Evaluating the Classification of Low Permeability Glutenite Reservoir with Logging Analysis
The composition of glutenite reservoir always have characteristics of complication, low maturity, poor sorting and high clay content, for it is the result of the multiple deposition.Its complication causes the difficulties in reservoir zonation, lithological discrimination, calculation of geologic parameter, fluid identification and so on.It is more difficult to evaluate reservoir without rockspecimen.We analyzed various sorts of logging data, took core and core wafer and then the analytical data is regarded to the specimen.By BP neural network method, fixed parameter such as effective thickness, extent of porosity and penetrance was acquired and the reservoir was classified and evaluated.All of these provided a basis for the reservoir classification without core specimen.
low permeability glutenite reservoir reservoir evaluation logging analysis neural network
Lingling Wang Pengfei Li Qiding Zhang Xiaochun Zuo Cunlei Li Panpan Chen
College of Petroleum Engineering, Liaoning Shihua University, Fushun 113001, Liaoning, China College of Petroleum Engineering, Liaoning Shihua University, Fushun 113001, Liaoning, China;School
国际会议
杭州
英文
698-702
2018-06-10（万方平台首次上网日期，不代表论文的发表时间）