Analysis on Cloud Data Service Platform for Digital Oilfieldsdline.info/fpaper/jdim/v14i6/jdimv14i6_7.pdf · the application of new technologies and industrialization practices. Therefore,

Journal of Digital Information Management Volume 14 Number 6 December 2016 413

Analysis on Cloud Data Service Platform for Digital Oilfields

ZHU Zheng-Ping1*, PAN Ren-Fang1, CHEN Zhe2, LI Gong-Quan1, ZHENG Guo-Sheng3

1College of Earth Science Digital Oilfield Research Center, Yangtze University,Wuhan ,430100 , China2Information Center of Petrochina Dagang Oilfield Company, Tianjing, 300280, China3Department of Engineering Sciences, NEUT, Yong-in, Kyunggi-do 907, Korea*Corresponding Author, email: zzp2015@ yangtzeu.edu.cn

Journal of DigitalInformation Management

ABSTRACT: Digital oilfields are highly complicatedinformation systems, and their size increases as theenterprise scale expands. Cloud computing as a newservice model has been gradually extended from thetraditional IT industry to traditional industrial domains, butresearch on and the application of the digital oilfield cloudplatform remain lacking. By introducing the reference frameof the integrated platform of oil enterprises at home andabroad, we adopt the design method of the integratedarchitecture of enterprises and the metadata-basedobject-oriented development model based on the designconcept of cloud computing to identify efficient andinexpensive information platform solutions. Research isconducted on a cloud data service management systemfor digital oilfields. The overall structure of the cloudplatform for digital oilfields is divided into five layers ofinfrastructure, data resources, functional services,applications, and terminal access and into two supportsubsystems, namely, cloud information specifications andstandards and cloud service management platform. Thecloud data service platform is generalized as anarchitecture with “a center, three layers, two buses, andtwo sub-functional systems.” Results show that the clouddata management system performs the four core functionsof model, data bus, data service bus, and data qualitycontrol management. Furthermore, integrating cloudcomputing into the transformation and upgrading oftraditional industries is feasible and applicable to otherrelated fields.

Subject Categories and DescriptorsI.2.10[Cloud Technology]: Cloud Data Analysis; I. 4.10 [CloudData]

General TermsDigital oilfields, Cloud Platform

Keywords: Cloud computing, Exploration and production,Central main database, Data bus, Data service

Received: 8 July 2016, Revised: 28 August 2016, Accepted: 10September 2016

1. Introduction

Digital oilfields (DOFs) originated from Digital Earth; theyconstitute the most important branch of Digital Earth andthe advanced stage of information-based development ofoilfields. With the development of information technology,advanced information technologies, such as cloudcomputing and service-oriented architecture (SOA) [1,2],have gradually emerged. Given their advanced designcharacteristics of being “loosely coupled” and “ready touse,” these technologies can provide information resourcesto users in the form of services. These technologies havepenetrated into the construction of information systemsin different industries because they can effectively copewith the ever-expanding system size. Meanwhile, the cloudplatform has also been gradually extended to various

414 Journal of Digital Information Management Volume 14 Number 6 Decemober 2016

industrial fields from the traditional IT industry.

To increase their competitiveness, oilfield companiesconstantly search for highly efficient exploration techniquesand methods. They attempt to perform dynamicmonitoring, analysis, and decision making during theprocesses of drilling, reservoir evaluation, and oil and gasproduction to improve the success rate of oil and gasexploration and reduce the operating costs of such anexploration. Information management plays a critical rolein achieving efficient data management.

China’s oil enterprises have achieved useful results in theconstruction of an integrated information platform; however,compared with those in foreign countries, these enterprisesare relatively backward and still immature with regard tothe application of new technologies and industrializationpractices. Therefore, we propose an overall solution forthe cloud data service platform for digital oilfields accordingto the developmental status of China by analyzing thebasic theory of cloud computing and by referring to theinformation integration platform at home and abroad. Theobjective is to enhance the level of data management andapplication of China’s oilfield enterprise and further improvethe utilization of digital oilfields.

