Abstracts

Determining the distribution of porosity and permeability is one of the main challenges in carbonate petroleum reservoir characterization and requires a thorough understanding of pore type and origin, as well as their spatial distributions. Conventional studies of carbonate reservoirs require interpretation and analysis of cores to understand porosity.

This study investigates the use of NMR logs in the determination of pore type and origin. This study is based on the analysis of both thin section and NMR data from a single well that cored the Lower Cretaceous (Aptian) shelf carbonates belonging to the Shuaiba Formation of the Middle East . Photographs of thin sections were used to determine pore type and origin according to Ahr’s genetic classification of carbonate porosity. Descriptive statistics and modeling were used to analyze the NMR T2 relaxation time distributions. Descriptive statistics analysis included estimating arithmetic average, standard deviation, skewness, median, mode and 90th percentile. T2 modeling was performed by fitting multiple log-normal distributions to the measured T2 distribution. Data from thin section and from NMR were then compared using conditional probabilities.

As expected, thin section analysis revealed the predominance of mud-supported fabrics and associated matrix porosity. Vugs and dissolved rudistid fragments account for most of the macro-porosity. Descriptive statistics showed that mode and 90th iv percentile had the greatest discrimination power for pore origin. The first principal component (PC1) of the mode-90th percentile system was then used to compute the probabilities of having a each pore origin knowing that PC1 belongs to a given interval. Results were good, with each origin being predictable within a certain range of PC1.

Three modeling runs were performed using 1, 2 and 3 log-normal distributions. Samples of different pore origin behaved distinctively. Depositional porosity showed no increase in fit quality with increasing number of distributions whereas facies selective and diagenetic porosity did, with diagenetic porosity showing the greatest increase. Conditional probabilities would however difficult to apply to the modeling results.

ABSTRACT

Image Resolution Analysis: A New, Robust

Approach to Seismic Survey Design. (May 2004)

Constantinos Tzimeas, B.S., Aristotle University of Thessaloniki , Greece ; M.S., University of Leeds , U.K.

Chair of Advisory Committee: Dr. Richard L. Gibson, Jr.

Seismic survey design methods often rely on qualitative measures to provide an optimal image of their objective target. Fold, ray tracing techniques counting ray hits on binned interfaces, and even advanced 3-D survey design methods that try to optimize offset and azimuth coverage are prone to fail (especially in complex geological or structural settings) in their imaging predictions. The reason for the potential failure of these commonly used approaches derives from the fact that they do not take into account the ray geometry at the target points.

Inverse theory results can provide quantitative and objective constraints on acquisition design. Beylkin's contribution to this field is an elegant and simple equation describing a reconstructed point scatterer given the source/receiver distribution used in the imaging experiment. Quantitative measures of spatial image resolution were developed to assess the efficacy of competing acquisition geometries. Apart from the source/receiver configuration, parameters such as the structure and seismic velocity also influence image resolution. Understanding their effect on image quality, allows us to better interpret the resolution results for the surveys under examination.

A salt model was used to simulate imaging of target points located underneath and near the flanks of the diapir. Three different survey designs were examined. Results from these simulations show that contrary to simple models, near-offsets do not always produce better resolved images than far-offsets. However, consideration of decreasing signal-to-noise ratio revealed that images obtained from the far-offset experiment are degrading faster than the near-offset ones.

The image analysis was performed on VSP field data as well as synthetics generated by finite difference forward modeling. The predicted image resolution results were compared to measured resolution from the migrated sections of both the field data and the synthetics. This comparison confirms that image resolution analysis provides as good a resolution prediction as the prestack Kirchhoff depth migrated section of the synthetic gathers. Even in the case of the migrated field data, despite the presence of error introducing factors (different signal-to-noise ratios, shape and frequency content of source wavelets, etc.), image resolution performed well exhibiting the same trends of resolution changes at different test points.

The toxicity and adverse health effects of arsenic are widely known. It is generally accepted that sorption/desorption reactions with oxy-hydroxide minerals (iron, manganese) control the fate and transport of inorganic arsenic in surface waters through adsorption and precipitation-dissolution processes. In terrestrial environments with limited reactive iron, recent data suggest organoarsenicals are potentially important components of the biogeochemical cycling of arsenic in near-surface environments. Elevated arsenic levels are common in South Texas from geogenic processes (weathering of As-containing rock units) and anthropogenic sources (a byproduct from decades of uranium mining). Sediments collected from South Texas show low reactive iron concentrations, undetectable in many areas, making oxy-hydroxide controls on arsenic unlikely. Studies have shown that eukaryotic algae isolated from arsenic-contaminated waters have increased tolerance to arsenate toxicity and the ability to uptake and biotransform arsenate. In this experiment, net uptake of arsenic over time by a freshwater cyanobacterium never previously exposed to arsenate was quantified as a function of increasing As concentrations and increasing N:P ratios. Toxic effects were not evident when comparing cyanobacterial growth, though extractions indicate accumulation of intracellular arsenic by the cyanobacterium. Increasing N:P ratios has minimal effect on net arsenate uptake over an 18 day period. However, cyanobacteria were shown to reduce arsenate at rates faster than the system can re-oxidize the arsenic suggesting gross arsenate uptake may be much higher. Widespread arsenate reduction by cyanobacterial blooms would increase arsenic mobility and potential toxicity and may be useful as a biomarker of arsenic exposure in oxic surface water environments.