Propagation of Gaussian wave packets in complex media and application to fracture characterization. Issue 2 (23rd May 2017) - Ding, Yinshuai; Zheng, Yingcai; Zhou, Hua-Wei; Howell, Michael; Hu, Hao; Zhang, Yu
Abstract: Knowledge of the subsurface fracture networks is critical in probing the tectonic stress states and flow of fluids in reservoirs containing fractures. We propose to characterize fractures using scattered seismic data, based on the theory of local plane-wave multiple scattering in a fractured medium. We construct a localized directional wave packet using point sources on the surface and propagate it toward the targeted subsurface fractures. The wave packet behaves as a local plane wave when interacting with the fractures. The interaction produces multiple scattering of the wave packet that eventually travels up to the surface receivers. The propagation direction and amplitude of the multiply scattered wave can be used to characterize fracture density, orientation and compliance. Two key aspects in this characterization process are the spatial localization and directionality of the wave packet. Here we first show the physical behaviour of a new localized wave, known as the Gaussian Wave Packet (GWP), by examining its analytical solution originally formulated for a homogenous medium. We then use a numerical finite-difference time-domain (FDTD) method to study its propagation behaviour in heterogeneous media. We find that a GWP can still be localized and directional in space even over a large propagation distance in heterogeneous media. We then propose a method to decompose the recorded seismic wavefield into GWPs based on the reverse-time concept. This method enables us to create a virtually recorded seismic data using field shot gathers, as if the source were an incident GWP. Finally, we demonstrate the feasibility of using GWPs for fracture characterization using three numerical examples. For a medium containing fractures, we can reliably invert for the local parameters of multiple fracture sets. Differing from conventional seismic imaging such as migration methods, our fracture characterization method is less sensitive to errors in the background velocity model. For a layered medium containing fractures, our method can correctly recover the fracture density even with an inaccurate velocity model.