Recent U.S. legislation applies a precautionary approach to setting catch regulations in federal fisheries management. A transparent approach to complying with federal guidelines involves calculating the catch recommendation that corresponds to a specified probability, P*, of exceeding the "true" overfishing limit (OFL) located within an estimated distribution. The P* methodology aims to manage the risk of overfishing explicitly, but choice of P* alone does not provide sufficient information on all of the risks associated with a control rule—both the probability of overfishing and the severity of overfishing. Rather, the ramifications of P* choices depend on the amount of uncertainty in the stock assessment and on the life history of the species in question. To evaluate these effects on the risks associated with P* rules, my study simulated fishing three example species under three levels of uncertainty. Trends identified among example species were consistent with predictions from life history. Periodic strategists, which have highly variable recruitment, experienced probabilities of overfishing which exceeded P* and which increased in time. Equilibrium strategists showed more predictable risks of overfishing but may have less capacity to recover from depleted biomass levels. Differences in the size of the OFL distribution—representing differences in levels of uncertainty—led to mixed results depending on whether the distribution was biased or whether uncertainty was fully characterized. Lastly, because OFL distributions are themselves estimates and subject to uncertainty in their shape and size, lower P* values closer to the tails of the estimated distribution produced more variable resulting risks. / Master of Science

Cattle ranching in Vermilion Parish is a social-techno-ecological system (STES) that is currently vulnerable due to changing social, technological and ecological conditions. In addressing ways to increase the adaptive capacity of cattle ranching in Vermilion Parish, I used a multiple, mixed method approach grounded in a critical constructivist framework. Constructivism is the idea that our relationship to facts is constructed by our social context. It is these perceptions that shape people’s actions. By looking at these perceptions through an emancipatory frame I was able to understand multiple interpretations of meaning, consciously address them, consider how they may have shaped our actions, and then alter those meanings and power relationships. In an effort to increase the adaptive capacity of cattle ranching in Vermilion Parish, my research focused on actions, why people perform those actions, and how to change them. This research connected the physical landscape of the marshes, the individual landscape of perception, and the conceptual landscape of resilience. If resilience is the ability of a system (cattle ranching in vermilion parish) to recover after a disturbance, adaptive capacity is when the actors within the system can influence that system’s resilience. I explored the history of cattle ranching in Vermilion Parish from three different, but overlapping perspectives – environmental, social, and technological. These perspectives compliment the information from interviews and 3CM sessions. These 15 interviews revealed the perception of 11 types of threats facing cattle ranching in Vermilion Parish. The body of literature surrounding resilience theory identifies traits of highly adaptive systems. The recommendations and suggestions outlined in Chapter 6 exist at the intersection of the actors’ perception of specific threats and the decidedly generalized traits of highly adaptive systems. These suggestions were geared towards increasing the adaptive capacity of cattle ranching in Vermilion Parish. Given these layered landscapes and their complexity, my recommendations were subject to feedback loops and long periods of integration. These recommendations contribute to the theoretical foundation detailed in Chapter 3 by identifying specific ways that the actors of this particular system may be able increase their own adaptive capacity. / text

The quantitative estimation of reservoir properties directly from seismic data is a major goal of reservoir characterization. Integrated reservoir characterization makes use of different varieties of well and seismic data to construct detailed spatial estimates of petrophysical and fluid reservoir properties. The advantage of data integration is the generation of consistent and accurate reservoir models that can be used for reservoir optimization, management and development. This is particularly valuable in mature field settings where hydrocarbons are known to exist but their exact location, pay, lateral variations and other properties are poorly defined. Recent approaches of reservoir characterization make use of individual seismic attributes to estimate inter-well reservoir properties. However, these attributes share a considerable amount of information among them and can lead to spurious correlations. An alternative approach is to evaluate reservoir properties using multiple seismic attributes. This study reports the results of an investigation of the use of multivariate seismic attributes to predict lateral reservoir properties of gross thickness, net thickness, gross effective porosity, net-to-gross ratio and net reservoir porosity thickness product. This approach uses principal component analysis and principal factor analysis to transform eighteen relatively correlated original seismic attributes into a set of mutually orthogonal or independent PC??s and PF??s which are designated as multivariate seismic attributes. Data from the N-sand interval of Vermilion Block 50 field, Gulf of Mexico, was used in this study. Multivariate analyses produced eighteen PC??s and three PF??s grid maps. A collocated cokriging geostaistical technique was used to estimate the spatial distribution of reservoir properties of eighteen wells penetrating the N-sand interval. Reservoir property maps generated by using multivariate seismic attributes yield highly accurate predictions of reservoir properties when compared to predictions produced with original individual seismic attributes. To the contrary of the original seismic attribute results, predicted reservoir properties of the multivariate seismic attributes honor the lateral geological heterogeneities imbedded within seismic data and strongly maintain the proposed geological model of the N-sand interval. Results suggest that multivariate seismic attribute technique can be used to predict various reservoir properties and can be applied to a wide variety of geological and geophysical settings.

The quantitative estimation of reservoir properties directly from seismic data is a major goal of reservoir characterization. Integrated reservoir characterization makes use of different varieties of well and seismic data to construct detailed spatial estimates of petrophysical and fluid reservoir properties. The advantage of data integration is the generation of consistent and accurate reservoir models that can be used for reservoir optimization, management and development. This is particularly valuable in mature field settings where hydrocarbons are known to exist but their exact location, pay, lateral variations and other properties are poorly defined. Recent approaches of reservoir characterization make use of individual seismic attributes to estimate inter-well reservoir properties. However, these attributes share a considerable amount of information among them and can lead to spurious correlations. An alternative approach is to evaluate reservoir properties using multiple seismic attributes. This study reports the results of an investigation of the use of multivariate seismic attributes to predict lateral reservoir properties of gross thickness, net thickness, gross effective porosity, net-to-gross ratio and net reservoir porosity thickness product. This approach uses principal component analysis and principal factor analysis to transform eighteen relatively correlated original seismic attributes into a set of mutually orthogonal or independent PC??s and PF??s which are designated as multivariate seismic attributes. Data from the N-sand interval of Vermilion Block 50 field, Gulf of Mexico, was used in this study. Multivariate analyses produced eighteen PC??s and three PF??s grid maps. A collocated cokriging geostaistical technique was used to estimate the spatial distribution of reservoir properties of eighteen wells penetrating the N-sand interval. Reservoir property maps generated by using multivariate seismic attributes yield highly accurate predictions of reservoir properties when compared to predictions produced with original individual seismic attributes. To the contrary of the original seismic attribute results, predicted reservoir properties of the multivariate seismic attributes honor the lateral geological heterogeneities imbedded within seismic data and strongly maintain the proposed geological model of the N-sand interval. Results suggest that multivariate seismic attribute technique can be used to predict various reservoir properties and can be applied to a wide variety of geological and geophysical settings.