Attribute analysis of seismic and GPR data for diagnosis of subsurface hydrocarbon contamination

• Grant number: 06/01350-1
• Support Opportunities: Regular Research Grants
• Start date: September 01, 2006
• End date: August 31, 2008
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Geophysics
• Principal Investigator: Renato Luiz Prado
• Grantee: Renato Luiz Prado
• Host Institution: Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The contamination of ground water and soils by hydrocarbons and their derivates usually occurs by spill and other accidents during exploration, refinement, leak, transportation, and storage operations. The analysis and diagnosis of hydrocarbon contamination by seismic reflection method and ground penetrating radar is based on the changes in physical, chemical, hydraulic and hydrogeochemical properties of the geological materials due to the presence of contaminant. Changes in dielectric permitivity, electrical conductivity, velocity and density can be detected by those geophysical methods.This project purposes to study the amplitude attribute of the reflected seismic and electromagnetic waves in hydrocarbon contaminated areas. This proposal is original because aim to integrate the AVO (Amplitude Variation with Offset) analysis of two different kind of waves and focus on the LNAPL (Light nonaqueous phase liquids) contaminant. The bibliography about this theme shows study cases in which the only parameter is the geophysical image, that is, the geophysical methods are a qualitative indicator. The empirical character and the huge ambiguity of this procedure leads the researches to more analytical studies. According to some studies there is a decrease in reflection wave amplitude with the thickness increasing of LNAPL contaminant.This research will be accomplished in a chemical industry site, in São Paulo city, in which there are already an extensive contamination diagnosis (type, extension, and percolation time). Models of contaminated flow will be achieved in order to give support to geophysical data interpretation, and to modeling seismic and electromagnetic signals. (AU)