Análise do grau de proteção do Aquífero Barreiras em perímetros sob fertilização química a partir de dados hidrogeofísicos - área da bacia do Rio Catu-RN

The use of chemical fertilization in arable perimeters provides increased productivity, though it can eventually lead to a qualitative depreciation of groundwater sources, especially if such sources are unconfined in nature. In this context, this thesis presents results from an analysis of the level of natural protection of the Barreiras Aquifer in an area located on the eastern coast of the Rio Grande do Norte State - Brazil. Such an aquifer is clastic in nature and has an unconfined hydraulic character, which clearly makes it susceptible to contamination from surface ground loads with contaminants associated with the leaching of excess fertilizers not absorbed by ground vegetation. The methodology used was based on the use of hydro-geophysical data, particularly inverse models of vertical electrical soundings (VES) and information from well profiles, allowing the acquisition of longitudinal conductance cartographies (S), data in mili-Siemens (mS), and the vulnerability of the aquifer. Such maps were prepared with emphasis to the unsaturated overlying zone, highlighting in particular its thickness and occurrence of clay lithologies. Thus, the longitudinal conductance and aquifer vulnerability reveal areas more susceptible to contamination in the northeast and east-central sections of the study area, with values equal to or less than 10mS and greater than or equal to 0,50, respectively. On the other hand, the southwestern section proved to be less susceptible to contamination, whose longitudinal conductance and vulnerability indices are greater than or equal to 30mS and less than or equal to 0,40, respectively.

Análise do grau de proteção do Aquífero Barreiras em perímetros sob fertilização química a partir de dados hidrogeofísicos - área da bacia do Rio Catu-RN

The use of chemical fertilization in arable perimeters provides increased productivity, though it can eventually lead to a qualitative depreciation of groundwater sources, especially if such sources are unconfined in nature. In this context, this thesis presents results from an analysis of the level of natural protection of the Barreiras Aquifer in an area located on the eastern coast of the Rio Grande do Norte State - Brazil. Such an aquifer is clastic in nature and has an unconfined hydraulic character, which clearly makes it susceptible to contamination from surface ground loads with contaminants associated with the leaching of excess fertilizers not absorbed by ground vegetation. The methodology used was based on the use of hydro-geophysical data, particularly inverse models of vertical electrical soundings (VES) and information from well profiles, allowing the acquisition of longitudinal conductance cartographies (S), data in mili-Siemens (mS), and the vulnerability of the aquifer. Such maps were prepared with emphasis to the unsaturated overlying zone, highlighting in particular its thickness and occurrence of clay lithologies. Thus, the longitudinal conductance and aquifer vulnerability reveal areas more susceptible to contamination in the northeast and east-central sections of the study area, with values equal to or less than 10mS and greater than or equal to 0,50, respectively. On the other hand, the southwestern section proved to be less susceptible to contamination, whose longitudinal conductance and vulnerability indices are greater than or equal to 30mS and less than or equal to 0,40, respectively.

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis