Study On Logging Productivity Prediction Method Of Deep Sandstone Reservoirs In H Block Of Eastern South China Sea

The production capacity forecast has an important guiding role for oilfield development and production.It can effectively and orderly implement the various plans of the oil production plant.It is the basis for the whole enterprise to formulate development plans and prepare development and adjustment bills.The main purpose of using logging data for reservoir productivity prediction research is to establish a relationship between reservoir productivity and logging data based on the analysis of existing logging,oil testing and core analysis data in the study area.Correspondence,and then use logging data to evaluate and predict reservoir capacity.At present,deep oil and gas reservoirs have gradually entered the exploration range.Due to the complex reservoir characteristics of deep reservoirs,it is difficult to evaluate their production capacity using well logging data.Therefore,research on the logging prediction method of deep reservoir productivity is of great significance for guiding the development of deep reservoir capacity.Firstly,by collecting and arranging the core data,logging data,geological data and test data of the block,analyzing the geological characteristics of the deep reservoirs in the H block of the eastern South China Sea,the logging response characteristics,the characteristics of the capillary pressure curve,the effective permeability,crude oil viscosity,mobility,and skin factor characteristics of different productivity reservoirs,it is found that the physical properties of the reservoir are the key to affecting reservoir productivity.And the effective permeability has the greatest impact on the reservoir productivity.In addition,when the viscosity of the crude oil is high,the reservoir productivity decreases with the increase of viscosity.Therefore,accurate calculation of reservoir effective permeability and viscosity is the key to accurately predict reservoir productivity in the study area.The analysis found that there is a good correlation between absolute permeability and effective permeability.Therefore,under the premise of accurately evaluating the absolute permeability,the effective permeability of the reservoir is predicted.Through multiple regression,based on flow unit classification,based on nuclear magnetic T2 full spectrum,the three permeability prediction methods,it is found that the prediction method of nuclear magnetic resonance T2 spectrum can fully consider the characteristics of severe heterogeneous reservoirs and solve the problem of permeability prediction in low permeability parts of reservoirs with fast permeability changes.However,the nuclear magnetic logging data is not in every well for its own reasons.Therefore,the flow unit classification method is used to predict the permeability in the reservoir without nuclear magnetic logging.The calculation method of the viscosity of the whole section of crude oil was established by the formation temperature and the density of the formation crude oil.After the capacity impact parameter evaluation model is established,the reservoir categories are divided into three categories by the capillary pressure curve morphology that reflects the characteristics of the reservoir pore throat structure.Then the reservoir classification and capacity classification will be combined,the capacity category boundary is divided into the oil production index per meter equal to 1 and 10 m~3/(d·MPa·m),and the capacity classification index Zz is established to classify the reservoir capacity category.Then use the reservoir quality index RQI to evaluate the Zz curve of the whole well and identify the reservoir type of the whole well.The capacity classification and identification method was applied to all wells in the deep reservoirs of the study area,and the accuracy rate reached more than 85%,and the application effect was good.Based on the density logging value,reservoir quality index and mobility,the capacity comprehensive index A is used to quantitatively predict the reservoir productivity,and the evaluation results are more accurate.In addition,the method of thickness-weighted capacity prediction calculates the production capacity of various reservoirs in the study area,that is,the production capacity of various reservoir units.After normalization,it is used as the effective thickness weight of various reservoirs,and the reservoir index Y is established to accurately predict the reservoir productivity with severe heterogeneity.The productivity prediction accuracy is within an order of magnitude.