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An inversion method for imaging near-wellbore thin beds slowness based on array acoustic logging data.

Authors :
Zi Wang
Wenzheng Yue
Source :
Frontiers in Earth Science; 2024, p01-09, 9p
Publication Year :
2024

Abstract

As a practical approach to reflecting the properties of the formation, the slowness of near-wellbore formation is of great significance to geophysical exploration, which can be used to evaluate rock brittleness, wellbore stability, fracturing effect, and invasion depth. Although traditional slowness imaging methods perform well in areas where the thickness of the heterogeneous formation is greater than the length of the receiver array of the logging instrument, they may fail when encountering thin beds. The thin beds' axial thickness, radial invasion depth, and radial slowness are challenging to identify, resulting in obtaining an average slowness value without longitudinal resolution. This paper proposes a thin beds slowness imaging inversion method that can effectively invert the axial thickness, radial invasion thicknesses, and radial slowness variations of thin beds with higher axial resolution compared to traditional methods. The new method adaptively extracts slowness sequences with different radial depths by combining receivers with different source distances. It obtains their corresponding radial thicknesses through ray theory, which does not depend on the arrival times of the first wave. This method is sensitive to thin beds, and the axis thickness of thin beds can be estimated by the change of radial slowness sequence and the combined source distance length. Combining the results at different depths allows a slowness image of the thin beds near-wellbore to be directly obtained. The effectiveness and accuracy of the proposed method are verified by synthetic data and field data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22966463
Database :
Complementary Index
Journal :
Frontiers in Earth Science
Publication Type :
Academic Journal
Accession number :
175917760
Full Text :
https://doi.org/10.3389/feart.2024.1292561