Production Exploration Wells Expert System Design And Implementation

With the development of computer software technology and the maturity of artificial intelligence (AI) theory, developing the application of expert system with practical value has increasingly become the main area of AI application research. In the process of well drilling, it is difficult for researchers to find relevant information in so many counted parameters to deal with the decisions.Artificial intelligence is a rapidly developing disciplines, it is an important research direction in computer science and technology. The basic principle is looking the computer as the tool, make the solution of the problem into a model and algorithm, and formulate corresponding software, so that the computer can simulate and realize the human intelligence.The expert system in artificial intelligence is to sum up the experience of domain experts into the rules, and use the experience as rule to diagnose faults. Expert system is made up of the knowledge base, inference engine, knowledge acquisition part, man-machine interface; explain mechanisms and the global database etc.The diagnosis process is fast and simple. It can based on the data, information and facts provided by user, using the expert experience or knowledge system which has been stored in the system to reason and judge, and finally gives the result and the credibility of the result, which helps customers make decision.So, the rule based decision expert system takes well drilling as an example, adopts the methods of production knowledge presentation, bases on the data of oil well, stores the experience and knowledge of experts into knowledge base, gives reasonable proposal by efficient reasoning and then improves the efficiency of the project.The knowledge base and the reasoning machine are the cores of the system. In this thesis, the production rules are united by rule elements in the knowledge base and the reasoning machine adopts the combine of matching and activating technology, positive reasoning technology and heuristically searches technology. The system also realizes the explanation function to trace the reasoning process, the function of calculating CF and the function of adding rules. This thesis is to design a reasonable knowledge base and a efficient judging mechanism, and to achieve a highly efficient decision-making expert system. This thesis uses VC and SQL database to realize production expert system. Specific include: Constructing the rational knowledge base deposit rule, design high efficiency reasoning machine to match facts and retrieval, the realization of the track record of reasoning, rules of explaining uncertainty reasoning and functions and so on. Users can through selecting parameter to get the reasoning result, through inputting facts reliability to get calculating conclusion credibility. The clear reasoning process can respond to user explanation request. Experts in the field can add rules through the man-machine interface, so knowledge extensibility and maintainability is very good.