Facies-Controlled Modeling for Permeability of Tight Gas Reservoir Based on Hydrodynamic and Geophysics Characteristics

Due to poor physical properties and strong heterogeneity of Daniudi tight gasfield (China), traditional methods are not ideal for predicting reservoir permeability. Based on geoscience data mining algorithms and modeling techniques, this parameter is predicted and characterized from a new perspectiv...

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Bibliographic Details
Published inGeofluids Vol. 2022; pp. 1 - 9
Main Author Yu, Peng
Format Journal Article
LanguageEnglish
Published Chichester Hindawi 28.01.2022
John Wiley & Sons, Inc
Wiley
Subjects
Accuracy
Algorithms
Analysis
Back propagation networks
Data analysis
Data logging
Data mining
Gas fields
Geology
Geophysics
Heterogeneity
Hydraulics
Hydrodynamics
Laws, regulations and rules
Logging
Modelling
Neural networks
Permeability
Physical properties
Reservoirs
Software
China
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Summary:Due to poor physical properties and strong heterogeneity of Daniudi tight gasfield (China), traditional methods are not ideal for predicting reservoir permeability. Based on geoscience data mining algorithms and modeling techniques, this parameter is predicted and characterized from a new perspective. The high precision hydraulic unit information was outputted by the BP neural network and the interwell database was predicted by sequential indicator simulation based on the logging and core data, the exponential and power law relationship functions were selected to participate in the construction of the permeability model. The results showed that the facies-controlled modeling system for permeability based on the hydrodynamic characteristics of tight gas reservoirs could effectively improve the accuracy of reservoir prediction, and the logging information in the longitudinal direction and the facies information in the plane were combined by the hydraulic unit.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1468-8115
1468-8123
DOI:10.1155/2022/5033078