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Fuzzy‐based nuclear analysis segregation model for distinguishing the properties of repository liquids and gas in gas storage
Author(s) -
Deng Rui,
Meng Qingwei
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4967
Subject(s) - petroleum engineering , petroleum , fossil fuel , gas oil ratio , enhanced oil recovery , pipeline (software) , layer (electronics) , environmental science , geology , materials science , engineering , waste management , nanotechnology , mechanical engineering , paleontology
Summary The geophysical well logging analysis is a major task of petroleum research and development, where petroleum oil (gas), transition petroleum layers, water layers, and dry‐layer segments are precisely distinguished from each other. The resistivity of the particular oil and gas layers in developing countries is below or close to the water layers. As electrical properties show, the particular oil and gas layer of water layers is not legitimately recognizable. The features of oil and gas strata and their strong components are different in the investigative field from those of different petroleum fields. In this way, various techniques and thoughts ought to be utilized to comprehend the particular issues in the examination zone. A nuclear analysis–based segregation model for distinguishing the properties of repository liquids is worked by utilizing the crude pipeline and distilled unit of oil (gas) layers, transitional oil water layers, water layers, and dry layers using dynamic nonlinear fuzzy clustering model. With directly complex transformation models, reservoir fluids can be separated. The outcomes are analyzed with various model, and the proposed method shows promising outcomes.