2. State of The Art

The concept of cloud computing is widely recognized andhas become a popular topic in the IT industry and otherindustries. The concept is widely applied in many domains,such as land resource management [3], machinerymanufacturing [4], agricultural and rural informationmanagement [5], and railway information sharing platforms[6].

The oil industry is one of the industries characterized bythe most intensive applications of information technology.With the rapid development of information technology,digital oilfields have elicited attention from global petroleumcompanies, such as British Petroleum (BP), Shell,Chevron, Schlumberger, and Halliburton [11]. These newtechnologies have been integrated into the oil industry.Nevertheless, the application of the latest informationtechnology in the oil industry lags behind that in the ITfield. For example, in the oil industry, cloud computingremains in its infancy stage. Existing research results oncombined cloud computing and petroleum technologyremain scarce.

Robert from the University of Queensland in Australia [12]adopted the deployment model of private cloud or theHybrid Cloud to meet the challenges faced by theupstream business of oil and gas. These challengesinclude data security and big data analysis. Robertstressed that additional applications based on cloudcomputing should be provided to the oil industry by otherindustries. With regard to the serious challenge posed bythe large amounts of data generated by integratedautomation and communication, Oladele et al. of Baker

Hughes [13] proposed a complete cloud data managementsystem and described the development status and trendsof several available cloud data management techniques.

In China, Peng Ying et al. [14] proposed a data storageand service platform for distributed oilfield geophysicalprospecting. The platform is based on cloud computingand aims to solve the problem of information sharing andreuse difficulties that are prevalent in the hardware andsoftware platforms of oil exploration units. Li Songtao in2013 [15] proposed four stages for oil group enterprisesto implement cloud computing. The four stages areinfrastructure as service, software as service, platform asservice and service infusion. Songtao pointed out theobjectives and tasks of each stage. In the same year,Hou Xiaofeng [16] proposed the basic model for thestructure design of cloud computing suitable for large-scale state-owned enterprises, and he takes the planningand structure design of cloud computing of CNOOC forexample, and establishes the basis for the standards ofcloud computing of CNOOC and communication modelsand universal language for cloud computing using thereference frame of cloud computing.

These studies have shown that regardless of location,the application of cloud computing in the oil industryremains in the theoretical research stage. No scholar hasconducted in-depth research on this subject. To this end,we propose a theoretical framework for digital oilfields byreferring to the actual development status of China’s oilenterprises and by incorporating advanced applicationsabroad. We investigated the data integration platform toexert certain pioneering effects on the construction of cloudcomputing in the area of digital oilfields.

The rest of this paper is organized as follows. Section 3presents the investigation and survey on the architectureof digital oilfields at home and abroad, the architecturedesign of the cloud platform for digital oilfields, and thearchitecture of the service platform of cloud data for digitaloilfields. Section 4 presents the design and realization ofthe service management system of cloud data. Section 5provides the conclusions.

3. Methodology

3.1 Analysis of the architecture of digital oilfieldsTo design an information integration platform for digitaloilfields that fits the development of China’s oilfieldenterprise and is in par with advanced foreign technology,we investigated and generalized the typical architecturesof information integration platforms at home and abroad.The information-based construction of foreign oilfieldenterprises relies mainly on several large oilfield servicecompanies, whereas China’s oilfield enterprise mainlyadopts independent information-based construction. Weselected two typical application examples, namely,Halliburton and Xinjiang Oilfield Company of ChinaPetroleum.


3.1.1 Examples of architectureHalliburton believes that the direction of information-baseddevelopment is toward “digital assets,” that is, a real-timecollaboration environment that models, observes, andmaximizes the benefits of assets. Based on the originalapplication software product developed for differentprofessions, They designed and constructed a newDecisionSpace enterprise-level information platform (seeFigure 1) by integrating advanced cloud computing andSOA. The platform contains four layers: data management(data source layer), integration (data integration andservice), application (function integration), and informationecosystem.

