Seismic attribute expression of fluvial-deltaic and turbidite systems

Much of the world's conventional oil and gas production comes from uvial deltaic and turbidite reservoirs. The ability to accurately interpret the architectural elements comprising these systems greatly reduces the risk in exploration and development in these environments. In addition to clastic environments, turbidites can also occur in carbonate environments, and formations of this type pose signi cant unanswered questions. In this dissertation, I demonstrate methods for using attributes to improve the interpretation in fluvial deltaic using data from Middle Pennsylvanian age Red Fork Formation of Oklahoma and the Oligecene-Miocene age Frio Formation of south Texas. I show how spectral phase and magnitude attributes can be effectively combined using an HSV color map to produce images that have considerable interpretational value. I develop an interactive method using the skill of the interpreter to blend attributes dynamically. I also apply a statistical technique to integrate multiple attributes in a non-linear manner. Incorporating my methods in the interpretation process has the potential to improve the exploration and development in these systems. I also look at the problem of mapping channel-forms the hybrid carbonate turbidite Oliogence age Mandu Formation in the Carnarvon Basin of Australia. I show how attributes tie to the geological features of the architectural elements. I demonstrate the capability to extract in 3-D the associated channel-forms. Further analysis using these methods has the potential to increase our understanding of how turbidites form in carbonate environments

Dynamic Thermal Structure of Imported Fire Ant Mounds

A study was undertaken to characterize surface temperatures of mounds of imported fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae) and S. richteri Forel, and their hybrid, as it relates to sun position and shape of the mounds, to better understand factors that affect absorption of solar radiation by the nest mound and to test feasibility of using thermal infrared imagery to remotely sense mounds. Mean mound surface temperature peaked shortly after solar noon and exceeded mean surface temperature of the surrounding surface. Temperature range for mounds and their surroundings peaked near solar noon, and the temperature range of the mound surface exceeded that of the surrounding area. The temperature difference between mounds and their surroundings peaked around solar noon and ranged from about 2 to 10°C. Quadratic trends relating temperature measurements to time of day (expressed as percentage of daylight hours from apparent sunrise to apparent sunset) explained 77 to 88% of the variation in the data. Mounds were asymmetrical, with the apex offset on average 81.5 ± 1.2 mm to the north of the average center. South facing aspects were about 20% larger than north facing aspects. Mound surface aspect and slope affected surface temperature; this affect was greatly influenced by time of day. Thermal infrared imagery was used to illustrate the effect of mound shape on surface temperature. These results indicate that the temperature differences between mounds and their surroundings are sufficient for detection using thermal infrared remote sensing, and predictable temporal changes in surface temperature may be useful for classifying mounds in images

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

A Genetic Algorithm for Best Subset . . .

Given a data set consisting of a large number of predictors plus a response, the problem addressed in this work is to select a minimal model which correctly predicts the response. Methods for achieving this subsetting of the predictors have been the topic of a considerable amount of study within the statistics community. Unfortunately, current methods often fail when the predictors are highly correlated. Furthermore, because of the exponential growth of the number of possible subsets as the number of candidate predictors increase, current methods have great difficulty handling high dimensional data sets. This paper details a method for variable selection using genetic algorithms. A genetic algorithm is described which uses a unique two criteria population management scheme. This method is explorative in nature, and allows for an approximation of the all possible subsets method over a set of interesting model sizes. Results of an application of this method to data are discussed. 1. INTR..

A Matrix Representation for Genetic Algorithms

Many problems have a structure with an inherently two (or higher) dimensional nature. Unfortunately, the classical method of representing problems when using Genetic Algorithms (GAs) is of a linear nature. We develop a genome representation with a related crossover mechanism which preserves spatial relationships for two dimensional problems. We then explore how crossover disruption rates relate to the spatial structure of the problem space. After discussing why a more appropriate representation is needed and exploring the theoretical aspects of our method, we empirically test our method to verify that it will be effective. We develop an easily understood abstracted class of problems with a two dimensional structure. A Monte Carlo study comparing the GAs using the string and matrix methods on a number of members of this problem class is then conducted. Results are presented which clearly show that for this particular problem, a matrix oriented GA should be used. Given our success in app..