Optimal 3D Reservoir Insight with a New Ultradeep-Reading Azimuthal LWD Resistivity Tool

Abstract

Abstract A new azimuthal electromagnetic (EM) logging-while-drilling (LWD) tool has been developed with multiple tilted antennas to measure three-dimensional (3D) electromagnetic fields. Multiple field trials successfully demonstrated the ultradeep detection range of more than 200 ft (60 m) with various transmitter-to-receiver spacings and operating frequencies, providing valuable geomapping insight for large-scale reservoir development. Additionally, this paper reveals the tool's capabilities in different geosteering applications, requiring different depth of detection (DOD) ranges for landing a well, optimizing well placement in thin reservoirs, and eliminating the need for a pilot hole. This paper discusses in detail a new 3D finite-difference (FD) method to simulate realistic and complicated formation structures in three dimensions, enabling accurate formation interpretations and inversion of reservoir geology. Solving the scattered potential boundary value problem with the 3DFD numerical algorithm simulates the EM signals in this new LWD ultradeep application, and the modeling accuracy was benchmarked alongside in-house modeling codes and 3D commercial software. To accelerate the computation in the 3D modeling, sliding window, multicore parallel cloud computing, and decoupling between model pixel grid and FD simulation grid have been implemented for practical applications. Additionally, 3D modeling is used in the inversion to provide more accurate and complex reservoir determinations. In addition to inversion, the tool provides 3D azimuthal multispacing, multifrequency geosignal, and resistivity measurements. Using the inversions and the 3D azimuthal images of the geosignal and resistivities enable improved reservoir understanding and geosteering decisions for the three dimensions. This paper describes two field trials from relatively thin to thick reservoirs to establish great and flexible geosteering performance because of multispacing, multifrequency measurements, and a robust signal and inversion process to optimize wellbore placements in the reservoir.