scholarly journals Image processing of 2D resistivity data for imaging faults

2005 ◽  
Vol 57 (4) ◽  
pp. 260-277 ◽  
Author(s):  
F. Nguyen ◽  
S. Garambois ◽  
D. Jongmans ◽  
E. Pirard ◽  
M.H. Loke
Keyword(s):  
Image Processing ◽  
Resistivity Data ◽  
2D Resistivity

Fuzzy constrained Lp-norm inversion of direct current resistivity data

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. E11-E24 ◽  
Author(s):  
Anand Singh ◽  
Shashi Prakash Sharma ◽  
İrfan Akca ◽  
Vikas Chand Baranwal
Keyword(s):  
Direct Current ◽  
Cluster Center ◽  
Resistivity Data ◽  
Data Inversion ◽  
Lp Norm ◽  
L2 Norm ◽  
Resistivity Model ◽  
Minimization Procedure ◽  
Fuzzy C Means Clustering ◽  
2D Resistivity

We evaluate the use of a fuzzy c-means clustering procedure to improve an inverted 2D resistivity model within the iterative error minimization procedure. The algorithm is coded in MATLAB language for the Lp-norm inversion of 2D direct current resistivity data and is referred to as fuzzy constrained inversion (FCI). Two additional input parameters are required to be provided by the interpreter: (1) the number of geologic units in the model (i.e., the number of clusters) and (2) the mean resistivity values of each geologic unit (i.e., cluster center values of the geologic units). The efficacy of our approach is evaluated by tests carried on the synthetic and field electrical resistivity tomography (ERT) data. Inversion results from the FCI algorithm are presented for conventional L1- and L2-norm minimization techniques. FCI indicates improvement over conventional inversion approaches in differentiating the geologic units if a proper number of the geologic units is provided to the algorithm. Inappropriate clustering information will affect the resulting resistivity models, particularly conductive geologic units existing in the model. We also determine that FCI is only effective when the observed ERT data can recognize the particular geologic units.

scholarly journals Coastal Hydrogeological Model in the Iron Ore Prospect Area of Widarapayung Coastal, Cilacap Regency Based on 2D-Resistivity Data

2018 ◽  
Vol 8 (2) ◽  
pp. 71
Author(s):  
Sehah Sehah ◽  
Sukmaji Anom Raharjo ◽  
Abdullah Nur Aziz
Keyword(s):  
Large Scale ◽  
Iron Ore ◽  
Salt Water ◽  
Shallow Aquifer ◽  
Mining Activities ◽  
Hydrogeological Model ◽  
Clayey Sand ◽  
Deep Aquifer ◽  
Resistivity Data ◽  
2D Resistivity

The coastal hydrogeological model of iron ore prospect area in Widarapayung coastal, Cilacap Regency, has been designed and performed based on the 2D-resistivity data. The background of this research is potentiality of iron sand in this area and its prospect to be mined. Mining activities in large-scale may lead into surface decreasing, triggering damage to the aquifer, abrasion, and saltwater intrusion in the coastal area. The acquisition of 2D-resistivity data has been performed on five trajectories including of WP-01 up to WP-05. Based on the modeling results, it can be concluded that the sub-surface rocks resistivity profile consists of WP-01 with the values of 1.93-114.00 Ωm; WP-02 with the values of 3.67-121.00 Ωm; WP-03 with the values of 3.86-78.40 Ωm; WP-04 with the values of 1.79-100.00 Ωm; and WP-05 with the values of 2.61-86.20 Ωm. After interpretation, it is found that the hydrogeological profile of sub-surface rocks consists of sand inserted with gravels (topsoil); sand containing iron ore granules inserted with silt (topsoil and shallow aquifer); clayey sand (semi-aquifer layer); sandy clay (semi-impermeable layer); and sand (deep aquifer which is intruded by salt water). Based on the analysis, the sand containing iron ore is part of the shallow aquifer, so the mining activities of iron sand is potential to damage and reduce aquifer function in storing and flowing the groundwater in the research area.

Uncertainties Analysis of Electrical Resistivity Tomography

2021 ◽  
Author(s):  
Yonatan Garkebo Doyoro ◽  
Chang Ping-Yu ◽  
Jordi Mahardika Puntu
Keyword(s):  
Model Resolution ◽  
Resistivity Data ◽  
Resistivity Method ◽  
Resistivity Model ◽  
2D Resistivity Imaging ◽  
Model Set ◽  
Different Depths ◽  
Measured Resistivity ◽  
2D Resistivity ◽  
Subsurface Cavities

<p>We examined the uncertainty of the resistivity method in cavity studies using a synthetic cavity model set at six-different depths. Conceptual models were simulated to generate synthetic resistivity data for dipole-dipole, pole-dipole, Wenner-Schlumberger, and pole-pole arrays. The 2D geoelectric models were recovered from the inversion of the synthetically measured resistivity data. The highest anomaly effect (1.46) and variance (24400) in resistivity data were recovered by dipole-dipole array, while the pole-pole array obtained the lowest anomaly effect (0.60) and variance (2401) for the target cavity T<sub>1</sub>. The anomaly effect and variance were linearly associated with the quality of the inverted models. The steeper anomaly gradient of resistivity indicated more distinct cavity boundaries, while the gentler gradient prevents the inference of the cavity boundaries. The recovered model zone above the depth of investigation index of 0.1 has shown relatively higher sensitivity. Modeling for dipole-dipole array provided the highest model resolution and anomaly gradient that shows a relatively distinct geometry of the cavity anomalies. On the contrary, the pole-dipole and Wenner-Schlumberger arrays recovered good model resolutions and moderate anomaly gradient but determining the anomaly geometries is relatively challenging. Whereas, the pole-pole array depicted the lowest model resolution and anomaly gradient with less clear geometry of the cavity anomalies. At deeper depths, the inverted models showed a reduction in model resolutions, overestimation in anomaly sizes, and deviation in anomaly positions, which can create ambiguity in resistivity model interpretations. Despite these uncertainties, our modeling specified that the 2D resistivity imaging is a potential technique to study subsurface cavities.</p>

scholarly journals Uncertainty of the 2D Resistivity Survey on the Subsurface Cavities

