Geostatistical and numerical simulation to predict the in situ chemical oxidation effectiveness

Published
2019-04-02
DOI: https://doi.org/10.14295/ras.v33i2.29282
Keywords: Remediation. In situ chemical oxidation. Stochastic models. Geostatistics. Numerical simualtion of flow and transport Remediação. Oxidação química in situ. Modelos estocásticos. Geoestatística. Simulação numérica de fluxo e transporte

    Authors

  • Elias Hideo Teramoto Laboratório de Estudos de Bacias (Lebac) -Unesp, Campus de Rio Claro, SP Centro de Estudos Ambientais (CEA), Unesp - Campus de Rio Claro, SP
  • Marco Aurélio Zequim Pede Laboratório de Estudos de Bacias (Lebac) -Unesp, Campus de Rio Claro/SP In Situ Remediation
  • Hung Kiang Chang Departamento de Geologia Aplicada - Unesp, Campus de Rio Claro, SP Laboratório de Estudos de Bacias (Lebac) -Unesp, Campus de Rio Claro,SP Centro de Estudos Ambientais (CEA), Unesp - Campus de Rio Claro,SP

Abstract

The efficiency of remediation systems such as chemical in situ oxidation (ISCO) is constrained by heterogeneities in the permeability. The uncertainties regarding to the presence of heterogeneities in aquifers in relation to successes of the remediation systems can be determined by means of stochastic simulations, although no such methodology has not been commonly employed for ISCO. Because this scenario, the goal of present work was to develop a methodological procedure to predict the efficiency of the in situ chemical oxidation remediation technique employing stochastic simulations and numerical simulations of flow and transport. In the simulated hypothetical cases, 30 equiprobable three-dimensional hydraulic conductivity random fields were generated and the remediation effectiveness was tested in all these scenarios. The results indicate that the proposed remediation system will be largely inefficient in 100% of cases, bring up the need for changes in the initial design, such as number of injection points and duration of injection. The high uncertainty degree in the assumed contamination scenario also suggests that further investigations are undertaken to reduce uncertainties and more realistic predictions.

How to Cite
Teramoto, E. H., Pede, M. A. Z., & Chang, H. K. (2019). Geostatistical and numerical simulation to predict the in situ chemical oxidation effectiveness. Águas Subterrâneas, 33(2), 134–145. https://doi.org/10.14295/ras.v33i2.29282