| dc.description.abstract | Turbidite reservoirs in deep-water depositional systems, such as the oil fields in
the offshore Gulf of Mexico and North Sea, are becoming an important exploration
target in the petroleum industry. Accurate seismic reservoir characterization, however,
is complicated by the heterogeneous of the sand and shale distribution and
also by the lack of resolution when imaging thin channel deposits. Amplitude variation
with offset (AVO) is a very important technique that is widely applied to locate
hydrocarbons. Inaccurate estimates of seismic reflection amplitudes may result
in misleading interpretations because of these problems in application to turbidite
reservoirs. Therefore, an efficient, accurate, and robust method of modeling seismic
responses for such complex reservoirs is crucial and necessary to reduce exploration
risk.
A fast and accurate approach generating synthetic seismograms for such reservoir
models combines wavefront construction ray tracing with composite reflection
coefficients in a hybrid modeling algorithm. The wavefront construction approach is
a modern, fast implementation of ray tracing that I have extended to model quasishear
wave propagation in anisotropic media. Composite reflection coefficients, which
are computed using propagator matrix methods, provide the exact seismic reflection
amplitude for a stratified reservoir model. This is a distinct improvement over conventional
AVO analysis based on a model with only two homogeneous half spaces. I
combine the two methods to compute synthetic seismograms for test models of turbidite
reservoirs in the Ursa field, Gulf of Mexico, validating the new results against
exact calculations using the discrete wavenumber method. The new method, however,
can also be used to generate synthetic seismograms for the laterally heterogeneous,
complex stratified reservoir models. The results show important frequency dependence
that may be useful for exploration.
Because turbidite channel systems often display complex vertical and lateral heterogeneity
that is difficult to measure directly, stochastic modeling is often used to predict the range of possible seismic responses. Though binary models containing
mixtures of sands and shales have been proposed in previous work, log measurements
show that these are not good representations of real seismic properties. Therefore,
I develop a new approach for generating stochastic turbidite models (STM) from a
combination of geological interpretation and well log measurements that are more realistic.
Calculations of the composite reflection coefficient and synthetic seismograms
predict direct hydrocarbon indicators associated with such turbidite sequences. The
STMs provide important insights to predict the seismic responses for the complexity
of turbidite reservoirs. Results of AVO responses predict the presence of gas saturation
in the sand beds. For example, as the source frequency increases, the uncertainty
in AVO responses for brine and gas sands predict the possibility of false interpretation
in AVO analysis. | en |
