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.
Original language | English |
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Pages (from-to) | D69-D83 |
Number of pages | 15 |
Journal | Geophysics |
Volume | 88 |
Issue number | 2 |
Early online date | 27 Jan 2023 |
DOIs | |
Publication status | Published - 1 Mar 2023 |
Bibliographical note
Funding Information:We would like to express our gratitude to C. Warren at Northumbria University for valuable help with gprMax modeling and W. Filinger at The University of Edinburgh for assistance in high-performance computing. This research was funded by the National Natural Science Foundation of China (41974165 and 42111530126), the HPC-Europa3 program (HPC175KVPR), the Open Fund of Hubei Key Laboratory of Marine Geological Resources (MGR202012), and CRSRI Open Research Program (CKWV2021883/KY).
Data Availability Statement
No data have been required for this paper.Keywords
- borehole geophysics
- ground-penetrating radar