Xinjiang Oilfield leads the information trend among oilfieldenterprises at home. Since 1993, it has been conductinglarge-scale data collection and sorting. In 2002, XinjiangOilfield formally proposed the standards of “digital oilfield.”In 2008, it realized desktop-based documents and data,desktop-based business and work, and desktop-basedoilfields in Xinjiang, with the applications of informationsystem covering all aspects of oilfield exploration anddevelopment. In 2009, the “Digital Xinjiang Oilfield Website”was established. On this basis, Xinjiang Oilfield designedthe overall planning and system architecture (Figure 2)for the development of digital oilfields. The systemarchitecture can be summarized as having three layers,two platforms, and one specification.

3.1.2 Comparative analysis of architectureWith regard to the architecture of digital oilfields, althoughexperts and related institutions at home and abroad haveprovided different solutions, the overall technical ideas arebasically similar and can be generalized into the followingtwo aspects.

(1) The data layer is the core layer of the entire platform.The data layers always serve as the core and foundationlayer of platforms, and they include at least two layers of

Figure 1. Framework of the DecisionSpace enterprise-level information platform

data source and data integration. The layer of data sourceis mainly responsible for on-site data collection, storage,and management, and the layer of data integrationtransfers the data to the upper application system in aunified form.

(2) A platform has a three-layer attribute. Throughdevelopment, software systems have evolved into a three-element system and structure that includes database,function, and application layers from the traditional two-element structure. A digital oilfield is also an applicationsystem to a certain extent, and it is a very large applicationsystem that involves many fields.

Comparison of the architectures of digital oilfields at homeand abroad indicates that the difference mainly lies in thefollowing two aspects.

(1) Application of new technologies. Foreign oil servicecompanies are superior to Chinese oil companies in termsof application of new technologies. Halliburton Companymainly uses the technical concept of SOA, and theyincorporate technical ideas of cloud computing in thedelivery and use of application software. Moreover, theytook the lead and put forward the concept of “ecologicalsoftware system” in the oil industry. For information-basedconstruction, China’s oilfield enterprise mainly usestraditional information technologies.

(2) Focus and level of research. Foreign oil companieshave formed a very complete information integrationplatform ranging from data acquisition, storage, andintegration to management, and they are heading towarda higher level development, that is, enterprise informationintegration. Meanwhile, China’s oilfield enterprise isconstrained by its management system and mainly adoptsthe model of independent construction in the domain ofdigital oilfields. Currently, studies focus on database andmulti-source heterogeneous data integration in an attempt


Figure 2. Architecture of the digital oilfield of Xinjiang Oilfield Company

to build a truly integrated data platform.

3.2 Architecture of the cloud platform of digitaloilfieldsAfter investigating the main problems in the constructionof digital oilfields in China’s oilfield enterprise and typicalarchitecture references, we created a structural diagramof a cloud digital oilfield(Figure 3).

The architecture can be divided into infrastructure, dataresource, functional service, application, and terminalaccess layers and into two support subsystems for digitaloilfields, that is, cloud information specifications andstandards and cloud service management platform.

(1) Infrastructure layer. This layer is mainly composed oftwo parts. One part comprises the necessary hardwareinfrastructures that support the operation of a digital oilfield, such as computing servers, storage, and networking.

The other part is the virtual resource pool, which is mainlycomposed of the operating system, virtual machines, andvirtualization tools. It aims to integrate the distributedhardware for deployment management into a unified poolof resources and output them in the form of service. Sucha system effectively separates applications and physicalresources and thoroughly eliminates the complexity andindependence of underlying physical resources. Thus,resource utilization efficiency is improved.

(2) Data resource layer. This layer is responsible for datastorage and management and provides high-performanceand high-quality data resource services. To further improvethe supporting effect of data on the application systemand increase data efficiency, we developed a three-layerstructure according to the above architecture investigation.The structure is composed of data source, central maindatabase, and data application layers.

(3) Functional service layer. This is the connection layer


of the cloud platform. For the lower layers, it is responsiblefor managing the infrastructure resource pool and dataresources. For the higher layers, it supports varioussoftware and modules of upper applications, which mainlyinclude public infrastructure, professional application, dataservice interface, and access function components of theinfrastructure layer. It also provides supporting service,an operation management environment, and functionalcomponents to the upper application system.

