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At present, the dynamic analysis in oilfield development is mainly performed by manual work, which is time-consuming, needing a long time period to prepare the data needed. The software used before is based on the ways of statistics and comparison. Artificial intelligence technologies have been applied in various areas, such as distribution of residual oil, recognition of indicator card of pumping wells, logging data analysis, and so on. But it is seldom used in the field of analysis on well array. With the oilfield developing, the artificial intelligence, decision-making technologies are needed to aid the technical staff to carry out the dynamic analysis.Enterprise data warehouse is built on the basis of the existing operation system of the enterprise. The information sorted and regrouped is supplied to the relative administrative decision staff. The oil field development data warehouse is built on the basis of metadata, many standard dimensional tables are built, such as date (year, season, month, ten days, week, day, and so on), well pattern (old well, first batch adjusting well, extension wells, and so on), factory and team, well station (combination station, transfer station and metering room), block (oilfield, block, cell, sub block, and so on). And there are other types of dimensions, such as process, oil production methods, reasons for well shut in, and so on. The data can be browsed according to the dimensional tables from various angles when correlating these dimension tables and the real tables. The data model used to analyze on line the oilfield development is built. The model stores the complex tables in the form of multi-dimensions, and basic tables in the form of relation tables. The online analyzer is connected with the data warehouse through the interface to get the data in the complex tables, to perform the processes of slice up, rotation, digging, and so on.The data warehouse is managed with the idea of metadata management, to maintain and manage unitedly the data of oilfield development and the data correlating to the computer program. The content design, structure design, code design and the program design of the metadata are carried out. The independent metadata management tool is programmed. The data acquisition, check and conformity, and so on are achieved. The main theory is that all the resources are managed and maintained unitedly, including the data and standard tables of various types on different servers.Using CORBA distribution technology, the process of data extraction and preprocess are broken into several remote service objects which are distributed to various servers. Users can run the query program on the browser to call the relative functions of the remote objects to get the service. The request for multi-service objects is implemented with multithread mechanism under the management of the thread manager. Relative data from several remote object servers can be extracted and processed simultaneously. Data analysis on well array and data query on the information of single well relative to oilfield development can be achieved. The data include history of well, processing, indicator diagram, structure of down hole pipes, connected graph, fluid production, oil production, water injection, curve of flowing pressure changing, and so on.In this project, the application of the distribution object technology in the database of oilfield development is studied using CORBA distribution object technology. Based on the oilfield data storage characteristic of decentralization, the maintenance, query and data exchange of the remote data distributed on various servers in the way of Web browser are achieved by taking advantage of the distribution object technology of improving the data utilization efficiency and the degree of data share, which facilitates the oilfield development technical staff greatly. Using the Web browser to process the remote data and exchange the data in the heterogeneous database, the bad effect caused by the diversity of the client environment to the oilfield development data application is solved effectively. Because of the choosing of Web browser form, there is no need for the client machine to configure the data access environment, so as to save the cost of software maintenance, diminish the bad effect caused by the decentralization of the oilfield data to oilfield development.The system provides the technical staff a fast and efficient production analyzer, and promotes the database construction greatly. According to the difficulty of dynamic analysis on well array and the complexity of relative data, the data warehouse, artificial neural network and the decision-making technology are applied to construct the distributed architecture of well array dynamic analysis, to analyze the change of well output, which facilitates the oilfield development work and makes contribution to the sustainable development of oilfield.
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