Sensitivity Analysis and Optimization for Enhancing the Look-Ahead Capability of Electromagnetic Logging While Drilling Tools

In the past decades, electromagnetic (EM) logging while drilling (LWD) has been widely used for well landing and geosteering in high angle and horizontal wells. Recently, this technology has been extended to geo-stopping applications in vertical wells and deviated wells, leveraging its excellent look-ahead-of-bit capability, particularly in ultra-deep reservoirs. Compared to traditional look-around applications in horizontal wells, achieving look-ahead capability is significantly more challenging because the sensitive region of the tool's response is primarily concentrated in the formation between the transmitting and receiving coils. Current look-ahead methods typically use the information from the drilled formation as a constraint to invert the formation ahead of the bit. However, this approach heavily relies on the accuracy of the surrounding formation property measurements. Therefore, to enhance the look-ahead capability and accuracy, it is necessary to further improve the contribution of the formation ahead of the bit to the tool's response.

In this paper, we analyze the spatial sensitivity of the magnetic field components based on the Born geometric factor. Among these, the coaxial (Hzz) and coplanar (Hxx and Hyy) components exhibit look-ahead sensitivity and can be used for look-ahead detection. In EM LWD look-ahead measurements, it is common to combine the coaxial and coplanar components to define the look-ahead signal. We further derive the spatial sensitivity functions for phase shift and amplitude ratio, with results showing that the primary contribution to the look-ahead signal still comes from the formation between the transmitter and receiver. To address this, we propose a signal enhancement method based on Multi-TR-spacing signal superposition. By exploiting the differences in sensitivity ranges of signals from different TR spacings, the method optimizes the sensitive space through signal superposition, thereby improving the tool’s look-ahead performance. Finally, we employ numerical simulation algorithms to compare the look-ahead capability of the new method with traditional methods. Simulation results demonstrate that, the look-ahead signal obtained with the new method is significantly enhanced to 1.5 times, and the maximum distance range has been increased by 30% that enabling the detection of interfaces at greater distances. Additionally, the new method results in a stronger sensitivity to the formation boundaries ahead of the bit, suggesting an improvement in inversion accuracy. It is important to emphasize that the method proposed in this paper can also be extended to look-around detection, for further enhancing the sensitivity of a specific detection area.