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.

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>

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 Geophysical Survey on Open Dumping Landfill for Monitoring Spread of Leachate: A Case Study in Pekanbaru, Riau, Indonesia

2020 ◽  
Vol 5 (2) ◽  
pp. 121-126
Author(s):  
Adi Suryadi ◽  
Frezy Ukhuah Islami ◽  
Husnul Kausarian ◽  
Dewandra Bagus Eka Putra
Keyword(s):  
Waste Disposal ◽  
Groundwater Resources ◽  
Preventive Action ◽  
Residential Areas ◽  
Resistivity Model ◽  
High Population Growth ◽  
Open Dumping ◽  
2D Resistivity

Pekanbaru is a city in Indonesia with high population growth. The increasing amount of the population has a parallel relationship with the increasing quantity of waste disposal. This study has been conducted on an open dumping landfill at Pekanbaru that surrounded by residential areas. Waste disposal produces leachate as a threat to surface water and groundwater resources. This study aims to investigate the contamination spread formed by leachate using the geophysical method. Direct Current Resistivity (DCR) has been used to produce 2 D Resistivity subsurface Models. Data acquisition has been done using multi-electrodes (32 electrodes) with spacing 2 m between electrodes. 2D Resistivity model produced, a contaminant from leachate represented by low resistivity value 26.1 - 870 Ωm. The deepest penetration of leachate that detected is around 3 m from the surface. It has been understood that leachate from the landfill of the study area is not contaminated groundwater yet. It confirmed by groundwater analysis at residential around the landfill area. By knowing the spreading of leachate, preventive action can be made to maintain the quality of groundwater resources.

scholarly journals The results of deep magnetotelluric sounding for studying the Nha Trang - Tanh Linh fault

2017 ◽  
Vol 17 (4B) ◽  
pp. 123-129
Author(s):  
Vo Thanh Son ◽  
Le Huy Minh ◽  
Nguyen Hong Phuong ◽  
Guy Marquis ◽  
Nguyen Ha Thanh ◽  
...  
Keyword(s):  
Lower Crust ◽  
Magnetotelluric Sounding ◽  
Two Dimensional ◽  
Upper Crust ◽  
Remarkable Change ◽  
Near Surface ◽  
Deep Fault ◽  
The Earth ◽  
Resistivity Model ◽  
2D Resistivity

The profile of deep magnetotelluric sounding (MT) from Duc Trong - Tuy Phong has been carried out in Lam Dong and Binh Thuan  provinces. The length of the Duc Trong - Tuy Phong profile is about 80 km with 15 stations and the distance between the stations measures about 5 km. Two-dimensional MT inversion was used to find a resistivity model that fits the data. The 2D resistivity model allows determining position and development formation of the Nha Trang - Tanh Linh  fault. This is the deep fault, which is showed by the boundaries of remarkable change of resistivity. In the near surface of the Earth (from ground to the depth of 6 km), the angle of inclination of this fault is about 60o; in the next part, the direction of the Nha Trang - Tanh Linh  faut is vertical. Geoelectrical section of the Nha Trang - Tanh Linh  profile shows that the resistivity of mid-crust is higher than that of lower-crust and of upper-crust.

NUMERICAL RESISTIVITY INTERPRETATION: GENERAL INHOMOGENEITY

Geophysics ◽  
1960 ◽  
Vol 25 (6) ◽  
pp. 1184-1194 ◽  
Author(s):  
K. Vozoff
Keyword(s):  
Linear Approximation ◽  
Arbitrary Function ◽  
Apparent Resistivity ◽  
Current Source ◽  
Resistivity Data ◽  
Resistivity Method ◽  
The Earth ◽  
Local Current ◽  
The Individual

A linear approximation is developed for the equation of conduction in a medium where resistivity is an arbitrary function of x, y, and z. This is applied by assuming the earth to be subdivided into small, homogeneous blocks of arbitrary resistivity. Under this approximation, the apparent resistivity is just the sum of the effects of the individual blocks. The equations are linear, and surface apparent resistivity data can be inverted to yield block resistivities. The quality of the approximation has been checked by comparison with model measurements in two situations: remote current source (telluric method), and local current source (resistivity method). It was found that the results are satisfactory provided that the proper type of expression is used for the effect of the resistivity contrast of each block.

