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.

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Thesis (M. Sc.)--University of Hong Kong, 1972. / Mimeographed.

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2003. / Includes bibliographical references (p. 65-66).

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This thesis gives an outline of the ionosphere and studies that were conducted to investigate / Thesis (M.Sc.) - University of KwaZulu-Natal, 2009.

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Research in incorporating natural fibers in composites has been in progress for a few decades where the various mechanical, electrical and acoustic properties of such composites were explored. Natural fiber composites (NFCs) have few benefits over the traditional glass or carbon fiber composites such as light weight, low manufacturing cost and requiring less energy for production. NFC is also bio-degradable and recyclable. The primary objectives of this research are to explore the static and dynamic properties of the hemp and linear low density polyethylene (LLDPE) and determine impact absorbing capability using the above mentioned properties. LLDPE is surface-treated with maleic anhydride grafted polyethylene (MA-g-PE) and sodium hydroxide (NaOH). A melt-mixing process is employed where LLDPE is compounded with the hemp fibers in 10%, 20% and 30% vol. fraction. Tensile and flexural properties are measured. The material is characterized by propagating Lamb waves generated using a dropped dead weight. Time-frequency information is extracted from a thin disc-like specimen using the Gabor Wavelet Transform (GWT) so as to characterize the material. Detection of defect is also established using the generated waves and GWT. Using Gabor wavelet coefficients, the dispersion and attenuation of the specimen are determined in different material directions. Comparison of attenuation of the waveforms is observed at different locations providing the knowledge of materials homogeneity, the materials behavior due to an impact and its impact absorbing character.