Background: This thesis explores the retirement behaviour of older people approaching retirement decisions. The research questions in focus deal with the attitudes toward work, the retirement preferences and the subjective well-being of the "youngest old", i.e. people aged 55–64. The included studies analyse the social determinants of these subjective evaluations and how they predict the timing of retirement and post-retirement well-being. Methods: In the included studies, methods are used that allow us to follow developments over time. Repeated cross-sectional analyses are employed to examine general developments pertaining to the older work force. These include OLS and logistic regression analysis. Longitudinal analyses are used to follow individual developments over time. These include Structural equation modelling and Cox regression analysis. Results: The results indicate that subjective evaluations such as attitudes to work and retirement preferences, as well as subjective well-being, are closely related to the structural conditions to which individuals are exposed, i.e. class position and work environment. The results also indicate that subjective evaluations such as preferred exit age and subjective well-being reported while in the work force are determinants of both the timing of retirement (in the case of preferred exit age and pre-retirement subjective well-being) and post-retirement subjective well-being (in the case of pre-retirement subjective well-being). Also, results indicate that recent policy changes in the Swedish pension systems are reflected in the retirement preferences of the older work force. A comparison of two time-points representing the incentive structure of the old and the new pension systems indicates that preferences were delayed with pension reform. Conclusion: The thesis contributes a temporal perspective to a research field that is dominated by research studying retirement behaviour at a single point of in time. The included studies underline the value of understanding retirement behaviour as a process rather than an isolated event. The way people evaluate their work, their well-being and their retirement prospects is intimately intertwined with their earlier experience. These subjective evaluations affect future retirement outcomes. Life course approaches offer illuminating tools for examining and explaining the significance of the biographies behind retirement behaviour. / Panel Survey of ageing and the elderly

Numerous studies have investigated the relationship between physical activity and physiological health (e.g., Burke et al., 2006; Irwin, 2004). Less attention has been paid to the contribution of physical activity on psychological well-being (Fox et al., 2000), and more specifically eudaimonic well-being, which reflects optimal psychological functioning and development at ones maximum potential (Ryff, 1989, 1995). This study investigated the role that health-enhancing physical activity (HEPA; any form of physical activity that benefits health and functional capacity; Miilunpalo et al., 2000) plays in eudaimonic well-being, which Ryff conceptualizes in terms of six dimensions: (1) Autonomy (i.e., being self-determined and independent); (2) Environmental Mastery (i.e., having a sense of mastery and competence in managing the environment); (3) Personal Growth (i.e., having a feeling of continued development); (4) Positive Relations with Others (i.e., having warm, satisfying, and trusting relationships with others); (5) Purpose in Life (i.e., having goals and a sense of direction in life); and, (6) Self-acceptance (i.e., possessing a positive attitude toward the self).<p> Employing Ryffs (1989, 1995) perspective of eudaimonic well-being, this study explored whether or not experiencing eudaimonia during HEPA moderates the relationship between HEPA and eudaimonic well-being. Additionally, it explored whether or not the relationship between experiencing eudaimonia during HEPA and eudaimonic well-being is mediated by basic need satisfaction. Undergraduate university students (N = 524; Mage = 20.7 years) completed an online survey including the Scales of Psychological Well-Being (Ryff & Keyes, 1995), the Short Questionnaire to Assess Health-enhancing Physical Activity (Wendel-Vos et al., 2003), the Hedonic and Eudaimonic Motives for Activity scale (Huta & Ryan, 2008), and the Psychological Need Satisfaction in Exercise Scale (Wilson, Rogers, et al., 2006). While level of HEPA was not significantly related to eudaimonic well-being (r = .05, p = .24), experiencing hedonia during HEPA (i.e., enjoying oneself, experiencing pleasure; r = .40, p < .01), experiencing eudaimonia during HEPA (r = .37, p < .01), and basic need satisfaction (r = .46, p < .01) were significantly related to eudaimonic well-being. Although experiencing eudaimonia during HEPA did not moderate the relationship between HEPA and eudaimonic well-being, experiencing eudaimonia during HEPA accounted for a significant 2.2% unique variance in eudaimonic well-being beyond HEPA and experiencing hedonia during HEPA (the full model accounted for a significant 18.2% of the variance in eudaimonic well-being).<p> Furthermore, the data were consistent with a model of partial mediation in that basic need satisfaction partially accounted for the relationship between experiencing eudaimonia during HEPA and eudaimonic well-being, supporting the proposition put forth by Ryan et al. (2008) that positive psychological well-being is a result of eudaimonic living that facilitates the satisfaction of our basic psychological needs. Findings from this study suggest that what appears to be significant in the relationship between HEPA and eudaimonic well-being is not the level of activity, but rather what is experienced during the activity. Future research may explore the directionality of the relationship by examining the extent to which eudaimonic well-being influences what is experienced during activity.