scholarly journals Interpretation of 2D-Subsurface Resistivity Data in The Iron Ore Prospect Area of Eastern Binangun Coastal, Regency of Cilacap, Central Jawa

2018 ◽  
Vol 3 (4) ◽  
pp. 214
Author(s):  
Muhammad Sehah ◽  
Sukmaji Anom Raharjo ◽  
Fajar Destiani
Keyword(s):  
Iron Ore ◽  
Fine Sand ◽  
Distribution Patterns ◽  
Research Area ◽  
Magnetic Method ◽  
Clayey Sand ◽  
Resistivity Data ◽  
Resistivity Method ◽  
Interpretation Process ◽  
2D Resistivity

Interpretation of 2D-subsurface rock resistivity data has been carried out in the iron ore prospect area of Eastern Binangun Coastal in ​​Cilacap Regency, Central Java. The background of this research is the potential for abundant iron sand in this area that prospects to be exploited. The research was conducted using a magnetic method in 2017 to map the distribution patterns of the local magnetic anomalies that were interpreted to originate from the distribution of iron ore in the subsurface. In 2018, the research continued using the 2D-resistivity method to find out the lithology section in the subsurface of research area. 2D-resistivity data acquisition is carried out on four tracks consisting of Bng-01 to Bng-04. The resistivity data modeling have produced the true resistivity value for each track in the form of the subsurface resistvity section, which including the Bng-01 track is 2.27 – 44.1 Ωm; the Bng-02 track is 4.5 – 58.6 Ωm; the Bng-03 track is 6.37 – 63.4 Ωm; and the Bng-04 track of 4.98 – 83.3 Ωm. After interpretation process, some models of subsurface rocks lithology section is obtained under the four trajectories. The rocks resulted from interpretation process consists of sand which inserted with gravel (> 58.6 Ωm); sand containing iron ore grains (28.2 – 83.3 Ωm), clayey sand (11.1 – 32.9 Ωm), sandy clay (4.98 – 13.5 Ωm), and fine sand which intruded by saltwater (<6.49 Ωm). Sand containing iron ore grains is main part of the coastal aquifer so that exploitation of iron sand has the potential to reduce aquifer function in storing and flowing of groundwater and causing of abrasion in the Eastern Binangun Coastal area.

PERBANDINGAN METODE HOMOMORPHIC FILTERING DAN METODE CONTRAST STRECHING UNTUK PERBAIKAN KUALITAS CITRA UNDERWATER

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Adi Mora Lubis ◽  
Nelly Astuti Hasibuan ◽  
Imam Saputra
Keyword(s):  
Digital Image ◽  
Water Environment ◽  
Repair Process ◽  
Image Process ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Underwater Image ◽  
Homomorphic Filtering ◽  
Contrast Stretching

Digital imagery is a two-dimensional image process through a digital computer that is used to manipulate and modify images in various ways. Photos are examples of two-dimensional images that can be processed easily. Each photo in the form of a digital image can be processed through a specific software. In the water environment, the light factor greatly influences the results of the quality of the image obtained. With the deepening of underwater shooting, the results obtained will be the darker the quality of the underwater image. . uneven lighting and bluish tones. One of the factors that influence the recognition results in pattern recognition is the quality of the image that is inputted. The image acquired from the source does not always have good quality. The process of repairing digital images that experience interference in lighting. The lighting repair process uses homomorphic filtering and uses contrast striching and will compare the quality of both methods and test to prove the results of image quality between homomorphic filtering and contrast streching. Until later the results of both methods can be seen which is better. homomorphic filtering and contrast stretching can produce image improvements with pretty good performance.Keywords: Digital Image, Underwater Image, Homomorphic Filtering, Contrast Streching, Matlab R2010a

IMPLEMENTASI METODE RETINEX UNTUK MENINGKATKAN KUALITAS CITRA UNDERWATER

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Bainun Harahap
Keyword(s):  
Water Environment ◽  
Repair Process ◽  
Image Process ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Underwater Image ◽  
Object Search ◽  
Image Improvement ◽  
Underwater Object

