3D modeling and inversion of the electrical resistivity tomography using steel cased boreholes as long electrodes

2014 ◽  
Vol 109 ◽  
pp. 292-300 ◽  
Author(s):  
Ying-Ying Zhang ◽  
De-Jun Liu ◽  
Qing-Hui Ai ◽  
Min-Jun Qin
2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Yonatan Garkebo Doyoro ◽  
Ping-Yu Chang ◽  
Jordi Mahardika Puntu ◽  
Ding-Jiun Lin ◽  
Tran Van Huu ◽  
...  

AbstractGeophysical modelling performs to obtain subsurface structures in agreement with measured data. Freeware algorithms for geoelectrical data inversion have not been widely used in geophysical communities; however, different open-source modelling/inversion algorithms were developed in recent years. In this study, we review the structures and applications of openly Python-based inversion packages, such as pyGIMLi (Python Library for Inversion and Modelling in Geophysics), BERT (Boundless Electrical Resistivity Tomography), ResIPy (Resistivity and Induced Polarization with Python), pyres (Python wrapper for electrical resistivity modelling), and SimPEG (Simulation and Parameter Estimation in Geophysics). In addition, we examine the recovering ability of pyGIMLi, BERT, ResIPy, and SimPEG freeware through inversion of the same synthetic model forward responses. A versatile pyGIMLi freeware is highly suitable for various geophysical data inversion. The SimPEG framework is developed to allow the user to explore, experiment with, and iterate over multiple approaches to the inverse problem. In contrast, BERT, pyres, and ResIPy are exclusively designed for geoelectric data inversion. BERT and pyGIMLi codes can be easily modified for the intended applications. Both pyres and ResIPy use the same mesh designs and inversion algorithms, but pyres uses scripting language, while ResIPy uses a graphical user interface (GUI) that removes the need for text inputs. Our numerical modelling shows that all the tested inversion freeware could be effective for relatively larger targets. pyGIMLi and BERT could also obtain reasonable model resolutions and anomaly accuracies for small-sized subsurface structures. Based on the heterogeneous layered model and experimental target scenario results, the geoelectrical data inversion could be more effective in pyGIMLi, BERT, and SimPEG freeware packages. Moreover, this study can provide insight into implementing suitable inversion freeware for reproducible geophysical research, mainly for geoelectrical modelling.


2011 ◽  
Vol 8 (4) ◽  
pp. 487-497 ◽  
Author(s):  
Panagiotis Tsourlos ◽  
Richard Ogilvy ◽  
Constantinos Papazachos ◽  
Philip Meldrum

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. A25-A28 ◽  
Author(s):  
Kamini Singha ◽  
Stephen Moysey

A number of issues impact electrical resistivity tomography (ERT) inversions: how ERT measurements sample the subsurface, the nature of subsurface heterogeneity, the geometry selected for data collection, the choice of data-misfit criteria, and regularization of the inverse problem. Lab-scale rock-physics models, typically used to estimate solute concentration from ERT, do not accommodate or account for these issues and therefore produce inaccurate geophysical estimates of solute concentrations. In contrast, the influence of measurement sensitivity and inversion artifacts can be captured by pixel-based rock-physics relationships, determined using numerical analogs that recreate the field-scale ERT experiment based on flow and transport modeling and a priori data. In the 2D synthetic example presented here, where ERT is used to monitor the transport of a saline tracer through the subsurface, improved estimates of concentration are obtained when field-scale rock-physics relationships based on numerical analogs are used.


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