Reverse Time Migration (RTM) Technology
Reverse Time Migration (RTM) has become the method of choice for seismic imaging in complicated areas. The method is based on directly solving the wave equation in the time domain (as opposed to the frequency domain). RTM can accurately handle any variation in subsurface material properties, and has no limit in imaging steep dips. RTM is not based on ray tracing and hence can perform in situations where Kirchhoff ray based migration breaks down.
RTM principal is based on reversing the forward modeling operation. In forward modeling, we input a velocity model, select the source location, and by numerically solving the wave equation in incremental time steps, wave propagation is computed in the subsurface. RTM operation consists of inputting the wave field recorded at the surface, and by stepping backwards in time, propagate the seismic events to the subsurface location where they were generated.
In the case of post stack depth migration, instead of simulating wave propagation for a single shot location, we insert a source function at every velocity boundary location. This is known as the ‘exploding reflector’ concept (Jon F. Claerbout, Imaging the Earth’s Interior, 1996). For forward modeling we start the wave propagation simulation at time=0 and carry the propagation until time=T. For migration we reverse the operation by starting the wave propagation at time=T and propagating backwards until time=0. By doing this, when time=0 is reached, the reflections initiated at the subsurface velocity boundaries and recorded at the surface will reach back to their exact subsurface locations. This operation is called ‘post stack reverse time migration."
Prestack MigrationIn the case of prestack modeling, wave propagation starts at the surface, propagates downwards, reflects at the velocity boundaries and is recorded back at the surface. In order to ‘map’ the surface recorded wave fronts back to the subsurface locations from where they were reflected, we need to back propagate the recorded wavefronts from the surface back to the subsurface. Since we don’t know at what location and depth each wavefront was reflected from, we use the fact that at a reflection point the incident wave and the reflected wave are time coincident. Based on this assumption, we perform the three step operation: (1) Simulate the wavefront propagating from the source location; (2) Downward propagate the recorded wavefronts from the surface to the subsurface; (3) At every time step cross-correlate the simulated wavefield with the downward propagated wavefield. At every subsurface location that the simulated wavefield correlates with the downward propagated recorded wavefield, an image will be constructed. The above 3-step procedure is the basis for prestack Reverse Time Migration.
The above figures 1-3 demonstrate the wave field propagation from the source. Figures 1-3 below show the downward propagation of the receiver wavefield. Figures 1-6 below show the result of the cross correlation between the source wavefield and the receiver wavefield.
In order to successfully accomplish the above procedure, several key numerical operations need to be defined. Numerical solution of the wave equation calls for two mathematical operations: (a) Computation of numerical derivatives and (b) Computation of time integration. In order to ensure numerical stability of the solution scheme, an appropriate time step needs to be selected, and in order to ensure wave propagation with minimal numerical dispersion, the appropriate frequency band needs to be defined. In most cases, finite differences operators are used as the mechanism for time integration. To ensure numerical stability of the solution scheme, the time step for wave propagation needs to be very small, resulting with accurate time integration when second order finite differences operators are used. However, in order to be able to accomplish accurate wave propagation with minimal or no numerical dispersion, a careful selection of the derivative operators need to be done.
The computational cost of RTM PSDM is very high. In order to be able to migrate a broader frequency range, a small size cell needs to be used as the numerical grid. This results with large computer memory requirement as well as an enormous number of floating point operations.
These two limitations lead very often to the use of a band limited selection of the input data, resulting with low frequency RTM PSDM. The tion to overcome these limitations in implementing of RTM PSDM leads us to develop solutions both in software and in hardware.
