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- W3213771107 endingPage "92" @default.
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- W3213771107 abstract "This chapter reviews multiple applications of seismic attributes in reservoir characterization of natural gas reservoirs. Some seismic attributes such as bright spots, flat spots, dim spots, and polarity changes provide direct gas indicators. Other attributes can be formulated to indicate reservoir rock and fluid properties. Seismic attributes play a pivotal role in the detection and delineation of natural gas reservoirs. Through integration with core and well log derived data, seismic attributes have been very successful in rock and fluid properties mapping. Some seismic attributes such as bright spots, flat spots, dim spots, polarity changes and AVO inversion attributes are direct gas indicators. Some attributes such as inverted acoustic impedance (AI) have strong relationships with elastic moduli and petrophysical data such as porosity, water saturation and lithology. Accordingly, fluid and rock properties of natural gas reservoirs can be formulated to a set of predefined seismic attributes using statistical or machine learning techniques. This chapter reviews multiple applications of seismic attributes and their combination in reservoir characterization of natural gas reservoirs. Several examples and case studies of their practical implementation in fluid typing and rock properties estimation are provided. Seismic attributes effectively aid the exploration and development of natural gas reservoirs. Through integration with well data, they help reduce uncertainty in reservoir static and dynamic simulation models and much more successful implantation of field development plans." @default.
- W3213771107 created "2021-11-22" @default.
- W3213771107 creator A5063746477 @default.
- W3213771107 creator A5065958119 @default.
- W3213771107 date "2022-01-01" @default.
- W3213771107 modified "2023-10-14" @default.
- W3213771107 title "Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties" @default.
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- W3213771107 doi "https://doi.org/10.1016/b978-0-323-85465-8.00007-8" @default.
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