Design And Implementation Of Rservoir Physical Property Mapping System On Ontology

In petroleum exploration and development,reservoir physical properties refer to important parameters that can reflect the physical and chemical properties of the geological layers in which oil and gas reservoirs are located.Comprehensive mapping of reservoir physical parameters through data graphical methods,fully exploring the value of reservoir physical parameters,is of great significance for achieving more efficient evaluation of reservoir oil storage capacity,productivity,and development difficulties.Traditional cartographic software has a single form,low degree of automation,and is difficult to maintain and expand.It cannot effectively improve business efficiency and improve business processes.In response to the above questions,this paper introduces the concept of ontology into the field of reservoir physical property mapping,uses ontology to model domain knowledge,and ultimately designs and implements a reservoir physical property mapping system.The main research results are as follows:1.Aiming at the sharing and standardization of knowledge data in reservoir physical property mapping,this paper proposes to use ontology technology to standardize the expression and modeling of reservoir physical property mapping domain knowledge.Firstly,collect the domain knowledge of reservoir physical property mapping,and use the Prot é g é tool to model through an improved seven-step ontology construction method.Secondly,use the OWL language to represent the domain ontology to achieve formal expression of the ontology.Finally,based on a relational database,expand the hybrid decomposition storage mode while ensuring the semantic integrity of the OWL ontology file,Realize the storage structure construction and ontology library construction of reservoir physical property ontology.2.Aiming at the problem of abnormal data appearing in oilfield logging due to comprehensive factors,which affects the accuracy of mapping,a WOA-BP based abnormal data detection model is proposed.Aiming at the difficulty in selecting the weights and thresholds of BP neural networks,the WOA optimization algorithm is used to calculate the optimal weights and thresholds of BP neural networks.Using the average absolute error,root mean square error,and average absolute percentage error as evaluation indicators,the detection effects of BP neural networks before and after optimization are compared.Through experiments,it has been shown that the BP neural network optimized using WOA has better stability and convergence accuracy.3.Aiming at the ontology reasoning problem of reservoir physical property mapping,an ontology reasoning mechanism based on Jena framework is proposed.Firstly,based on the previous analysis of the conceptual relationships and attributes of reservoir physical property mapping ontology,inference rules are extracted,and custom rules are formally represented using Jena Rules language.Secondly,on the basis of user-defined rules,a rule inference engine supported by the Jena framework is selected,and the Rete inference algorithm is introduced.The efficiency of rule matching is compared with the default forward chain inference algorithm of the rule engine based on the matching time.The experimental results show that the Rete inference algorithm is more efficient in rule matching.4.Based on the above research results,a reservoir physical property mapping system has been designed and implemented and put into practical production.Field results show that the reservoir physical property mapping system in this study effectively improves the flexibility of mapping content selection and the expandability of the mapping system,solves the problem of knowledge sharing in this field to a certain extent,and reduces the system development and management costs of comprehensive mapping,The work efficiency of reservoir physical property evaluation personnel has been greatly improved.