Corrections of logging-while-drilling electromagnetic resistivity logging data acquired from the horizontal well for the shale oil reservoir

• Published in: Applied geophysics 2023-03, Vol.20 (1), p.9-19
• Main Authors: Liu, Ying-Ming, Wang, Lei, Wang, Cai-Zhi, Wang, Hao, Qiao, Ping
• Format: Article
• Language: English
• Subjects: Algorithms; Anisotropy; Borehole Geophysics; Boreholes; Data acquisition; Data logging; Drilling; Earth and Environmental Science; Earth Sciences; Electrical resistivity; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Heterogeneity; Horizontal wells; Logging; Oil reservoirs; Oil shale; Qualitative analysis; Quantitative analysis; Reservoirs; Sedimentary rocks; Shale oil; Shales; Water pollution
• ISSN: 1672-7975; 1993-0658
• DOI: 10.1007/s11770-022-0954-2

The responses of logging-while-drilling (LWD) electromagnetic resistivity logging in horizontal wells are usually complex due to the effect of the strong heterogeneity and anisotropy of the shale oil reservoir. Therefore, the qualitative interpretation and quantitative evaluation of such data are still challenging. To this end, a correction method is developed for the LWD resistivity logging data acquired from a horizontal well for the shale oil reservoir. First, the electrical interpretation model, which considers the formation resistivity properties and various mud types, is established to accommodate the shale oil formation and horizontal well environment. The effects of the borehole on the measured signals, that is, phase shift and attenuation ratio, are simulated. The relationship between the complicated tool and point source responses in a homogeneous medium is established to suppress these effects. The point-by-point real-time anisotropy correction method is developed for the LWD resistivity data from thick beds based on this borehole correction process and the analytical algorithm. The boundary positions and relative dipping information for the thin formations should be obtained from the mapping logging data. Finally, the horizontal and vertical resistivities of each layer are extracted using the one-dimensional (1D) formation model in association with the gradient optimization algorithm. Numerical results show that the LWD resistivity data after the borehole correction can be simplified to 1D, laying the foundations for the fast data process. Moreover, the horizontal and vertical resistivities of shale oil beds are accurately determined using the anisotropy correction of LWD resistivity data from horizontal wells, thereby providing reliable electrical parameters for the interpretation and quantitative evaluation of the shale oil reservoir.