masterThesis
Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo
Fecha
2009-04-22Registro en:
COSTA, Kleber Carlos de Oliveira. Análise de DFA e de agrupamento do perfil de
densidade de poços de petróleo. 2009. 190 f. Dissertação (Mestrado em Pesquisa e Desenvolvimento em Ciência e Engenharia de Petróleo) - Universidade Federal do Rio Grande do Norte, Natal, 2009.
Autor
Costa, Kleber Carlos de Oliveira
Resumen
In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This
technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the
second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure.
Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data
generated by the k-means method shows spatial patterns, we create the parameter Ω
(index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means