Electrical resistivity tomography

Summary

Electrical resistivity tomography (ERT) or electrical resistivity imaging (ERI) is a geophysical technique for imaging sub-surface structures from electrical resistivity measurements made at the surface, or by electrodes in one or more boreholes. If the electrodes are suspended in the boreholes, deeper sections can be investigated. It is closely related to the medical imaging technique electrical impedance tomography (EIT), and mathematically is the same inverse problem. In contrast to medical EIT, however, ERT is essentially a direct current method. A related geophysical method, induced polarization (or spectral induced polarization), measures the transient response and aims to determine the subsurface chargeability properties. Electrical resistivity measurements can be used for identification and quantification of depth of groundwater, detection of clays, and measurement of groundwater conductivity. History The technique evolved from techniques of electrical prospectin

Official source

https://en.wikipedia.org/wiki/Electrical_resistivity_tomography

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An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment

Damiano Pasetto, Matteo Rossi

The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.

2015

Noninvasive measurement of stroke volume changes in critically ill patients by means of electrical impedance tomography

Fabian Braun, Mathieu Lemay, Martin Proença, Jean-Philippe Thiran

Previous animal experiments have suggested that electrical impedance tomography (EIT) has the ability to noninvasively track changes in cardiac stroke volume (SV). The present study intended to reproduce these findings in patients during a fluid challenge. In a prospective observational study including critically ill patients on mechanical ventilation, SV was estimated via ECG-gated EIT before and after a fluid challenge and compared to transpulmonary thermodilution reference measurements. Relative changes in EIT-derived cardiosynchronous impedance changes in the heart (Delta Z(H)) and lung region (Delta Z(L)) were compared to changes in reference SV by assessing the concordance rate (CR) and Pearson's correlation coefficient (R). We compared 39 measurements of 20 patients. Delta Z(H) did not show to be a reliable estimate for tracking changes of SV (CR = 52.6% and R = 0.13 with P = 0.44). In contrast, Delta Z(L) showed an acceptable trending performance (CR = 94.4% and R = 0.72 with P < 0.0001). Our results indicate that ECG-gated EIT measurements of Delta Z(L) are able to noninvasively monitor changes in SV during a fluid challenge in critically ill patients. However, this was not possible using Delta Z(H). The present approach is limited by the influences induced by ventilation, posture or changes in electrode-skin contact and requires further validation.

SPRINGER HEIDELBERG2019

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Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to their ill-posedness, image reconstruction typically uses regularization, which implies a hyperparameter controlling the tradeoff between noise rejection and resolution or other accuracies. In order to compare reconstruction algorithms, it is common to choose hyperparameter values such that the reconstructed images have equal noise performance (NP), i.e., the amount of measurement noise reflected in the images. For EIT many methods have been suggested, but none work well when the data originate from different measurement setups, such as for different electrode positions or measurement patterns. To address this issue, we propose a new NP metric based on the average signal-to-noise ratio in the image domain. The approach is validated for EIT using simulation experiments on a human thorax model and measurements on a resistor phantom. Results show that the approach is robust to the measurement configuration (i.e., number and position of electrodes, skip pattern) and the reconstruction algorithm used. We propose this novel approach as a way to select optimized measurement configurations and algorithms.

Ieee-Inst Electrical Electronics Engineers Inc2017