(4) Application layer. It directly faces end users andprovides a high-quality software operating environment andexperience to researchers. Users merely need to log onthe Internet network and submit an application to themanagement center of the cloud platform. Afterward, theycan obtain all available application software serviceswithout needing to purchase, deploy, or manage these

applications. According to the research needs for digitaloilfields and the deployment pattern for existing software,the application system mainly includes an auxiliarydecision-making system, a production and runningmanagement system, and a collaborative researchenvironment.

(5) Terminal access layer. This layer is the closest to theuser. It contains the method and tools with which usersvisit and obtain cloud platform resources. It mainlyincludes portals, mobile terminals, desktop applications,and virtual desktops.

(6) Cloud service management platform. It guarantees theavailability, reliability, and security of platform operation,and it mainly includes service quality control, securitymanagement, and service process management.

Figure 3. Framework of the cloud platform of a digital oilfield


3.3 Architecture of the cloud data service platformof digital oilfieldsWith data as the main research objective and main line,the cloud data service platform for digital oilfields is asub-platform of digital oilfield cloud platform and anexample of a cloud data oilfield. For the design process,based on the cloud platform for digital oilfields, we focusedon the specific refinement processes of the data resourceand functional component layers to realize the design ofthe service platform of cloud data for digital oilfields (alsoknown as cloud data service platform, Figure 4).

3.3.1 General structural designBased on the abovementioned architecture of the clouddigital oilfield and with the aim of providing cloud dataservices, further refinement was made for the dataresource, functional component, and application layersand the cloud data service architecture with “a center,three layers, two buses, and two sub-functional systems.”The center indicates the presence of one central maindatabase level. The three layers are data source, centralmain database, and data application. The two buses aredata integration and data service. The two sub-functional

Figure 4. Framework of the cloud data service of a digital oilfield

systems are data quality control and standard and clouddata service management.

3.3.2 Analysis of the hierarchical model ofarchitecture


(1) Data source layer

The data source layer supports the collection,management, and application of all types of professionaldata from the aspects of the exploration and productionsector, oil company management, oil extraction plant, andprofessional services company. It uploads the data to thecentral main database as the data source. According tobusiness needs, data sources can be divided intoprofessional, production, and real-time data. Accordingto data type, data sources can be divided into raw, results,and management data. From the perspective of dataintegration time, data sources can be divided into historicaland normalized data. From the perspective of data storagemethods, data sources can be divided into Oracle, SQLserver, Access, Excel, and text files. From the perspectiveof the nature of data, data sources can be divided intostatic, dynamic, and real-time data.

(2) Central main database level

In accordance with the protection strategy for data assets,to safely, correctly, and completely store and manage alltypes of professional raw data and the results of the datafor exploration and development, the layer should havethe following characteristics: unique data source, absenceof data redundancy, it is the main data source of theapplication system, having a standardized regular data-updating mechanism, having a high degree of data sharing,and can give full play to the potential value of data assets.Moreover, it should be able to realize reasonable storagesettings of the database and reduce data maintenancecosts.

Given that many professions are involved in upstream oilindustry research, management of data needs iscomplicated. Different storing methods and systemstructures are involved. Therefore, the central maindatabase for digital oilfields is not a database at thephysical level, but a system composed of multiple physicaldatabases characterized by a unified data model andlogical integration. For this reason, through acomprehensive analysis, we developed a constructionprogram of the central main database that is composedof a large database, a central main database of explorationand development, and a research results database. Thesethree databases form an integrated central main databaseunder uniform management through shared main data.

(3) Data application level

The central main database manages the data to supportall types of comprehensive applications in the upperlayers. According to the application type, it can be dividedinto auxiliary decision making, development, productionand operation management, and exploration anddevelopment of integrated research. Aside from providingdirect data support for these integrated researchapplications, according to different types of researchneeds, the central main database also provides a model

of re-organization in different ways based on applicationcharacteristics.

(4) Data integration bus

The data integration bus is a means of technical realizationprovided for the data from all types of data sources to besubmitted to the central main database. To shield thedifference between different data sources from the centralmain database, a unified data integration bus needs to bebuilt between the data source and central main databaseto create a path for different data flowing from differentprofessional data sources to the data center. For the dataintegration bus, aside from analyzing the existingprofessional database construction, we need to establisha universal data extraction, transfer, and loading (ETL)mechanism and conduct a corresponding data qualityinspection based on unified norms and standards of thecentral main database to keep records of problem dataand provide feedback. For historical data, the method ofone-time migration is used to perform the entire migration.For normalized data, according to different updatefrequencies, different ETL strategies are developed, andcontinuous data update and synchronization are realizedautomatically or manually.

