Reverse time migration imaging of ground-penetrating radar data in complex environments
Tuesday, 16 December 2014
Because reverse-time migration (RTM) honors the physics of wave propagation more closely than other migration algorithms, it has become the preferred imaging tool in seismic exploration over the past 10-15 years. This shift has been facilitated by advances in computational power which have made it feasible to routinely migrate large datasets. Despite this evolution in exploration seismology, the use of RTM has remained relatively limited in ground-penetrating radar (GPR) applications even though the advantages in GPR imaging are comparable. For example, within the RTM framework it is possible to include antenna radiation directly in the imaging algorithm. Additionally complications such as irregular surface topography and highly heterogeneous subsurface electrical properties can be incorporated naturally into an RTM algorithm. I have implemented both pre- and post-stack RTM algorithms for GPR imaging. The post-stack algorithm utilizes the exploding reflector concept and an approximate formulation of the EM wave equation to account for propagation through lossy media. The pre-stack algorithm utilizes the full two way solution to Maxwell’s equations, and includes radiation patterns directly in the imaging routine. Here, I investigate amplitude reconstruction using RTM in complex environments with a focus on complex topography and the interplay between radar radiation patterns and topography. Complex topography alters wavefield kinematics making for a challenging imaging problem; topographic variation can substantially distort radiation patterns, produce irregular spreading, and alter amplitudes by focusing and defocusing effects at the surface. The effects are magnified when the topographic variations are on the same order as the depth of investigation – a situation that is often encountered in GPR investigations. I consider both pre- and post-stack GPR imaging in the presence of large topographic and subsurface variability. Using both synthetic and field examples I show that a carefully constructed RTM algorithm is capable of accurate reconstruction of GPR reflection amplitudes in complex media and thereby facilitates estimation of reflection coefficients at a reflecting boundary.