Application of Integrated Seismic Data Processing and Interpretation to Subtle Reservoir Survey

Nowadays, it becomes very urgent to find remain oil under the oil shortage worldwide.However, most of simple reservoirs have been discovered and those undiscovered are mostly complex structural, stratigraphic and lithologic ones. Summarized in this paper is the integrated seismic processing/interpretation technique established on the basis of pre-stack AVO processing and interpretation.Information feedbacks occurred between the pre-stack and post-stack processes so as to improve the accuracy in utilization of data and avoid pitfalls in seismic attributes. Through the integration of seismic data with geologic data, parameters that were most essential to describing hydrocarbon characteristics were determined and comprehensively appraised, and regularities of reservoir generation and distribution were described so as to accurately appraise reservoirs, delineate favorite traps and pinpoint wells.

Seismic Data Processing and Interpretation on the Loess Plateau, Part1: Seismic Data Processing

Branching river channels and the coexistence of valleys, ridges, hiils, and slopes＇as the result of long-term weathering and erosion form the unique loess topography. The Changqing Geophysical Company, working in these complex conditions, has established a suite of technologies for high-fidelity processing and fine interpretation of seismic data. This article introduces the processes involved in the data processing and interpretation and illustrates the results.

Semantic-based query processing for relational data integration

To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.

Integrated Data Processing Method for GPS and INS Field Test over Rocky Mountain

The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS outputs and the offset of GPS and INS, state equations and observations are designed to perform the calculation and improve the navigation accuracy. An example shows that with the method the reliable navigation parameters have been obtained.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

Challenges and countermeasures of log evaluation in unconventional petroleum exploration and development

To promote adaptation of logging evaluation technologies to the development trend of unconventional oil and gas exploration and development era in China,the current situation and challenges of logging evaluation technologies in China are analyzed systematically.Based on the concept of that demand drives technology development,and referring to the international leading technologies,development strategy of logging evaluation technology in China has been put forward.(1)Deepen petrophysics study:mobile 2 D NMR laboratory analysis technology for full diameter core should be developed,characteristic charts and evaluation standards of different fluid properties,different pore structures and different core exposure times should be established based on longitudinal and traverse relaxation spectra;in-depth digital rock experiment and mathematical and physical simulation research should be carried out to create innovative logging evaluation methods;acoustic and electrical anisotropy experimental analysis technology should be developed,and corresponding logging evaluation methods be innovated.(2)Strengthen target processing of logging data:precise inversion processing technology and sensitive information extraction technology of 2 D NMR logging should be developed to finely describe the micro-pore distribution in tight reservoir and accurately distinguish movable oil,bound oil,and bound water etc.The processing method of 3 D ultra-distance detection acoustic logging should be researched.(3)Develop special logging interpretation and evaluation methods:first,mathematical model for quantitatively describing the saturation distribution law of unconventional oil and gas near source and in source should be created;second,evaluation methods and standards of shale oil and deep shale gas"sweet-spots"with mobile oil content and gas content as key parameter separately should be researched vigorously;third,calculation methods of pore pressure under two high-pressure genetic mechanisms,under-compaction and hydrocarbon charging,should be improved;fourth,evaluation method of formation fracability considering the reservoir geologic and engineering quality,and optimization method of horizontal well fracturing stage and cluster based on comprehensive evaluation of stress barrier and lithologic barrier should be worked out.

Oil-gas reservoir in the Mesozoic strata in the Chaoshan depression,northern South China Sea:a new insight from long off set seismic data

The Chaoshan depression,a Mesozoic basin in the Dongsha sea area,northern South China Sea,is characterized by well-preserved Mesozoic strata,being good conditions for oil-gas preservation,promising good prospects for oil-gas exploration.However,breakthrough in oil-gas exploration in the Mesozoic strata has not been achieved due to less seismic surveys.New long-off set seismic data were processed that acquired with dense grid with single source and single cable.In addition,the data were processed with 3D imaging method and fi ner processing was performed to highlight the target strata.Combining the new imaging result and other geological information,we conducted integrated interpretation and proposed an exploratory well A-1-1 for potential hydrocarbon.The result provides a reliable basis for achieving breakthroughs in oil and gas exploration in the Mesozoic strata in the northern South China Sea.