How are you today? The question was asked on a website by the artist Erik Krikortz, and the answers were displayed as a light show on a building complex in central Stockholm. In this thesis more than 20000 people have rated their subjective well-being on their own chosen occasions, on a seven graded scale of smileys in different colours. Results from November 2007 were analysed. The most frequently chosen colour was yellow, symbolising slightly better moods than average. Comparing means between days of the week showed that people feel the best on Sundays and are least happy on Tuesdays. Posthoc tests indicated significant dips in well-being on two days of the month. After answering the main question participants could also choose to rate their subjective experience of how well their sleep, family and friends, physical activity, stress levels and inspiration had been that day. The variables with the highest correlation with well-being were found to be “inspiration” and “family and friends”. Lowest were correlations for “sleep” and “physical activity”. The last variable was blank, for people to fill out for themselves and rate. The most frequently used word here was by far “love”, followed by “work” and “weather”. Summing up the results it seems social activities means most for the subjective well-being.

<p>Self-compassion has been shown to predict well-being, possibly by buffering people against the unpleasant emotional and cognitive reactions that accompany negative life events. Although most previous research has been conducted with young adults, preliminary studies show that self-compassion may be beneficial for older adults. Three studies tested self-compassion's impact on thoughts, emotions, and behaviors associated with aging using samples of individuals between the ages of 62 and 104. Study 1 examined self-compassion as it relates to health promotion behaviors, specifically use of assistance and trying new activities. Although some findings supported the hypotheses, results showed that high and low self-compassionate individuals did not differ in their use of assistance or willingness to try new activities. Study 2 implemented a brief self-compassion manipulation to test its effects on thoughts and emotions. Unfortunately, random assignment failed to equate the experimental conditions, rendering the results difficult to interpret. After controlling for baseline self-compassion, the manipulation did not have the predicted effects on well-being. In fact, participants seemed to benefit more when merely writing about negative events than when writing about them in a self-compassionate fashion. Finally, Study 3 examined self-compassionate cognitions, specifically whether or not self-compassionate thoughts mediate the relationship between trait self-compassion and emotional well-being. Self-compassionate participants did think differently than their low self-compassion counterparts, and these cognitions mediated the relationship between self-compassion and positivity of their responses. However, cognitions did not mediate the relationship between trait self-compassion and emotion outcomes. Two possible explanations for the unexpected results of the three studies include the relatively healthy nature of the sample and the strength of the self-compassion manipulation. Suggestions for future research include examining how self-compassion relates to the motivations behind engaging in health promotion, allowing participants to write more freely in the self-compassion manipulations, and bringing self-compassion research with older adults into controlled laboratory settings.</p> / Dissertation

The oil and gas industries use sophisticated logging tools during and after drilling. These logging tools employ internal electronics for sensing viscosity, pressure, temperature, and other important quantities. To protect the sensitive electronics, which typically have a maximum allowable temperature of 100 㬠they are shielded and insulated from the harsh external drilling environment. The insulation reduces the external heat input, but it also makes rejection of the heat generated within the electronics challenging. Electronic component failures promoted by elevated temperatures, and thermal stress, require a time consuming and expensive logging tool replacement process. Better thermal management of the electronics in logging tools promises to save oil and gas companies time and money. This research focuses on this critical thermal management challenge. Specifically, this thesis describes the design, fabrication, and test of an innovative thermal management system capable of cooling commercial-off-the-shelf electronics for extended periods in harsh ambient temperatures exceeding 200 㮠Resistive heaters embedded in quad-flat-packages simulate the electronics used in oil well logging. A custom high temperature oven facilitates the evaluation of a full scale prototype of the thermal management system. We anticipate the prototype device will validate computer modeling efforts on which its design was based, and advance future designs of the thermal management system.

To increase the successful rate of acid stimulation, a method is required to diagnose the effectiveness of stimulation which will help us to improve stimulation design and decide whether future action, such as diversion, is needed. For this purpose, it is important to know how much acid enters each layer in a multilayer carbonate formation and if the low-permeability layer is treated well. This work develops a numerical model to determine the temperature behavior for both injection and flow-back situations. An important phenomenon in this process is the heat generated by reaction, affecting the temperature behavior significantly. The result of the thermal model showed significant temperature effects caused by reaction, providing a mechanism to quantitatively determine the acid flow profile. Based on this mechanism, a further inverse model can be developed to determine the acid distribution in each layer.

