The focus of this research is to develop and extend the application of existing technologies to enhance seismic reservoir characterization. The chapters presented in this dissertation constitute five individual studies consisting of three applications of the Radon transform, one aspect of acoustic wave propagation, and a pilot study of generating a stochastic reservoir model.
The first three studies focus on the use of the Radon transform to enhance surface-recorded, controlled-source seismic data. First, the use of this transform was extended to enhance diffraction patterns, which may be indicative of subsurface fractures. The geometry of primary reflections and diffractions on synthetic common-shot-gather data indicate that Radon filters can predict and model primary reflections upon inverse transformation. These modeled primaries can then be adaptively subtracted from the input gather to enhance the diffractions. Second, I examine the amplitude distortions at near and far offsets caused by free-surface multiple removal using Radon filters. These amplitudes are often needlessly reduced due to a truncation effect when the commonly used, unweighted least-squares solution is applied. Synthetic examples indicate that a weighted solution to the transformation minimizes this effect and preserves the reflection amplitudes. Third, a novel processing flow was developed to generate a stacked seismic section using the Radon transform. This procedure has the advantage over traditional summation of normal moveout corrected common midpoint gathers because it circumvents the need to perform manual and interpretive velocity analysis.
The fourth study involves the detection of thin layers in periodic layerstacks. Numerical modeling of acoustic wave propagation suggests that the sinusoidal components of an incident signal with a wavelength that corresponds to the periodicity of the material be preferentially reflected. Isolating the different portions of the reflected wavefield and calculating the energy spectra may provide evidence of thin periodic layers which are deterministically unresolvable on their own.
Object-based reservoir modeling often incorporates the use of lithology logs, deterministic seismic interpretation, architectural element analysis, geologic intuition, and modern and outcrop analogs. This last project consists of a pilot study where a more quantitative approach to define the statistical parameters currently derived through geologic intuition and analogs was developed. This approach utilizes a simulated annealing optimization technique for inversion and the pilot study shows that it can improve the correlation between synthesized and control logs. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/29691 |
| Date | 03 February 2005 |
| Creators | Nowak, Ethan J. |
| Contributors | Geosciences, Imhof, Matthias G., Snoke, J. Arthur, Coruh, Cahit, Mikulich, Matthew, Castle, James W. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | ejn-th5.2.pdf |
Page generated in 0.0026 seconds