Abstract

The recent increase in energy demand has propelled research on the discovery of unconventional energy sources as conventional oil and gas reservoirs are been depleted. Hence, in this study, we investigate the feasibility of using the Borehole Controlled Source Electromagnetic (BSCSEM) method for gas hydrate exploration in Qilian Mountain, China. To achieve this, we developed an accurate and efficient forward modeling code for the simulation of electromagnetic diffusion problems based on the total field formulation using the Frequency Domain Finite Difference (FDFD) approach. We used large grid sizes to reduce the computational cost of simulating the borehole to surface responses and also examined the effect of applying the Perfectly Matched Layer (PML) on the BSCSEM computational area. Subsequently, we investigate the effects of the higher and lower-order approximations and used spatial operators of the lower order and first-order accuracy in substantial parts of the computational domain including but not limited to layer boundaries during the solution process. We also investigate responses from different source orientations and source length, with a focus on the electric dipoles for 2D and 3D models of buried resistive targets. Finally, we performed 2D modeling to detect onshore gas hydrate deposit for known scenarios using a suitable BSCSEM configuration for 200 m borehole dipole with an average current of 10 A. Our results generally indicate that the BSCSEM responses from the vertical transmitters were highly effective in characterizing the resistive layers as well as the measurement of the vertical component of the electric field. By changing the depth of the vertical dipole sources, we found out that BSCSEM showed the ability to gain information about the subsurface medium from different angles. Hence, we conclude that in a complex environment, the combined use of the horizontal and the vertical transmitters to acquire three component (3C) field data and the joint analysis of their electric responses helps to delineate the subsurface structure more clearly.

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