Use of Signal Processing to Study Internal Erosion in Porous Media

Internal erosion is considered to be a major cause of flooding in earth dams. Though the mechanism of initiation is well defined (i.e. suffusion, backward erosion, contact erosion and concentrated leak), the ability to detect it and prevent catastrophes from happening is still being investigated. This study focuses on backward erosion also known as piping. It aims at using geophysical techniques, mainly seismic, to monitor water seepage in porous media and detect the initiation of backward erosion in a controlled environment. For this purpose, a laboratory setup was built to better understand the effect of piping evolution on the seismic response. The seismic activity was monitored in energy and rate with the increase in hydraulic head (increase in flow) highlighting the presence of major events that accelerated towards the end of the experiment leading to the collapse of the sample.

[1]  Caroline Chaux,et al.  Sparse adaptive template matching and filtering for 2D seismic images with dual-tree wavelets and proximal methods , 2015, 2015 IEEE International Conference on Image Processing (ICIP).

[2]  Hans Sellmeijer,et al.  Fine-tuning of the backward erosion piping model through small-scale, medium-scale and IJkdijk experiments , 2011 .

[3]  Chi Fai Wan,et al.  Time for Development of Internal Erosion and Piping in Embankment Dams , 2003 .

[4]  Robert J. Skoumal,et al.  Optimizing multi-station earthquake template matching through re-examination of the Youngstown, Ohio, sequence , 2014 .

[5]  Michael A. Mooney,et al.  Monitoring the tidal response of a sea levee with ambient seismic noise , 2017 .

[6]  A. Bolève,et al.  Dyke leakage localization and hydraulic permeability estimation through self-potential and hydro-acoustic measurements: Self-potential ‘abacus’ diagram for hydraulic permeability estimation and uncertainty computation , 2012 .

[7]  Michael H. Ritzwoller,et al.  Source location of the 26 sec microseism from cross‐correlations of ambient seismic noise , 2006 .

[8]  Michael A. Mooney,et al.  Backward Erosion Monitored by Spatial–Temporal Pore Pressure Changes during Field Experiments , 2016 .

[9]  A. J. Brown,et al.  Defra research into Internal Erosion , 2008 .

[10]  Michael A. Mooney,et al.  Preliminary Implementation of Geophysical Techniques to Monitor Embankment Dam Filter Cracking at the Laboratory Scale , 2012 .

[11]  Hans Sellmeijer,et al.  Observations on the process of backward erosion piping in small-, medium- and full-scale experiments , 2011 .

[12]  En-Jui Lee,et al.  Rapid earthquake detection through GPU-Based template matching , 2017, Comput. Geosci..

[13]  Robin Fell,et al.  Internal erosion of dams and their foundations , 2007 .

[14]  Norman Alfred Fisher Smith,et al.  A history of dams , 1971 .

[15]  Clara E Yoon,et al.  Earthquake detection through computationally efficient similarity search , 2015, Science Advances.

[16]  Robert M. Koerner,et al.  ACOUSTIC EMISSION BEHAVIOR OF GRANULAR SOILS , 1976 .

[17]  John H. Schmertmann Discussion of “Time for Development of Internal Erosion and Piping in Embankment Dams” by Robin Fell, Chi Fai Wan, John Cyganiewicz, and Mark Foster , 2004 .

[18]  Zefeng Li,et al.  High-resolution seismic event detection using local similarity for Large-N arrays , 2018, Scientific Reports.