Extracting mud invasion information using borehole radar - A numerical study

Journal Article (2023)
Author(s)

F. Zhou (China University of Geosciences, Wuhan, TU Delft - Applied Geophysics and Petrophysics)

Iraklis Giannakis (University of Aberdeen)

Antonios Giannopoulos (The University of Edinburgh)

Klaus Holliger (University of Lausanne)

Evert Slob (TU Delft - Applied Geophysics and Petrophysics)

Research Group
Applied Geophysics and Petrophysics
Copyright
© 2023 F. Zhou, Iraklis Giannakis, Antonios Giannopoulos, Klaus Holliger, E.C. Slob
DOI related publication
https://doi.org/10.1190/geo2022-0121.1
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 F. Zhou, Iraklis Giannakis, Antonios Giannopoulos, Klaus Holliger, E.C. Slob
Research Group
Applied Geophysics and Petrophysics
Issue number
2
Volume number
88
Pages (from-to)
D69-D83
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Abstract

In hydrocarbon drilling, mud filtrate penetrates permeable formations and alters the pore fluid characteristics in the immediate vicinity of the borehole. Typically, the prevailing in situ pore fluids are displaced by the invading mud filtrate, which leads to gradually changing distributions of the fluid and electrical properties. Understanding this invasion process is crucial for the interpretation of logging data and associated reservoir evaluations. Conventional logging methods tend to be inadequate for this purpose as their resolution is too low. We find that invasion depth can be determined from borehole radar data using an optimized antenna configuration and time-lapse measurements. A series of parametric sensitivity analyses provide information about the effects of variations of the rock and fluid properties on the identification and extraction of borehole radar signals reflected from the invasion front. Our results suggest that by embedding the radar antennas in cavities filled with an absorbing dielectric material, it is possible to minimize the interference arising from the metal components of the logging tool. In the simulated reservoir scenario, a time-lapse measurement mode with a time interval of at least 6 h can reliably extract the radar signals reflected from the invasion front, and the proposed borehole radar has a lateral detection range from 0.15 to 1 m. A comprehensive range of parametric sensitivity analyses indicates that the signals reflected from the invasion front are principally influenced by oil viscosity, porosity, and mud and formation water salinity, as well as by molecular diffusion coefficient and cementation exponent. These properties and parameters should be carefully explored and assessed when applying borehole radar to evaluate mud invasion information in a reservoir environment.

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