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New mathematical method aids water prospecting and dam security


Wholesome dam. Credit: Pavel Odinev/Skoltech

Scientists from Skoltech and St. Petersburg State University have proposed a mathematical methodology for deciphering knowledge on underground water flows. The brand new approach is extra environment friendly and gives extra accuracy in imaging fluids for planning building works, inspecting dams for integrity, and finding water reservoirs for agriculture and personal consumption in dry areas. The research is revealed in IEEE Transactions on Geoscience and Distant Sensing.

Detecting subsurface water flows is vital for building security, dam monitoring, and groundwater prospecting. Underground fluid flows represent a hazard for the inspiration components of buildings and subway methods, in addition to an early warning of an impending dam breach. In dry climates, reminiscent of in Spain, Israel, Australia, or the south of Russia, figuring out the place water flows beneath the bottom affords a approach to faucet into this useful resource for agricultural, industrial, and personal wants.

The previous decade has seen the rise of a brand new strategy to underground water flow imaging: self-potential mapping. The underlying premise is that as water seeps by means of porous rock, it generates electrical potential, which signifies its presence.

The primary problem with self-potential mapping is that whereas researchers can reliably decide up these electrical alerts, making sense of them and localizing precise underground flows has proved difficult. Till now, no passable mathematical method has been out there for processing massive quantities of self-potential knowledge for areas with tough terrain.

Within the latest paper in IEEE TGRS, a Russian analysis crew from Skoltech and St. Petersburg State proposed such a way. It’s able to quickly processing many measurements and exactly accounting for the advanced geometry of the studied area. The latter is especially vital for figuring out dam breaches, as a result of dam geometry strongly impacts {the electrical} potential.

“The ultimate result is that the method greatly improves the quality of geophysical interpretation,” the research’s first creator, Mikhail Malovichko of Skoltech, commented. “Technically speaking, we are increasing the accuracy of the inverse problem. Considering the improvement in subsurface imaging, we believe this approach has great potential within the industry.”


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Extra data:
M.S. Malovichko et al, Utility of optimum management to inversion of self-potential knowledge: concept and artificial examples, IEEE Transactions on Geoscience and Distant Sensing (2021). DOI: 10.1109/TGRS.2021.3121538

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New mathematical methodology aids water prospecting and dam safety (2022, January 11)
retrieved 11 January 2022
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