,30%of PPW should be a suitable ratio to replace BFS as the raw material of alkali-activated slag(AAS).

Study of Water Injection Efficiency through Modern Geological-Mathematical Models in Guneshly Field

Guneshli is a unique oil field for.its huge oil reserves. Fasila layer is one of the main productive series with more than 3,300 tons of oil production per year. It is an important task to continue efficently develop this object. Development of Fasila was analysed based on geological-mathematical models, production performance was predicted through use of advanced ＂evolution＂ modeling program. In addition, the impact of water injection from deep water Guneshly was identified and relavant proposals were put forward.

Error Analysis of Assembly Linkage of Transport Jig for Large Aircraft Parts

Aiming at the assembly accuracy of a large aircraft transport jig, the effect of component error and the error of work-piece surface on the work-piece position and orientation in the 3-2-1 fixturing scheme is studied with the object pose space description method. The error mapping model between the connecting part of the front frame rack and its support base is modeled using the homogeneous transformation matrix(HTM) method. The probabilistic error is simulated using the Monte Carlo method. The measurement experiment was conducted by the laser tracker to verify the effectiveness of the approach, and the approach has been successfully applied to the production of transport jig.

咸阳市土地利用及生态系统服务价值时空变化

为掌握咸阳市土地利用变化特征及生态系统服务价值变化规律,采用土地利用转移矩阵分析咸阳市土地利用变化,并对其生态系统服务价值进行评估分析,结果显示:(1)土地利用占比由大到小依次为:耕地>水域>林地>建设用地>未利用地;(2)人类活动对土地利用的影响程度在逐渐加深,林地和建设用地的利用程度均呈上升趋势;(3)咸阳市的土地利用变化主要是耕地向建设用地转移以及耕地与林地的互相转移;(4)2003—2021年咸阳市生态系统服务价值增加3.2301亿元,整体呈先增长后减少的趋势;(5)除供给服务价值呈持续减少趋势外,调节服务价值、支持服务价值和文化服务价值均呈先增加后减少趋势。研究结果可为优化土地利用结构和布局,协调土地管理与生态环境关系提供依据。

农产品流通数字化对农村居民生活水平的影响研究

在理论分析的基础上,构建农村居民生活水平和农产品流通数字化水平评价指标体系。基于2013年—2021年我国31个省(区)市的面板数据,采用因子分析法分别测算农村居民生活水平和农产品流通数字化水平数值,并进一步运用固定效应模型分析农产品流通数字化水平对农村居民生活水平的影响。发现农产品流通数字化水平有利于提升农村居民生活水平,在农业发达地区,农产品流通数字化水平对农村居民生活水平的提升作用更强。据此从加强农业欠发达地区农村数字化基础设施建设、提升农民数字素养和加大政府扶持力度三个方面提出相应建议。

河北省农产品国际竞争力评价及影响因素研究

发展农产品贸易,提升农产品国际竞争力对促进河北省农业高质量发展具有重要意义。以2006—2020年河北省农产品生产需求等相关数据为依据,采用熵权法构建农产品国际竞争力综合评价指标体系,研究了河北省农产品国际竞争力水平及发展趋势,并综合运用双钻石模型,从国际国内2个层面探究河北省农产品国际竞争力的影响因素,以期为全省农产品国际竞争力提升提供参考依据。结果表明:河北省农产品国际竞争力呈现稳步增长态势,农产品全球指标与国内指标走势基本一致,规模以上农副食品加工业R&D人员和沿海港口货物吞吐总量对竞争力的影响较大。

关于函数逼近法理论的一点认识

现有教材中常将本质相同的连续函数最佳平方逼近问题、离散数据最小二乘曲线拟合问题分开阐述.本文重新组织现有理论结构给出一般性结论同时也阐述两类问题的区别——最小二乘法思想在空间理论上的统一、同一向量组在不同线性空间中线性无关性表达形式的不同、元素在不同线性空间上内积表达式的差异.最后通过例题说明两类问题求解步骤的统一——连续函数最佳平方逼近也需要“造型”,并通过实例显示同一向量组的线性无关性在不同空间中的具体表现.这种新的知识点组织方式即避免了相同公式的重复性推导,又可使学生通过比较学习避免混淆便于理解.