Investigating Approaches of Data Integrity Preservation for Secure Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) typically use in-network processing to reduce the communication overhead. Due to the fusion of data items sourced at different nodes into a single one during in-network processing, the sanctity of the aggregated data needs to be ensured. Especially, the data integrity of the aggregated result is critical as any malicious update to it can jeopardize not one, but many sensor readings. In this paper, we analyse three different approaches to providing integrity support for SDA in WSNs. The first one is traditional MAC, in which each leaf node and intermediate node share a key with parent (symmetric key). The second is aggregate MAC (AMAC), in which a base station shares a unique key with all the other sensor nodes. The third is homomorphic MAC (Homo MAC) that is purely symmetric key-based approach. These approaches exhibit diverse trade-off in resource consumption and security assumptions. Adding together to that, we also propose a probabilistic and improved variant of homomorphic MAC that improves the security strength for secure data aggregation in WSNs. We carry out simulations in TinyOS environment to experimentally evaluate the impact of each of these on the resource consumption in WSNs.

An Integration Framework for Digital Progressive Die Design and Manufacturing

This paper reports an effort to develop an intelligent integration framework for digital progressive die design and manufacturing. Both data-and process-centric integration functions are provided by the framework as if a special ight-weight PDM/PLM (Product Data Management/Product Lifecycle Management) and WM (Workflow Management) system is embedded in the integrated engineering environment. A flexible integration approach based on the CAD (Computer-Aided Design) framework tenet is employed to rapidly build up the system while the intrinsic characteristics of the process are comprehensively taken into account. Introduction of this integration framework would greatly improve the dynamic performance of the overall progressive die design and manufacturing process.

A Survey of Web Information System and Applications

The fourth international conference on Web information systems and applications （WISA 2007） has received 409 submissions and has accepted 37 papers for publication in this issue. The papers cover broad research areas, including Web mining and data warehouse, Deep Web and Web integration, P2P networks, text processing and information retrieval, as well as Web Services and Web infrastructure. After briefly introducing the WISA conference, the survey outlines the current activities and future trends concerning Web information systems and applications based on the papers accepted for publication.

Deep Learning Applied to Computational Mechanics:A Comprehensive Review,State of the Art,and the Classics

Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.

LÉVY AREA ANALYSIS AND PARAMETER ESTIMATION FOR FOU PROCESSES VIA NON-GEOMETRIC ROUGH PATH THEORY

This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting.To tackle this problem,we propose a novel approach based on rough path theory that allows us to construct pathwise rough path estimators from both continuous and discrete observations of a single path.Our approach is particularly suitable for high-frequency data.To formulate the parameter estimators,we introduce a theory of pathwise Itôintegrals with respect to fractional Brownian motion.By establishing the regularity of fractional Ornstein-Uhlenbeck processes and analyzing the long-term behavior of the associated Lévy area processes,we demonstrate that our estimators are strongly consistent and pathwise stable.Our findings offer a new perspective on estimating the drift parameter matrix for fractional Ornstein-Uhlenbeck processes in multi-dimensional settings,and may have practical implications for fields including finance,economics,and engineering.

智能传感技术在水肥一体系统中的应用研究

以进一步提升水肥一体机系统的作业效率为目标,选取智能传感的监测技术,针对整机的监测控制与信号处理展开应用设计研究。考虑水肥一体机过程作业肥液融合的均匀性及系统各模块之间的协同性功能实现,结合微分补偿的传感数据算法处理方法,进行智能传感的水肥一体机架构布局,并匹配可执行的软件控制程序及硬件实施结构,进行实地传感应用监测与灌施控制作业试验。结果表明:水肥一体机系统的数据监测准确率可达95.25%,系统故障率相对降低3.79%,监测数据准确及时,能够确保系统各环节指令得到有效的调整与反馈,进而保证灌施土壤的含水稳定率相对提升7.87%,对于作物的稳定生长与产量提升有重要的参考价值。

