Interface detection of near-borehole stratified formation under different permeabilities based on seismoelectric logs: A finite-difference modeling

Abstract

Seismoelectric wavefields arising from electrokinetic effects in fluid-filled porous media are valuable for reservoir exploration. Identifying the formation interface is crucial for reservoir exploration. In this study, we developed a finite-difference (FD) algorithm for calculating borehole seismoelectric wavefields and proposed the use of seismoelectric logs to detect permeability interfaces in near-borehole formations. The borehole-formation acoustic wave and its induced electromagnetic (EM) wavefield are calculated separately using the FD algorithm where the feedback effect of the EM wavefield on the acoustic wave is disregarded. We find that various acoustic-guided waves propagating along the borehole wall (P, S, and Stoneley waves) could generate significant EM waves at the formation interfaces with varying permeabilities. At the horizontal interfaces, the acoustic field does not generate significant interface signals. The EM wave induced by the Stoneley wave is clearly observed in the borehole, whereas those induced by the P and S waves are barely distinguishable. At the tilted interfaces, the Stoneley-wave-induced EM wave is more noticeable, and even P- and S- waves-induced EM waves are clearly observed. The mud cake and invaded zone near the borehole wall have little influence on the interface detection of near-borehole formations using seismoelectric logs. The collar wave during sonic logging while drilling, is a nerve-wracking, noisy signal that can significantly impede the extraction of P- and S-wave velocities. However, the collar wave can generate significant interfacial EM signals, thereby allowing for the detection of formation interfaces using the collar wave. Theoretical calculation shows that compared with the acoustic field in sonic logging, the electric field in seismoelectric logging has more advantages in stratified interface identification. It shows that seismoelectric logging has potential application value in the detection of the formation interface.