Predicting rock permeability from well logs in uncored wells is an important task in reservoir characterization. Due to the high costs of coring and laboratory analysis, typically cores are acquired in only a few wells. Since most wells are logged, the common practice is to estimate permeability from logs using correlation equations developed from limited core data. Most commonly, permeability is estimated from various well logs using statistical regression. For sandstones, often the logs of permeability can be correlated with porosity, but in carbonates the porosity permeability relationship tends to be much more complex and erratic. For this reason permeability prediction is a critical aspect of reservoir characterization in complex reservoirs such as carbonate reservoirs. In order to improve the permeability estimation in these reservoirs, several statistical regression techniques have already been tested in previous work to correlate permeability with different well logs. It has been shown that statistical regression for data correlation is quite promising in predicting complex reservoirs. But using all the possible well logs to predict permeability is not appropriate because the possibility of spurious correlation increases if you use more well logs. In statistics, variable selection is used to remove unnecessary independent variables and give a better prediction. So we apply variable selection to the permeability prediction procedures in order to further improve permeability estimation. We present three approaches to further improve reservoir permeability prediction based on well logs via data correlation and variable selection in this research. The first is a combination of stepwise algorithm with ACE technique. The second approach is the application of tree regression and cross-validation. The third is multivariate adaptive regression splines. Three methods are tested and compared at two complex carbonate reservoirs in west Texas: Salt Creek Field Unit (SCFU) and North Robertson Unit (NRU). The result of SCFU shows that permeability prediction is improved by applying variable selection to non-parametric regression ACE while tree regression is unable to predict permeability because it can not preserve the continuity of permeability. In NRU, none of these three methods can predict permeability accurately. This is due to the high complexity of NRU reservoir and measurement accuracy. In this reservoir, high permeability is discrete from low permeability, which makes prediction even more difficult. Permeability predictions based on well logs in complex carbonate reservoirs can be further improved by selecting appropriate well logs for data correlation. In comparing the relative predictive performance of the three regression methods, the stepwise with ACE method appears to outperform the other two methods.

Horizontal wells are drilled to achieve improved reservoir coverage, high production rates, and to overcome water coning problems, etc. Many of these wells often produce at rates much below the expected production rates. Low productivity of horizontal wells is attributed to various factors such as drilling induced formation damage, high completion skins, and variable formation properties along the length of the wellbore as in the case of heterogeneous carbonate reservoirs. Matrix acidizing is used to overcome the formation damage by injecting the acid into the carbonate rock to improve well performance. Designing the matrix acidizing treatments for horizontal wells is a challenging task because of the complex process. The estimation of acid distribution along wellbore is required to analyze that the zones needing stimulation are receiving enough acid. It is even more important in cases where the reservoir properties are varying along the length of the wellbore. A model is developed in this study to simulate the placement of injected acid in a long horizontal well and to predict the subsequent effect of the acid in creating wormholes, overcoming damage effects, and stimulating productivity. The model tracks the interface between the acid and the completion fluid in the wellbore, models transient flow in the reservoir during acid injection, considers frictional effects in the tubulars, and predicts the depth of penetration of acid as a function of the acid volume and injection rate at all locations along the completion. A computer program is developed implementing the developed model. The program is used to simulate hypothetical examples of acid placement in a long horizontal section. A real field example of using the model to history match actual treatment data from a North Sea chalk well is demonstrated. The model will help to optimize acid stimulation in horizontal wells.

Multiple transverse fracturing along a horizontal well is a relatively new technology that is designed to increase well productivity by increasing the contact between the reservoir and the wellbore. For multiple transverse fractures, the performance of the well system is determined by three aspects: the inflow from the reservoir to the fracture, the flow from the fracture to the wellbore, and the inflow from the reservoir to the horizontal wellbore. These three aspects influence each other and combined, influence the wellbore outflow. In this study, we develop a model to effectively formulate the inter-relationships of a multi-fracture system. This model includes a reservoir model and a wellbore model. The reservoir model is established to calculate both independent and inter-fracture productivity index to quantify the contribution from all fractures on pressure drop of each fracture, by using the source functions to solve the single-phase gas reservoir flow model. The wellbore model is used to calculate the pressure distribution along the wellbore and the relationship of pressure between neighboring fractures, based on the basic pressure drop model derived from the mechanical energy balance. A set of equations with exactly the same number of fractures will be formed to model the system by integrating the two models. Because the equations are nonlinear, iteration method is used to solve them. With our integrated reservoir and wellbore model, we conduct a field study to find the best strategy to develop the field by hydraulic fracturing. The influence of reservoir size, horizontal and vertical permeability, well placement, and fracture orientation, type (longitudinal and transverse), number and distribution are completely examined in this study. For any specific field, a rigorous step-by-step procedure is proposed to optimize the field.

This work of well performance modeling is focused on solving problems of transient and pseudo-steady state fluid flow in a rectilinear closed boundaries reservoir. This model has been applied to predict and to optimize gas production from a horizontal well intercepted by multiple transverse fractures in a bounded reservoir, and it also provides well-testing solutions. The well performance model is designed to provide enhanced efficiency with the same reliability for pressure transient analysis, and well performance prediction, especially in complex well fracture configuration. The principle is to simplify the calculation of the pressure response to an instantaneous withdraw, which happens in other fractures, within a shorter computational time. This pressure response is substituted with the interaction between the two whole fractures. This method is validated through comparison to results of rigorous Distributed Volumetric Sources (DVS) method in simple symmetric fracture configuration, and to results of field production data for complex well/fracture configuration of a tight gas reservoir. The results show a good agreement in both ways. This model indicates the capability to handle the situations, such as: various well drainages, asymmetry of the fracture wings, and curved horizontal well. The advantage of this well performance model is to provide faster processing - reducing the computational time as the number of fractures increase. Also, this approach is able to be applied as an optimization and screening tool to obtain the best fracture configurations for reservoir development of economically marginal fields, in terms of the number and dimensions of fractures per well, also with external economic and operational constraints.