DOI: 10.20868/upm.thesis.51678
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Environmental risks associated with flowback and produced waters in shale gas projects

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Cited by 1 publication
(2 citation statements)
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“…However, information from existing exploitations can serve as guides. Here we estimated the expected concentrations of pollutants in the storage tank on the basis of: the forecasting volume of return water, calculated using the values coming from an experimental database [Hayes, 2009] adjusting according an empirical expression [Ma, 2018]; and the contaminant concentration in this water, calculated by a predictive model which assess their evolution that has been adjusted from experimental data [Ma et al, 2018]. This information is very useful in the first management phases of the return waters, and will serve as a basis for further design of safety plans that include the monitoring and development of mitigation measures.…”
Section: Chemical Concentration In the Storage Tankmentioning
confidence: 99%
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“…However, information from existing exploitations can serve as guides. Here we estimated the expected concentrations of pollutants in the storage tank on the basis of: the forecasting volume of return water, calculated using the values coming from an experimental database [Hayes, 2009] adjusting according an empirical expression [Ma, 2018]; and the contaminant concentration in this water, calculated by a predictive model which assess their evolution that has been adjusted from experimental data [Ma et al, 2018]. This information is very useful in the first management phases of the return waters, and will serve as a basis for further design of safety plans that include the monitoring and development of mitigation measures.…”
Section: Chemical Concentration In the Storage Tankmentioning
confidence: 99%
“…Based on the experimental data of volumes (Table 1 at 1, 5, 14 and 90 days) from the horizontal wells [Hayes, 2009], an empirical expression for modelling the evolution of the volume of return water is given in Eq. (3) [Ma, 2018]…”
Section: Return Water Volume Modelmentioning
confidence: 99%