基于CBR RBR的推理机在机械比能分析模型中的研究  

Research on Inference Engine in Mechanical Specific Energy Model Based on CBR and RBR

作　　者：李龙[1] 黄霞 金铄 LI Long;HUANG Xia;JIN Shuo(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318)

机构地区：[1]东北石油大学计算机与信息技术学院,大庆163318

出　　处：《计算机与数字工程》2024年第2期622-625,共4页Computer & Digital Engineering

摘　　要：为了解决录井储层物性评价时由于环境复杂,人员耗费周期长、缺少对数据的全面分析与利用、机械比能分析模型的不确定性的问题,引入知识库的概念,利用CBR RBR推理决策,结合录井专业知识,针对不同情况下的勘探情况,分别建立案例库和规则库,利用混合的推理方法,检索出与当前情况相似度较高的案例库中的案例,并进行推理得出高效的机械比能模型,使之取代人工选择模型,节约人力资源,利用知识驱动概念使模型更加高效,可根据现场人员的需求设计推理结构,可以提高模型的效率,极大地满足储层物性评价需要。In order to solve the problems of complex environment,long personnel time-consuming period,lack of comprehensive analysis and utilization of data,and uncertainty of mechanical specific energy analysis model when evaluating the physical properties of mud logging reservoirs,the concept of knowledge base is introduced and CBR RBR is used for inferring and decision-making.Combining logging expertise,a case database and a rule database are established for different exploration situations,this hybrid inference method is used to retrieve cases in the case database that are more similar to the current situation.An efficient mechanical specific energy model is developed to replace the manual selection model,human resources are saved,and knowledge-driven concepts to make the model more efficient.The inference structure can be designed according to the needs of on-site personnel,and the efficiency of the model can be improved to greatly meet the needs of reservoir physical property evaluation.

关 键 词：CBR RBR 知识驱动 知识库 推理机 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]