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A modified shear-wave velocity estimation method based on well-log data.
- Source :
-
Journal of Applied Geophysics . Feb2020, Vol. 173, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- Shear wave (S-wave) velocity is crucial for AVO inversion and fluid identification. Estimating S-wave velocity based on the rock physical model is commonly necessary for practical reservoir prediction. However, it is difficult to obtain some crucial parameters such as the pore aspect ratio accurately in some conventional estimation methods. Additionally, estimating S-wave velocity usually needs to use some optimization algorithms that depend on the initial values, which may decrease the accuracy of the estimation results. To solve these difficulties, we propose a concise S-wave velocity estimation method based on the notion of the consolidation parameter. We introduce a novel parameter defined as the product of consolidation parameter and porosity for calculating S-wave velocity, and propose a simple equation about the novel parameter after derivation. We solve the simple equation and obtain the novel parameter without needing any optimization algorithm. Then, the S-wave velocity is estimated accurately by using the novel parameter. The calculation of the proposed method is concise, because the optimization algorithm is needless, and the conventional parameters, such as the consolidation parameter and the pore-aspect ratio, can be disregarded. We test the estimation method by using well-log data from an oil field, where the lithology is complex. In the data test, the estimation error of the proposed method decreases compared with the error of the conventional method. • We propose a simple method to predict S-wave velocity. • The flexible estimation method needs no optimization algorithms. • The method is accurate even the lithology is complex. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09269851
- Volume :
- 173
- Database :
- Academic Search Index
- Journal :
- Journal of Applied Geophysics
- Publication Type :
- Academic Journal
- Accession number :
- 141808580
- Full Text :
- https://doi.org/10.1016/j.jappgeo.2019.103932