2021 ◽  
Vol 11 (7) ◽  
pp. 3143
Author(s):  
Yonatan Garkebo Doyoro ◽  
Ping-Yu Chang ◽  
Jordi Mahardika Puntu
Keyword(s):  
High Sensitivity ◽  
Two Dimensional ◽  
Model Resolution ◽  
Resistivity Data ◽  
Resistivity Method ◽  
Resistivity Model ◽  
Measured Resistivity ◽  
2D Resistivity ◽  
Subsurface Cavities

We examined the uncertainty of the two-dimensional (2D) resistivity method using conceptual cavity models. The experimental cavity study was conducted to validate numerical model results. Spatial resolution and sensitivity to resistivity perturbations were also assessed using checkerboard tests. Conceptual models were simulated to generate synthetic resistivity data for dipole-dipole (DD), pole-dipole (PD), Wenner–Schlumberger (WS), and pole-pole (PP) arrays. The synthetically measured resistivity data were inverted to obtain the geoelectric models. The highest anomaly effect (1.46) and variance (24,400 Ω·m) in resistivity data were recovered by the DD array, whereas the PP array obtained the lowest anomaly effect (0.60) and variance (2401 Ω·m) for the shallowest target cavity set at 2.2 m depth. The anomaly effect and variance showed direct dependency on the quality of the inverted models. The DD array provided the highest model resolution that shows relatively distinct anomaly geometries. In contrast, the PD and WS arrays recovered good resolutions, but it is challenging to determine the correct anomaly geometries with them. The PP array reproduced the lowest resolution with less precise anomaly geometries. Moreover, all the tested arrays showed high sensitivity to the resistivity contrasts at shallow depth. The DD and WS arrays displayed the higher sensitivity to the resistivity perturbations compared to the PD and PP arrays. The inverted models showed a reduction in sensitivity, model resolution, and accuracy at deeper depths, creating ambiguity in resistivity model interpretations. Despite these uncertainties, our modeling specified that two-dimensional resistivity imaging is a potential technique to study subsurface cavities. We inferred that the DD array is the most appropriate for cavity surveys. The PD and WS arrays are adequate, while the PP array is the least suitable for cavity studies.

scholarly journals Geo-Electrical Method of Assessment of Coefficient of Permeability and Porosity of Soil of a Poultry Farmland

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Fakunle M. Alani ◽  
Abidoye L. Kolawole ◽  
Alabi O. Olalekan ◽  
Olatona G. Ismail
Keyword(s):  
Soil Analysis ◽  
Resistivity Measurement ◽  
Soil Samples ◽  
Disposal Site ◽  
Depth Range ◽  
Electrical Method ◽  
Resistivity Data ◽  
Coefficient Of Permeability ◽  
2D Resistivity ◽  
Density Methods

Abstract Leachate collected at the bottom of dead bird’s disposal pits may leak and migrate to pollute groundwater when soils and rocks present are porous. This study assessed the coefficient of permeability (K) and porosity (Ф) of soils and rocks in poultry farmland using 2 Dimensional (2D) electrical resistivity method and soil analysis. Geo-electrical data collection was achieved by using the dipole-dipole array. The field resistivity measurement was carried out along three traverse lines (three Profiles) of 100 m long which were oriented along with East-West directions. These measurements were taken in the order of increasing in offset distance interval of 5 m. The acquired apparent resistivity data were inverted using DIPPROWIN modeling software to perform 2D data inversion. Five soil samples from different locations at depths of 0 – 15 cm and 15 – 30 cm, on the poultry farmland, were collected, transported, and tested in the laboratory. K and Ф were determined using falling head and density methods respectively. The results obtained from the processed field resistivity data from the three profiles were presented as field data pseudo-sections, theoretical pseudo-section, and 2D resistivity structures. The 2D resistivity structure revealed three structures viz; highly conductive, slightly conductive, and resistive. The resistivity values of these structures ranged from 14.1-99.0 Ω m, 100-848 Ω m, and 1350-90330 Ω m respectively. The highly conductive structures were found in profiles 1 and 3 due to the downward migration of the contaminants from the dead bird disposal pit 1 and the feces disposal site through clayey sand soil. This occurs at the depth range of few meters from the surface to greater than 20 m. The presence of the slightly conductive structure is a result of filtration of the contaminants by the soil materials which increased the resistivity of the soil. The movement of the contaminant through the soil is an indication of the porous and permeable nature of the farmland. The resistive structure is only noticeable in profiles 1 and 2 but very prominent at the depth range of 5 m to more than 20 m and 5 m to 35 m along the profile length. The results of the analysis of the five soil samples from the poultry farmland showed a high value of 0.552 and 3.554 x 10−2cm/s of porosity (Ф) and coefficient of permeability (K) respectively. A strong correlation of R 2 = 0.9878 existed between Ф and K. With these results geo-electrical method had successfully assessed Ф and K of the soil of the poultry farmland.

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