(5) Data service bus

The data of the central main database are stored andmanaged in accordance with the storage requirementsand standard specifications of the data center. However,at the application level, given that the purposes ofapplications differ, the means to use these data also differ;therefore, a unified data service system is required toprevent the difference at the application level from affectingthe central main database.

For terminal data users, a data organization and displaymode that suits the habits of users is required. Thus, acustomized mechanism must be built for users to quicklyorganize data so that it can support different user habitsand business expansion.

For researchers specializing in comprehensive subjects,a mechanism for rapid data exchange is necessary totransfer and load the data of the central main database tothe application system in a format approved by theintegrated application software. Consequently, fast andseamless connection between the central main databaseand the integrated application software system can berealized.

For software system developers, a database-independentdata service mechanism must be provided. The relativelymature one at present is WebService, and the integratedbus in the data center needs an underlying data packagethat supports WebService to prevent the developer fromimproperly using the underlying database and to ensurethe security of the database.


4. Result Analysis And Discussion

Constructing a service platform of cloud data for digitaloilfields involves a large amount of workload. With thestudies conducted by the oilfield enterprise, the dataarchitecture of the data integration platform would continue

to extend and expand, which poses a great challenge todatabase management, operation, and maintenance. Tothis end, in this study, based on metadata managementtheory, we preliminarily achieved the design andimplementation of a functional system for cloud dataservice and management, as shown in Figure 5.

Figure 5. Diagram of the service management of cloud data

Figure 6. Model admin interface diagram


The system is a powerful tool to maintain the vitality ofthe central main database, and it adopts a thin client B/Smode design. According to the main existing problems,the system performs four main functions: modelmanagement, data bus management, data service busmanagement and data quality control systemmanagement. The purposes are to track resourcedevelopment changes, provide statistics on data storage,establish a meta-model database, track model changes,publish a data dictionary, and build an exploration anddevelopment data cloud platform that integrates modelmetadata management, data integration, datamanagement, and data service applications. The mainperformance is as follows:

(1) Automatically upgraded model management(Figure6, it is generated by application of Chinese version).Users can query and browse professional and centraldatabases. The functions include database instanceand upgrade and downgrade of the main database.Therefore, the life cycle of the central main databasecan be extended.

(2) Automatical ly integrated data distr ibut ionmanagement(Figure 7, it is generated by application ofChinese version). Automatic incremental integrationmanagement is conducted for data from differentprofessional databases flowing to the central maindatabase.

Figure 7. Data integration interface realtime monitor display

Figure 8. Interface management diagram of data service

(3) “One-stop” data service management(Figure 8, it isgenerated by application of Chinese version). Withcustomizable data service applications, it can provide one-stop data service for application systems or professionalsoftware of exploration and development.

5. Conclusion

To establish highly efficient and inexpensively integratedinformation platform solutions, we adopted the designmethod of integrated architecture of enterprises and the


metadata-based object-oriented development model basedon the design concept of cloud computing. We conductedresearch on the cloud data service management systemfor digital oilfields. The following conclusions were obtained.

(1) Constrained by its management system, China’s oilfieldenterprises need to construct a genuine informationintegration platform. With its advanced “loose coupling”and “ready-to-use” design concept, cloud computing canrealize highly effective management of oilfield informationand enhance the competitiveness of enterprises.

(2) Data are an important carrier of oilfield information,and the cloud data service platform is a sub-platform ofthe cloud data service platform. It is also an example ofcloud data oilfield, and it can be generalized as anarchitecture containing “a center, three layers, two buses,and two sub-functional systems.”

To examine the main business needs of oil and gasexploration and development, we specifically investigatedthe architecture of the cloud data service platform for digitaloilfields. However, we only preliminarily realized the designof a management system. The scope of data coverageand application functions re quire further in-depth study.

