ALBERT

Description: In recent years, marine controlled source electromagnetics (CSEM) has found increasing use in hydrocarbon exploration due to its ability to detect thin resistive zones beneath the seafloor. It is the purpose of this paper to evaluate the physics of CSEM for an ocean whose electrical thickness is comparable to or much thinner than that of the overburden using the in-line configuration through examination of the elliptically polarized seafloor electric field, the time-averaged energy flow depicted by the real part of the complex Poynting vector, energy dissipation through Joule heating and the Fréchet derivatives of the seafloor field with respect to the subseafloor conductivity that is assumed to be isotropic. The deep water (ocean layer electrically much thicker than the overburden) seafloor EM response for a model containing a resistive reservoir layer has a greater amplitude and reduced phase as a function of offset compared to that for a half-space, or a stronger and faster response. For an ocean whose electrical thickness is comparable to or much smaller than that of the overburden, the electric field displays a greater amplitude and reduced phase at small offsets, shifting to a stronger amplitude and increased phase at intermediate offsets and a weaker amplitude and enhanced phase at long offsets, or a stronger and faster response that first changes to stronger and slower, and then transitions to weaker and slower. These transitions can be understood by visualizing the energy flow throughout the structure caused by the competing influences of the dipole source and guided energy flow in the reservoir layer, and the air interaction caused by coupling of the entire subseafloor resistivity structure with the sea surface. A stronger and faster response occurs when guided energy flow is dominant, while a weaker and slower response occurs when the air interaction is dominant. However, at intermediate offsets for some models, the air interaction can partially or fully reverse the direction of energy flux in the reservoir layer toward rather than away from the source, resulting in a stronger and slower response. The Fréchet derivatives are dominated by preferential sensitivity to the reservoir layer conductivity for all water depths except at high frequencies, but also display a shift with offset from the galvanic to the inductive mode in the underburden and overburden due to the interplay of guided energy flow and the air interaction. This means that the sensitivity to the horizontal conductivity is almost as strong as to the vertical component in the shallow parts of the subsurface, and in fact is stronger than the vertical sensitivity deeper down. However, the sensitivity to horizontal conductivity is still weak compared to the vertical component within thin resistive regions. The horizontal sensitivity is gradually decreased when the water becomes deep. These observations in part explain the success of shallow towed CSEM using only measurements of the in-line component of the electric field.

Description: Electromagnetic responses reflect the interaction between applied electromagnetic fields and heterogeneous geoelectrical structures. Quantifying the relationship between multiscale electrical properties and the observed electromagnetic response is therefore important for meaningful geologic interpretation. We present here examples of near-surface electromagnetic responses whose spatial fluctuations appear on all length scales, are repeatable and fractally distributed, supporting the notion of a ‘rough geology’ exhibiting multiscale hierarchical structure. Bounded by end member cases from homogenized isotropic and anisotropic media, we present numerical modelling results of the electromagnetic responses of textured and spatially correlated, stochastic geologic media, demonstrating that the electromagnetic response is a power law distribution, rather than a smooth response polluted with random, incoherent noise as commonly assumed. Our modelling results show that these electromagnetic responses due to spatially correlated geologic textures are examples of fractional Brownian motion. Furthermore, our results suggest that the fractal behaviour of the electromagnetic responses is correlated with degree of the spatial correlation, the contrasts in ground conductivity, and the preferred orientation of small-scale heterogeneity. In addition, the EM responses acquired across a fault zone comprising different lithological units and varying wavelengths of geologic heterogeneity also support our inferences from numerical modelling.