Digital imagery is a two-dimensional image process through a digital computer that is used to manipulate and modify images in various ways. Photos are examples of two-dimensional images that can be processed easily. Each photo in the form of a digital image can be processed through certain software devices. In the water environment, light factors greatly influence the results of image quality obtained. With the deepening of underwater shooting, the results obtained will be the darker the quality of the underwater image. Underwater imagery is widely used as an object in various activities such as underwater habitat mapping, underwater environment monitoring, underwater object search. Uneven lighting and colors that tend to be bluish and runny. One of the factors that influence the recognition results in pattern recognition is the quality of the image that is inputted. The image acquired from the source does not always have good quality. The process of improvement in digital images that experience interference in lighting and exposure to sunlight. The lighting repair process uses the retinex method and will compare the quality of the two methods later. Until later the results of both methods can be seen which is better. Retinex method can produce image improvement with high performance.Keywords: Digital Cintra, Underwater, Matlab Retinex Method

ASSECSSING MOCA TEST IN SUBACUTE STROKE PATIENTS AND COMPARE MOCA VERSUS MMSE

2016 ◽  
pp. 120-127
Author(s):  
Dinh Toan Nguyen
Keyword(s):  
Human Life ◽  
Statistical Significance ◽  
High Sensitivity ◽  
Stroke Patients ◽  
Cross Sectional ◽  
Female Age ◽  
Subacute Stroke ◽  
Duration Of Illness ◽  
Dsm Iv

Background: Dementia after stroke, particularly subacute period is often overlooked. Today the quality of human life is increasingly high, finding scales that have high value for detection of dementia in patients with stroke is increasingly interested. MoCA test is high sensitivity with mild dementia and identify more abnormalities of awareness caused by vascular, but MoCA have not been studied much in Vietnam. Objective: Assessing MoCA test in subacute stroke patients and compare MoCA versus MMSE in these patients. Subjects: 90 patients with subacute stroke period, these people are being treated at Department of cardiovascular internal medicine at Hue Central Hospital, from 7/2014 - 7/2015. Methods: cross-sectional description and analysis. Results: The mean age is 65.57 ± 13.38, accounting for 54.4% male and 45.6% female. Age, duration of illness has weak correlation with MoCA. The risk factors: hypertension, stroke ischemic transient, alcoholism, smoking, heart disease, diabetes, dyslipidemia related no statistical significance with MoCA. The proportion of dementia in subacute stroke according MoCA is 82.2%. The concordance between MoCA and MMSE was good (kappa = 0.684). Using DSM-IV criteria as the gold standard we found MoCA more valuable in the dementia diagnosis than MMSE (AUC 0.864 versus 0.774, p <0.05). Conclusion: The rate of dementia in stroke subacute period according MoCA is quite high. MoCA is valuable than MMSE in detecting dementia in patients with stroke subacute period, this scale is short, easy to implement so should put into using widely in clinical practice. Key words: MoCA test, subacute stroke, dementia

scholarly journals Two-Dimensional Sampling-Recovery Algorithm of a Realization of Gaussian Processes on the Input and Output of Linear Systems

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1079
Author(s):  
Vladimir Kazakov ◽  
Mauro A. Enciso ◽  
Francisco Mendoza
Keyword(s):  
Gaussian Processes ◽  
Research Method ◽  
General Algorithm ◽  
Two Dimensional ◽  
Recovery Algorithm ◽  
Conditional Mean ◽  
Quality Of Recovery ◽  
Input And Output ◽  
Statistical Relationships

Based on the application of the conditional mean rule, a sampling-recovery algorithm is studied for a Gaussian two-dimensional process. The components of such a process are the input and output processes of an arbitrary linear system, which are characterized by their statistical relationships. Realizations are sampled in both processes, and the number and location of samples in the general case are arbitrary for each component. As a result, general expressions are found that determine the optimal structure of the recovery devices, as well as evaluate the quality of recovery of each component of the two-dimensional process. The main feature of the obtained algorithm is that the realizations of both components or one of them is recovered based on two sets of samples related to the input and output processes. This means that the recovery involves not only its own samples of the restored realization, but also the samples of the realization of another component, statistically related to the first one. This type of general algorithm is characterized by a significantly improved recovery quality, as evidenced by the results of six non-trivial examples with different versions of the algorithms. The research method used and the proposed general algorithm for the reconstruction of multidimensional Gaussian processes have not been discussed in the literature.

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