References

[1]Ye, Y., Ying, S., Li, W.Z., Zhang, T. (2005). Researchof SOA and Its System Building. Application Research ofComputers, 22 (2) 32-34.

[2]Gorder, P. F(2008). Coming soon: Research in a cloud.Computing in Science & Engineering, 10 (6) 6-10.

[3] Fang, L., Yao, S., Liu, T., Liu, R. (2010). A CloudComputing Application in Land Resources InformationManagement. In: International Conference on Grid & CloudComputing, p. 388-393. Nanjing, China: IEEE ComputerSociety, November. 2010.

[4] Ji, H., Yang, Q. J., Han, X. M.(2012). EnterpriseProduct Platform Services in Cloud Manufacturing.Development ÿ Innovation of Machinery ÿ ElectricalProducts, 25(3)30-32.

[5] Chen, M. K., Wang, J. L., Lu,Z. Y. Niu, Y.(2011).Research on Agriculture Information Resources SharingSystem Construction Based on Cloud Computing.Agricutre Network Informaiton, 2011 (4) 5-7.

[6] Zhang, L. Y., Shi, T. Y., Liu, C. H., Zhang, W. J.(2013).Research on railway information sharing platformframework and key technology based on Cloud Computing.

In: The eighth China Intelligent Transportation AnnualMeting, p. 818-823. Hefei, China: Intelligent TransportationSociety, September. 2013.

[7] Edwards, T., Saunders, M., Moore-Cernoch, K(2006).Advanced Collaborative Environments in BP. In: IntelligentEnergy Conference and Exhibition, SPE-100113-MS.Amsterdam, The Netherlands: Society of PetroleumEngineers, April 2006.

[8] Knoppe, R., Holloway, S(2008). The Application ofKnowledge and Continuous Learning to the Implementationof Collaborative Work Environments at Shell. In: IntelligentEnergy Conference and Exhibition, SPE-112060-MS.Amsterdam, The Netherlands: Society of PetroleumEngineers, February. 2008.

[9] Crompton, J., Gilman, H (2011). The future of integratedoperations. SPE Economics & Management, 3(1) 45-51

[10]Matthews, W., Ronan, D (2008). Lessons Learned:Design and Use of Schlumberger’s Newest Energy Center.In: Intelligent Energy Conference and Exhibition, SPE-112198-MS. Amsterdam, The Netherlands: Society ofPetroleum Engineers, February. 2008.

[11] Anthony, E. P., Al-Enezi, B. A., Al-Mufarej, M.,Moricca, G., Saputelli, L. A., Kain, J., et al. (2013). ValueGenerated Through Automated Workflows Using DigitalOilfield Concepts - Case Study. In: SPE Kuwait Oil andGas Show and Conference, SPE-167327-MS. Kuwait City,Kuwait: Society of Petroleum Engineers, October 2013.

[12] Perrons, R. K., Hems, A. (2012). Public Private orHybrid? What the Upstream Oil & Gas Industry Can Learnfrom Other Sectors about “the Cloud”. In: Abu DhabiInternational Petroleum Conference and Exhibition, SPE-161993-MS. Abu Dhabi, UAE: Society of PetroleumEngineers, November 2012.

[13] Bello, O., Srivastava, D., Smith, D. (2014). Cloud-based data management in oil and gas fields: advanceschallenges and opportunties. Genetics in Medicine, 15(2)1685-1692.

[14] Pen,Y., Wan,J. H., Wu,L.(2011). Distributed oilfieldgeophysical data storage and service platform based onCloud Computing .Computer Research and Development,48 (s1) 224-228.

[15] Li, S.T.(2013). Cloud computing implementation routeof oil group enterprises .Office automation, 6 (3) 18-22.

[16] Hou, X. F., Teng, T.(2013). Application of cloudcomputing reference architecture in the informationtechnology of central enterprises, Information TechnologyStandards, 2013 (3) 26-31.

Documents

Analysis on Cloud Data Service Platform for Digital Oilfieldsdline.info/fpaper/jdim/v14i6/jdimv14i6_7.pdf · the application of new technologies and industrialization practices. Therefore,