Browsing by Subject "genetic"
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Item A Modified Genetic Algorithm Applied to Horizontal Well Placement Optimization in Gas Condensate Reservoirs(2011-02-22) Morales, AdrianHydrocarbon use has been increasing and will continue to increase for the foreseeable future in even the most pessimistic energy scenarios. Over the past few decades, natural gas has become the major player and revenue source for many countries and multinationals. Its presence and power share will continue to grow in the world energy mix. Much of the current gas reserves are found in gas condensate reservoirs. When these reservoirs are allowed to deplete, the pressure drops below the dew point pressure and a liquid condensate will begin to form in the wellbore or near wellbore formation, possibly affecting production. A field optimization includes determining the number of wells, type (vertical, horizontal, multilateral, etc.), trajectory and location of wells. Optimum well placement has been studied extensively for oil reservoirs. However, well placement in gas condensate reservoirs has received little attention when compared to oil. In most cases involving a homogeneous gas reservoir, the optimum well location could be determined as the center of the reservoir, but when considering the complexity of a heterogeneous reservoir with initial compositional variation, the well placement dilemma does not produce such a simple result. In this research, a horizontal well placement problem is optimized by using a modified Genetic Algorithm. The algorithm presented has been modified specifically for gas condensate reservoirs. Unlike oil reservoirs, the cumulative production in gas reservoirs does not vary significantly (although the variation is not economically negligible) and there are possibly more local optimums. Therefore the possibility of finding better production scenarios in subsequent optimization steps is not much higher than the worse case scenarios, which delays finding the best production plan. The second modification is developed in order to find optimum well location in a reservoir with geological uncertainties. In this modification, for the first time, the probability of success of optimum production is defined by the user. These modifications magnify the small variations and produce a faster convergence while also giving the user the option to input the probability of success when compared to a Standard Genetic Algorithm.Item Biochemical and Genetic Characterization of Bacteriophage Holins(2013-11-06) To, Kam HoBacteriophages infect and kill bacterial cells. During the infection cycle, a phage attaches to the host cell surface, then ejects its DNA into the cytoplasm, where its progenies are subsequently assembled. The final step of the infection cycle is host cell lysis, which allows the progeny virions to escape into the environment. However, the timing of lysis, and thus the length of the infection cycle, is independent of endolysin biosynthesis and rather depends on the function of a second class of lysis proteins, the holins. Holins are small integral membrane proteins that accumulate harmlessly in the membrane during the infection cycle, until they suddenly form lethal lesions in the membrane at an allele-specific time. This membrane damage allows the endolysin to attack the cell wall. This dissertation focuses on several aspects of the structural and functional aspect of holins. First, Y is the putative holin gene of the paradigm coliphage P2. Although Y is not related to the S holin of phage lambda according to its primary structure, its characterization might prove useful in discerning the essential traits for holin function. In this instance, physiological and genetic approaches are utilized to show that Y exhibits the essential holin functional criteria, namely, allele-specific delayed-onset lethality and sensitivity to the energization of the membrane. These results suggest that class I holins share a set of unique features that are needed for their remarkable ability to program the end of the phage infection cycle with precise timing. Nevertheless, I report studies involving phenotypic analysis of a systematic library of clustered site-directed mutants of S105, and then conclude with experiments designed to probe the structure of the mature ?S-hole? in the membrane of the cell using chemical probes. Furthermore, I address whether the Y holin and the S21 pinholin of phage 21 effect membrane depolarization with the same all-or-nothing fashion as S while using the same tethered- cell assay previously employed for studying S. Finally, the holin and antiholin in Mu, one of the few paradigm coliphage, were identified and characterized. The introductory chapter is intended to serve as an update to the last major review on holin function in 2000.Item Genetic analysis of the Kemp's ridley sea turtle (Lepidochelys kempii) and estimates of effective population size(Texas A&M University, 2004-09-30) Stephens, Sarah HollandThe critically endangered Kemp's ridley sea turtle experienced a dramatic decline in population size (demographic bottleneck) between 1947 and 1987 from 160,000 mature individuals to less than 5000. Demographic bottlenecks can cause genetic bottlenecks where significant losses of genetic diversity occur through genetic drift. The loss of genetic diversity can lower fitness through the random loss of adaptive alleles and through an increase in the expression of deleterious alleles. Molecular genetic studies on endangered species require collecting tissue using non-invasive or minimally invasive techniques. Such sampling techniques are well developed for birds and mammals, but not for sea turtles. The first objective was to explore the relative success of several minimally invasive tissue-sampling methods as source of DNA from Kemp's ridley sea turtles. Tissue sampling techniques included; blood, cheek swabs, cloacal swabs, carapace scrapings, and a minimally invasive tissue biopsy of the hind flipper. Single copy nuclear DNA loci were PCR amplified with turtle-specific primers. Blood tissue provided the best DNA extractions. Additionally, archival plasma samples are shown to be good sources of DNA. However, when dealing with hatchlings or very small individuals in field situations, the tissue biopsy of the hind flipper is the preferred method. This study's main focus was to evaluate whether the Kemp's ridley sea turtle sustained a measurable loss of genetic variation resulting from the demographic bottleneck. To achieve this goal, three alternative approaches were used to detect a reduction in Kemp's ridley's effective population size (Ne) from microsatellite data. These approaches were 1) Temporal change in allele frequencies, 2)An excess of heterozygotes in progeny, and 3)A mean ratio (M) of the number of alleles (k) to the range of allele size (r). DNA samples were obtained from Kemp's ridleys caught in the wild. PCR was used to amplify eight microsatellite loci and allele frequencies were determined. Data from only four microsatellites could be used. Although the reduced number of loci was a limiting factor in this study, the results of all three approaches suggest that Kemp's ridley sustained a measurable loss of genetic variation due to the demographic bottleneck.Item Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms(2011-08-08) Gibbs, Trevor HowardHorizontal well placement determination within a reservoir is a significant and difficult step in the reservoir development process. Determining the optimal well location is a complex problem involving many factors including geological considerations, reservoir and fluid properties, economic costs, lateral direction, and technical ability. The most thorough approach to this problem is that of an exhaustive search, in which a simulation is run for every conceivable well position in the reservoir. Although thorough and accurate, this approach is typically not used in real world applications due to the time constraints from the excessive number of simulations. This project suggests the use of a genetic algorithm applied to the horizontal well placement problem in a gas reservoir to reduce the required number of simulations. This research aims to first determine if well placement optimization is even necessary in a gas reservoir, and if so, to determine the benefit of optimization. Performance of the genetic algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on reservoir recovery. The wells are constrained by surface gas rate and bottom-hole pressure for each case. This project's main new contribution is its application of using genetic algorithms to study the effect of well placement optimization in gas reservoirs. Two fundamental questions have been answered in this research. First, does well placement in a gas reservoir affect the reservoir performance? If so, what is an efficient method to find the optimal well location based on reservoir performance? The research provides evidence that well placement optimization is an important criterion during the reservoir development phase of a horizontal-well project in gas reservoirs, but it is less significant to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are an extremely efficient and robust tool to find the optimal location.