A clustering approach applied to time-lapse ERT interpretation — Case study of Lascaux cave

Xu, Shan; Sirieix, Colette; Riss, Joëlle; Malaurent, Philippe

doi:10.1016/j.jappgeo.2017.07.006

Cited by 22 publications

(8 citation statements)

References 30 publications

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“…In such case, a real effort should be made for optimising more complex measuring protocols with regard to highly resistive karst environments. Clustering tools could also improve the detection of structures in the ERT images, as proposed by Xu et al (2017). In such cases, fully taking advantage of the time-lapse information, i.e.…”

Section: Discussionmentioning

confidence: 99%

“…A few studies have already used repeated ERT surveys to track hydrological changes in karst areas. Recently, Xu et al (2017) investigated time-lapse ERT data to define subsurface characteristics near the Lascaux cave (France). Carrière et al (2016) successfully used time-lapse ERT and magnetic resonance sounding (MRS) to identify the role of the porous matrix in regulating water infiltration from epikarst structures, previously identified by groundpenetrating radar (GPR) and ERT surveys in southern France (Carrière et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring

Watlet

Kaufmann

Triantafyllou

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Water infiltration and recharge processes in karst systems are complex and difficult to measure with conventional hydrological methods. In particular, temporarily saturated groundwater reservoirs hosted in the vadose zone can play a buffering role in water infiltration. This results from the pronounced porosity and permeability contrasts created by local karstification processes of carbonate rocks. Analyses of time-lapse 2-D geoelectrical imaging over a period of 3 years at the Rochefort Cave Laboratory (RCL) site in south Belgium highlight variable hydrodynamics in a karst vadose zone. This represents the first long-term and permanently installed electrical resistivity tomography (ERT) monitoring in a karst landscape. The collected data were compared to conventional hydrological measurements (drip discharge monitoring, soil moisture and water conductivity data sets) and a detailed structural analysis of the local geological structures providing a thorough understanding of the groundwater infiltration. Seasonal changes affect all the imaged areas leading to increases in resistivity in spring and summer attributed to enhanced evapotranspiration, whereas winter is characterised by a general decrease in resistivity associated with a groundwater recharge of the vadose zone. Three types of hydrological dynamics, corresponding to areas with distinct lithological and structural features, could be identified via changes in resistivity: (D1) upper conductive layers, associated with clay-rich soil and epikarst, showing the highest variability related to weather conditions; (D2) deeper and more resistive limestone areas, characterised by variable degrees of porosity and clay contents, hence showing more diffuse seasonal variations; and (D3) a conductive fractured zone associated with damped seasonal dynamics, while showing a great variability similar to that of the upper layers in response to rainfall events. This study provides detailed images of the sources of drip discharge spots traditionally monitored in caves and aims to support modelling approaches of karst hydrological processes.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring

Watlet

Kaufmann

Triantafyllou

et al. 2018

Hydrol. Earth Syst. Sci.

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“…Nonetheless, ERT results interpretation can be used as a posterior validation tool for conduit geometries and more broadly the groundwater flow path. This point may constitute an open question for further investigations about hydrogeophysics since recent studies highlighted successfully applied geophysics applications for karst features detection [71][72][73].…”

Section: Discussionmentioning

confidence: 99%

Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers

Sivelle

Renard

Labat

2020

Water

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Artificial tracer tests constitute one of the most powerful tools to investigate solute transport in conduit-dominated karstic aquifers. One can retrieve information about the internal structure of the aquifer directly by a careful analysis of the residence time distribution (RTD). Moreover, recent studies have shown the strong dependence of solute transport in karstic aquifers on boundary conditions. Information from artificial tracer tests leads us to propose a hypothesis about the internal structure of the aquifers and the effect of the boundary conditions (mainly high or low water level). So, a multi-tracer test calibration of a model appeared to be more consistent in identifying the effects of changes to the boundary conditions and to take into consideration their effects on solute transport. In this study, we proposed to run the inverse problem based on artificial tracer tests with a numerical procedure composed of the following three main steps: (1) conduit network geometries were simulated using a pseudo-genetic algorithm; (2) the hypothesis about boundary conditions was imposed in the simulated conduit networks; and (3) flow and solute transport were simulated. Then, using a trial-and-error procedure, the simulated RTDs were compared to the observed RTD on a large range of simulations, allowing identification of the conduit geometries and boundary conditions that better honor the field data. This constitutes a new approach to better constrain inverse problems using a multi-tracer test calibration including transient flow.

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“…Chen, 2017), to interpret ERT timelapse measurements (e.g. Xu et al, 2017), and for parameter estimation (e.g. Calderon-Macias et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

A data mining approach for improved interpretation of ERT inverted sections using the DBSCAN clustering algorithm

Sabor

Jougnot

Guérin

et al. 2021

Geophysical Journal International

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Summary Geophysical imaging using the inversion procedure is a powerful tool for the exploration of the Earth's subsurface. However, the interpretation of inverted images can sometimes be difficult, due to the inherent limitations of existing inversion algorithms, which produce smoothed sections. In order to improve and automate the processing and interpretation of inverted geophysical models, we propose an approach inspired from data mining. We selected an algorithm known as DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to perform clustering of inverted geophysical sections. The methodology relies on the automatic sorting and clustering of data. DBSCAN detects clusters in the inverted electrical resistivity values, with no prior knowledge of the number of clusters. This algorithm has the advantage of being defined by only two parameters: the neighbourhood of a point in the data space, and the minimum number of data points in this neighbourhood. We propose an objective procedure for the determination of these two parameters. The proof of concept described here is applied to simulated ERT (Electrical Resistivity Tomography) sections, for the following three cases: two layers with a step, two layers with a rebound, and two layers with an anomaly embedded in the upper layer. To validate this approach, sensitivity studies were carried out on both of the above parameters, as well as to assess the influence of noise on the algorithm's performance. Finally, this methodology was tested on real field data. DBSCAN detects clusters in the inverted electrical resistivity models, and the former are then associated with various types of earth materials, thus allowing the structure of the prospected area to be determined. The proposed data-mining algorithm is shown to be effective, and to improve the interpretation of the inverted ERT sections. This new approach has considerable potential, as it can be applied to any geophysical data represented in the form of sections or maps.

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A clustering approach applied to time-lapse ERT interpretation — Case study of Lascaux cave

Cited by 22 publications

References 30 publications

Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring

Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring

Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers

A data mining approach for improved interpretation of ERT inverted sections using the DBSCAN clustering algorithm

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