In the last two decades a lot of effort has been directed towards
methods that have the potential to succeed in imaging complex 3D
subsurface structures from multi-coverage seismic data. The necessity
of an estimate for the wave propagation velocities, required for
transforming the data from the time domain to the depth domain, poses
one of the fundamental problems in seismic imaging. Inadequate
velocity models distort the final depth image. So-called data-oriented
approaches are a class of imaging methods that avoid the explicit
parameterisation of a velocity model in the first imaging steps.
Instead, the data-oriented approaches parameterise the reflection
events in the time domain and try to obtain as much information as
possible from the measured data. The extracted information is then
used to transform the seismic data into depth.
The common-reflection-surface (CRS) stack is one of the data-oriented
imaging approaches. This method makes use of second-order traveltime
approximations in order to describe seismic reflection events in the
time domain. For the processing of data from a 3D acquisition, the
traveltime equations can be used as stacking operators to simulate a
zero-offset (ZO) volume of high accuracy and high signal-to-noise
ratio from multi-coverage prestack data. During the stack, reflection
energy from the entire five-dimensional data hyper-volume enters into
the construction of one ZO sample. The eight parameters, which express
the traveltime approximation for the ZO case, relate to kinematic
wavefield attributes. These locally describe the propagation
directions and curvatures of specific wavefronts at the Earth's
surface which have travelled through the subsurface. Thus, the
kinematic wavefield attributes constitute integral quantities of the
medium's parameters and are suitable to estimate the properties of the
Earth's interior. The accurate determination of the wavefield
attributes is, therefore, a crucial step in the CRS processing.
In this thesis the derivation of the traveltime approximations is
presented. The kinematic wavefield attributes are introduced by means
of concepts known from geometrical optics. The determination of the
eight kinematic wavefield attributes for the ZO case from 3D
multi-coverage seismic data is elaborated. The applications of the
attributes to support and facilitate 3D seismic imaging are discussed.
In this context emphasis is put on the utilisation of the kinematic
wavefield attributes for the 3D CRS stack. The proposed search
algorithms are validated on a synthetic data example and have shown to
be successful. Finally, the 3D CRS stack is applied to a real marine
dataset. In this way the functionality of the search algorithms on
complex data is verified. Moreover, the imaging quality of the 3D CRS
stack is checked by migrating the simulated ZO volume to depth and
comparing the obtained result with the result from a prestack depth
migration. The comparison shows that the CRS based result is
competitive to the result of the prestack depth migration. Thus, CRS
based imaging is an alternative to prestack depth migration due to the
good imaging quality and also due to the provided information in form
of the kinematic wavefield attributes.
Steffen Bergler
3 D seismic imaging coherence analysis kinematic wavefield attributes paraxial ray theory reflection seismic