基于Profibus-DP总线控制的机电一体化系统

以机电一体化控制系统为例介绍了Profibus-DP现场总线在机电一体化中的应用,重点阐述了机电一体化系统各站点的功能、Profibus-DP总线的控制方案、控制特点以及控制的技术实现原理。整个系统的控制器采用Siemens的S7-300作为主站,9个S7-200和变频器作为从站,监控整条生产线的生产过程,通过Profibus-DP总线实现了对整个系统的集中控制,又能分散控制各底层设备,从而实现集中与分布式相结合的灵活控制模式。该方案的实施提高了整个控制系统运行的可靠性,实现了多速控制。

GeoFrame Petrophysics软件包的开发与应用

在对 Geo Frame petrophysics软件包的开发与应用过程中 ,结合大庆地区地质情况 ,优选了补偿中子、岩性密度、自然伽马等校正模块 ,建立了 7种岩性的深层岩性库。同时建立了适应于大庆油田深层的处理解释模型。实际投产处理 175口井的测井资料 ,并与岩心资料进行了对比分析 ,精度达到了生产要求。

Digital management technology and its application to investment casting enterprises

With the advent of Industry 4.0, more and more investment casting enterprises are implementing production manufacturing systems, especially in the last two years. This paper summarizes three new common requirements of the digital management aspect in precision casting enterprises, and puts forward three corresponding techniques. They are: the production process tracking card technology based on the main-sub card mode; the workshop site production process processing technology based on the barcode; and the equipment data integration technology. Then, this paper discusses in detail the principle, application and effect of these technologies; to provide the reference for enterprises to move towards digital casting and intelligent casting.

Key Techniques for the Development of Web-Based PDM System

Some key techniques for the development of web-based product data management （PDM） system are introduced. The four-tiered B/S architecture of a PDM system-BITPDM is introduced first, followed by its design and implementation, including virtual data vault, flexible coding system, document management, product structure and configuration management, workflow/process and product maturity management. BITPDM can facilitate the activities from new product introduction phase to manufacturing, and manage the product data andtheir dynamic changing history. Based on Microsoft. NET, XML, web service and SOAP techniques, BITPDM realizes the integration and efficient management of product information.

Optimizing Query Results Integration Process Using an Extended Fuzzy C-Means Algorithm

Cleaning duplicate data is a major problem that persists even though many works have been done to solve it, due to the exponential growth of data amount treated and the necessity to use scalable and speed algorithms. This problem depends on the type and quality of data, and differs according to the volume of data set manipulated. In this paper we are going to introduce a novel framework based on extended fuzzy C-means algorithm by using topic ontology. This work aims to improve the OLAP querying process over heterogeneous data warehouses that contain big data sets, by improving query results integration, eliminating redundancies by using the extended classification algorithm, and measuring the loss of information.

Application of FPGA in Process Tomography Systems

This paper will provide some insights on the application of Field Programmable Gate Array (FPGA) in process tomography. The focus of this paper will be to investigate the performance of the technology with respect to various tomography systems and comparison to other similar technologies including the Application Specific Integrated Circuit (ASIC), Graphics Processing Unit (GPU) and the microcontroller. Fundamentally, the FPGA is primarily used in the Data Acquisition System (DAQ) due to its better performance and better trade-off as compared to competitor technologies. However, the drawback of using FPGA is that it is relatively more expensive.

应用生成对抗网络的地震数据重建和去噪一体化方法

在实际采集过程中,受地形条件和人为因素的影响,地震数据不仅在空间上会出现采样不足或不规则的情况,而且会混入噪声,不利于后续地震数据的处理和解释。通常将重建与去噪分为两个阶段处理,这样往往会引入额外的误差。为此,文中提出了一种基于条件韦氏生成对抗网络(cWGAN)的地震数据重建去噪一体化方法,该方法研究的重点是在缺失道和噪声的混合干扰下,准确提取地震数据的有效特征。首先,以U-Net模型为基本网络结构来构建生成器模型,分级提取地震数据同相轴特征;在判别器模型中引入条件约束,引导生成器优化梯度方向。其次,建立重建和去噪误差描述模型,该模型设计了一体化损失函数,可以兼顾重建与去噪两方面的处理任务。最后,经过合成数据和实际数据测试,证明文中所提的网络模型恢复的地震数据信噪比更高且具有较强鲁棒性。