Comparação da análise de diferentes perfis de poços pelo método DFA

The study of complex systems has become a prestigious area of science, although relatively young . Its importance was demonstrated by the diversity of applications that several studies have already provided to various fields such as biology , economics and Climatology . In physics , the approach of complex systems is creating paradigms that influence markedly the new methods , bringing to Statistical Physics problems macroscopic level no longer restricted to classical studies such as those of thermodynamics . The present work aims to make a comparison and verification of statistical data on clusters of profiles Sonic ( DT ) , Gamma Ray ( GR ) , induction ( ILD ) , neutron ( NPHI ) and density ( RHOB ) to be physical measured quantities during exploratory drilling of fundamental importance to locate , identify and characterize oil reservoirs . Software were used : Statistica , Matlab R2006a , Origin 6.1 and Fortran for comparison and verification of the data profiles of oil wells ceded the field Namorado School by ANP ( National Petroleum Agency ) . It was possible to demonstrate the importance of the DFA method and that it proved quite satisfactory in that work, coming to the conclusion that the data H ( Hurst exponent ) produce spatial data with greater congestion . Therefore , we find that it is possible to find spatial pattern using the Hurst coefficient . The profiles of 56 wells have confirmed the existence of spatial patterns of Hurst exponents , ie parameter B. The profile does not directly assessed catalogs verification of geological lithology , but reveals a non-random spatial distribution

Bem-estar psicológico de servidores e funcionários técnico-administrativos das Instituições de Ensino Superior Públicas e Privadas : indicadores e antecedentes

The elaboration of this thesis aimed at getting to know the structure of the psychological well-being (PWB) at work and analysing the differences in the PWB levels among technical-administrative servants in public and private Institutions of Higher Education (IES) in the municipality of João Pessoa. Two hundred and thirty-three public and private IES male and female servants of João Pessoa participated in the research, replying to an instrument composed of questionnaires referring to the elaborated model. Factorial and regression analyses were accomplished in order to test the hypotheses in respect of the proposed model. The results showed that the PWB related with the work is composed of indicators such as affection, vitality, anxiety, depression, satisfaction at work and aspiration for accomplishment and reduction of the self-efficiency. The observed PWB predictors at work were the IES type, presence of children, age and the escape and back-out facing strategy. These predictors possess relationship of moderation among them in the explanation of PWB. On comparing the PWB experienced by the technical-administrative servants, it was observed that those linked to private IES showed higher PWB rates. Furthermore, there are differences among PWB predictors in accordance with the IES type. The applicability of the results of this thesis is wide as regards social interventions in the search of health improvement under a psycho-sociological perspective. Eventually, the thematic of this thesis intends to reinforce the studies on the worker s health, since by knowing what would lead him into a feeling of accomplishment and well-being will result in more chances of promoting him, while creating opportunities of a sounder life for these people in psychological terms

Resiliência e socialização organizacional de novos servidores: um estudo transcultural

The main aim of the study was to analyze the relationship between resilience and organizational socialization among newcomers from the Federal University of Rio Grande do Norte (UFRN), and the Norwegian University of Science and Technology (NTNU), comparing the results obtained in a cross-cultural perspective. The sample (N=205) was composed of mentored (N=70) and non-mentored (N=72) professors and technical-administrative employees at UFRN, and their non-mentored counterparts at NTNU (N=63). The data collection instruments used were the Organizational Socialization Inventory (OSI), the Resilience Scale for Adults (RSA) and a sociodemographic form. Data analysis was preceded by a number of tests to verify possible distinct response styles among the respondents, as they came from different cultures. Descriptive analysis and t-tests were performed to identify and compare organizational socialization and resilience outcomes. Hierarchical regression analyses were carried out, the first ones involving all participants (N=205), to observe the predictive power of resilience factors in relation to organizational socialization factors, beyond the effects of nationality, occupation and mentoring experience. The other hierarchical regression analyses were conducted separately for the professors (N=109) and technical-administrative employees (N=96); and for the mentored (N=70) and non-mentored newcomers from UFRN (N=72), and nonmentored newcomers from NTNU (N=63), to compare the predictive power of resilience in relation to organizational socialization between newcomers from the two occupations, and also among the three groups of participants. The results of this study showed that socialization and resilience profiles differed according to demographic and cultural characteristics, and to the socialization strategies adopted in the institutions studied. Furthermore, it was observed that resilience added a significant incremental prediction to all socialization factors, beyond nationality, occupation, and mentoring experience. The predictive contribution from each of the resilience factors was also noteworthy, mainly those of Planned Future and Social Resources. With respect to nationality, occupation and mentoring experience, it was noted that they explained a significant part of the variance in almost all organizational socialization factors, in addition to playing a meaningful role in predicting the scores of such factors, with some evidence of moderation or mediation by the resilience factors. Considering these and the comparative results of the predictive power of resilience in relation to the organizational socialization, between the two occupations and among the three groups of participants, as a whole, the main findings of this study were as follows: resilience tends to contribute to organizational socialization outcomes; the resilience of some subjects may be a differential factor for success in those situations in which individuals face working conditions that are less favorable to promoting their adaptation; and, a formal mentoring program may contribute to improving newcomer resilience, producing better and more homogeneous organizational socialization outcomes. The practical implications, limitations and main contributions of the study are discussed, with a number of suggestions for future research

DFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poços de petróleo

Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution