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An integrated study involving advanced seismic attribute and reservoir characterization tools in Macuspana Basin of Mexico provided an understanding of the structure, reservoir continuity, and quality of three mature reservoirs that optimized new drilling locations for exploration and development and generated a reservoir model for simulation purposes. Conventional and advanced technologies were integrated after a feasibility analysis to generate several attribute cubes over a 3D seismic volume; these included acoustic impedance, amplitude variation with offset (AVO), porosity derived from artificial neural network (ANN) schemes, and spectral decomposition. These attributes, added to the structural and stratigraphic analysis and to a J-function capillary pressure analysis, yielded information on compartmentalization that provided a geologic model to support reservoir delineation and characterization. Cobo, Bitzal, and Guiro fields are in Macuspana Basin, state of Tabasco, southeastern Mexico (Figure 1). The Cobo area, which includes the Cobo, Bitzal, and Guiro fields, is stratigraphically and structurally complex; its complexity is comparable to that of many other gas-producing fields in Macuspana Basin in which the dominant trap mechanisms vary from fault-assisted closures with a stratigraphic component to purely stratigraphic traps. The fields have produced gas for more than 20 years from a series of thin, principally Plio-Pleistocene sands thought to be fluvial-to-deltaic in origin. Cobo fields are cut by many NE-SW striking faults. Some northwest-dipping faults exhibit classic growth fault geometries; some show evidence for reactivation and inversion. This complexity, coupled with older well data, makes analysis using traditional exploration and reservoir characterization tools challenging. Figure 1. Map of Cobo area. Historically in Cobo fields, selection of well locations depended first on structural and stratigraphic analysis using limited 2D seismic; then, when 3D seismic became available, 3D seismic interpretation, detailed amplitude analysis, and AVO schemes were used as the basis for proposing new well sites. Amplitude, AVO, and resistivity measurements …

Abstract Conventional seismic inversion operates in the time domain and outputs relative impedances. Spectral inversion (Portniaguine and Castagna, 2005; Partyka, 2005) operates in the frequency domain where the spectrum of a local seismic response is taken to be a superposition of sinusoidal transfer functions associated with reflection coefficient pairs. Thus, the output time domain reflectivity series is a superposition of odd and even impulse functions. Widess (1957; reprinted in 1973) showed that odd impulse functions have a resolution limit of about 1/8th of a wavelength, below which the response is approximately the derivative of the seismic wavelet, irrespective of layer thickness. As an odd impulse pair thins below this limit, the peak frequency of the response remains relatively constant while the amplitude decreases almost linearly with thickness. According to this model, for layer thickness below 1/8th of a wavelength one cannot separate differences in reflection coefficient magnitude from changes in layer thickness (even in the absence of noise), and thus 1/8th of a wavelength is generally considered the limit of seismic resolution. However, for even impulse pairs, response frequency varies continuously with layer thickness and, in the absence of noise, layer thickness and reflection coefficient magnitude can both be precisely determined. Thus, for an isolated layer with an even component of reflectivity, resolution is nearly perfect in the absence of noise. Spectral inversion, by appropriately weighting odd and even components of reflection coefficient pairs, can thus achieve the best possible combination of resolution and robustness to noise. As is the case with all sparse-spike inversion methods, the output reflectivity series contains frequency components outside the band of the original seismic data. As the spectra of impulse pairs are sinusoids with infinite frequency content, in the absence of noise, all frequencies out to Nyquist can theoretically be recovered. In practice, in the presence of noise, the useful data bandwidth can often be increased by a factor of two or three. The broader the bandwidth of the original data, the more robust the process is against noise. By examining filter panels of the output reflectivity series, one can select the bandwidth that provides the most enhanced "spectrally broadened" image. Filtering back to the original bandwidth of the data reproduces the original data - the process is thus amplitude preserving and does not introduce "false" events. The spectral inversion method applied here requires no "starting model" and consequently makes no direct use of well information. The results are thus objective in the sense that they have not been biased by any interpretive input. Examples Case studies from Lake Maracaibo and the deep-water Gulf of Mexico illustrate the image improvement that results from such a process. It is important to note that in these case studies the only use of well control was in wavelet extraction and verification of results. No well information was incorporated into the inversion process. Figure 1 compares a conventional seismic section from Lake Maracaibo to a section spectrally broadened using spectral inversion. The increased frequency content (and corresponding improved resolution) after spectral broadening is obvious.

Three conserver agroecosystems emphasizing food self-sufficiency (a rural mountain homestead, a retrofitted suburban homesite, and a semiarid desert homestead) were selected for energy analysis. Energy diagrams were used to detail flows of renewable natural energy (sun and rain), fossil-fuel-based inputs, and food production. Energy inputs were considered in terms of equal work potential to permit comparisons of ratios between the relative contributions of natural and fuel-based inputs. Food production was expressed in a newly defined unit of equal nutritive value, the “nutritional equivalent kilocalorie”, based on the food’s protein quantity and quality and its caloric content. Energy ratios and indices were calculated, relating energy inputs, food production, and number of people supported. System inhabitants were found to observe a conserver lifestyle, consuming 12.5 to 25% as much total energy as the average United States inhabitant. Efficiency of food output per fossil fuel input on these homesteads is equal to or greater than that of the United States of America food system as a whole.