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The Research On Attribute Synthetic Evaluation Model Of Discrimination And Grade Division Of Oil-bearing Reservoir

Posted on:2022-09-20Degree:MasterType:Thesis
Country:ChinaCandidate:J SunFull Text:PDF
GTID:2481306551998319Subject:Applied Mathematics
Abstract/Summary:
The identification of oil-bearing reservoir is the core link between petroleum exploration and development,and the accurate division of oil,water and dry layers is the basis for making production plans.However,it’s difficult to distinguish and classify the oil-bearing reservoir due to the complexity of geological and the diversity of influencing factors,it greatly reduces the efficiency of oil.Comprehensive theoretical analysis,mathematical model and actual measurement are used to discriminate the oil-bearing reservoir based on previous research results and a large number of observation data.Firstly,the density,porosity,permeability,water saturation and shale content are selected as the evaluation indexes of reservoir oil and gas properties based on previous research results and a large number of engineering practices,and it has been analyzed and researched from both qualitative and quantitative aspects.Secondly,the effective discrimination rate of the oil layer is 76.4%based on the coupling theory of grey wolf optimization algorithm and support vector machine,but consider that the grey wolf algorithm is easy to fall into the local optimization,get the system parameters according to differential grey wolf optimization algorithm,and then obtain the rate is 87.64%by the coupling of the differential grey wolf evolution algorithm and the support vector machine,which significantly improves the discrimination accuracy.Finally,in order to further improve the oil recovery rate,with the identical results,the oil layer classification model was established by attribute mathematical theory,and the classification standards of various evaluation indicators of the oil layer are constructed,and a sample data belongs to which level can be predicted by the attribute comprehensive evaluation theory.The model was validated by selecting the measured data from an oil field in Shanxi,the evaluation results obtained are basically consistent with the field measurements,which fully proves the effectiveness of the model.Comprehensive theoretical analysis,mathematical modeling,and actual measurement verification methods provide a theoretical basis for the determination of reservoir oil and gas properties and the classification of oil layers,which is important for determining areas with an industrial production value,formulating oil production plans,and realizing the best economic benefits.
Keywords/Search Tags:reservoir oil and gas properties, discrimination and division, support vector machine, differential gray wolf optimization algorithm, attribute evaluation
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