由于复杂结构井钻井过程存在大量复杂和不确定性因素,建立精确的数学模型来解决钻井决策问题十分困难,提出了基于实例推理技术构建钻井过程智能决策支持系统。在传统的实例相似度计算模型基础上,针对不同类型的属性设计了一个相似度综合计算模型,有效地解决信息的不精确性。详细描述了系统的总体结构、实例表示与组织以及推理模型的设计。
Considering the difficulty in establishing accurate math models for solving decision problems due to a great number of complex and uncertain factors in well drilling, an intelligent decision support system based on case reasoning for drilling well of complex architecture is put forward. A similarity synthetic computing model for different types of attributes is designed based on traditional computing models. The model can process effectively imprecise information. The architecture, the case expression and organization, and the reasoning model of the system are expounded in detail.