An Eigenfunction Representation of Deep Waveguides with Application to Unconventional Reservoirs

Guided waves that propagate in deep low-velocity zones can be described using displacement-stress eigenfunction theory. For a layered subsurface, these eigenfunctions provide a framework to calculate guided-wave properties at a fraction of the time required for fully numerical approaches for wave-equation modeling, such as the finite-difference approach. Using a 1D velocity model representing the low-velocity Eagle Ford Shale, an unconventional hydrocarbon reservoir, we verify the accuracy of the displacement eigenfunctions by comparing with finite-difference modeling. We use the amplitude portion of the Green's function for source-receiver eigenfunction pairs as a proxy for expected guided-wave amplitude. These response functions are used to investigate the impact of velocity contrast, reservoir thickness, and receiver depth on guided-wave amplitudes for discrete frequencies. We find that receivers located within the low-velocity zone record larger guided-wave amplitudes. This property may be used to infer the location of the recording array in relation to the low-velocity reservoir. We also study guided-wave energy distribution between the different layers of the Eagle Ford model and find that most of the high-frequency energy is confined to the low-velocity reservoir. We corroborate this measurement with field microseismic data recorded by DAS (distributed acoustic sensing) fiber installed outside of the Eagle Ford. The data contain high-frequency body-wave energy, but the guided waves are confined to low frequencies since the recording array is outside the waveguide. We also study the energy distribution between the fundamental and first guided-wave modes as a function of frequency and source depth and find a nodal point in the first mode for source depths originating in the middle of the low-velocity zone, which we validate with the same field data. The varying modal energy distribution can provide useful constraints for microseismic event depth estimation.