scholarly journals Hydrogeological and geophysical study for deeper groundwater resource in quartzitic hard rock ridge region from 2D resistivity data

2014 ◽  
Vol 123 (3) ◽  
pp. 531-543 ◽  
Author(s):  
DEWASHISH KUMAR ◽  
V ANANDA RAO ◽  
V S SARMA
Keyword(s):  
Hard Rock ◽  
Groundwater Resource ◽  
Resistivity Data ◽  
Geophysical Study ◽  
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 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

scholarly journals Use of resistivity measurements to detect urban caves in Mexico City and to assess the related hazard

2004 ◽  
Vol 4 (4) ◽  
pp. 541-547 ◽  
Author(s):  
R. G. Antonio-Carpio ◽  
M. A. Pérez-Flores ◽  
D. Camargo-Guzmán ◽  
A. Alanís-Alcantar
Keyword(s):  
Mexico City ◽  
Building Materials ◽  
Horizontal Distribution ◽  
Private Company ◽  
Resistivity Measurements ◽  
Resistivity Data ◽  
Geophysical Study ◽  
Xix Century ◽  
Resistivity Image ◽  
The City

Abstract. In the XIX century when Mexico City was much smaller than at present, there was non-regulated mining of building materials in a region of tuffs northwest of the city in an inhabited countryside. With the growth of the city during the XX century, this region was increasingly populated and in the 1970's many two-level bricks houses were built, without regard for underground caves created by the earlier extractions. Some ground sinkings in adjacent areas alarmed the residents who now are worried about this permanent hazard. An association of residents contracted a private company for a geophysical study in order to know the distribution of the caves. Resistivity measurements were taken in the area to detect the caves in order to alert city authorities. Resistivity data along most of the streets were collected with the array pole-dipole that consisted of three grounded electrodes. We performed 2-D dimensional inversions to the data in order to get a 2-D resistivity image of every street. This is similar to a resistivity cross-section of the ground but obtained from the inversion of pole-dipole and Schlumberger resistivity data simultaneously. Using the information of previous drills we modified our programming code in order to perform constrained inversion and to get more accurate resistivity models in agreement with the drills. From the resistivity models obtained for every street it was possible to produce a map which shows the horizontal distribution of the resistive bodies at a depth of 12m. These resistive bodies show coherent alignments that seem to correspond with a distributions of interconnected caves or tunnels used for extracting the sandy-tuffs. From these kind of interpretation method it was intended to get a more accurate horizontal distribution of the excavated areas in order to better know the urbanized area affected and lead the authorities to remedy the area with refill material.

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