Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
نویسندگان
چکیده
The map of permeability distribution in the reservoirs is considered one most essential steps geologic model building due to its governing fluid flow through reservoir which makes it influential parameter on history matching than other parameters. For that, petrophysical properties that are tuned during matching. Unfortunately, prediction relationship between static petrophysics (porosity) and dynamic (permeability) from conventional wells logs has a sophisticated problem solve by statistical methods for heterogeneous formations. this paper examines ability performance artificial intelligence method compared results with zone indicator carbonate Iraqi formation. methodology research can be Summarized was estimated using two methods: Flow Artificial intelligence, models built, where difference them estimation, simulation run will conducted both models, estimation examined comparing their effect showed predicted matched observed data different responses more accurately method. That conclusion represented good simulated all such model.
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ژورنال
عنوان ژورنال: Iraqi geological journal
سال: 2023
ISSN: ['2414-6064', '2663-8754']
DOI: https://doi.org/10.46717/igj.56.1e.2ms-2023-5-12