Clayey Sand Soil's Behaviour Analysis and Imaging Subsurface Structure via Engineering Characterizations and Integrated Geophysicals Tomography Modeling Methods

Bery, Andy Anderson; Saad, Rosli

doi:10.4236/ijg.2012.31011

Cited by 16 publications

(14 citation statements)

References 14 publications

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“…Resistivity survey plays significant role in many large-scale sites characterization (Dahlin et al 2007;Bery and Saad 2012), groundwater exploration (Saad et al 2012a) and mineral prospecting (Saad et al 2012b;Song et al 2017). Unfortunately, the measured apparent resistivity data from such surveys cannot be used directly to describe the subsurface (De Donno and Cardarelli 2017).…”

Section: Introductionmentioning

confidence: 99%

Linear regression models for estimating true subsurface resistivity from apparent resistivity data

Muhammad

Saad

2018

J Earth Syst Sci

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Simple linear regression (SLR) models for rapid estimation of true subsurface resistivity from apparent resistivity measurements are developed and assessed in this study. The objective is to minimize the processing time and computer memory required to carry out inversion with conventional algorithms. The arrays considered are Wenner, Wenner-Schlumberger and dipole-dipole. The parameters investigated are apparent resistivity (ρ a) and true resistivity (ρ t) as independent and dependent variables, respectively. For the fact that subsurface resistivity is nonlinear, the datasets were first transformed into logarithmic scale to satisfy the basic regression assumptions. Three models, one each for the three array types, are thus developed based on simple linear relationships between the dependent and independent variables. The generated SLR coefficients were used to estimate ρ t for different ρ a datasets for validation. Accuracy of the models was assessed using coefficient of determination (R 2), F-test, standard error (SE) and weighted mean absolute percentage error (wMAPE). The model calibration R 2 and F-value are obtained as 0.75 and 2286, 0.63 and 1097, and 0.47 and 446 for the Wenner, Wenner-Schlumberger and dipoledipole array models, respectively. The SE for calibration and validation are obtained as 0.12 and 0.13, 0.16 and 0.25, and 0.21 and 0.24 for the Wenner, Wenner-Schlumberger and dipole-dipole array models, respectively. Similarly, the wMAPE for calibration and validation are estimated as 3.27 and 3.49%, 3.88 and 5.72%, and 5.35 and 6.07% for the three array models, respectively. When compared with standard constraint least-squares (SCLS) inversion and Incomplete Gauss-Newton (IGN) algorithms, the SLR models were found to reduce about 80-96.5% of the processing time and memory space required to carry out the inversion with the SCLS algorithm. It is concluded that the SLR models can rapidly estimate ρ t for the various arrays accurately.

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Section: Introductionmentioning

confidence: 99%

Linear regression models for estimating true subsurface resistivity from apparent resistivity data

Muhammad

Saad

2018

J Earth Syst Sci

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“…There are three categories of common techniques to determine these engineering properties, such as insitu test, geophysical methods, and laboratory. Geophysical methods were developed because of their accuracy to specify soil properties based on quantification [2].…”

Section: Introductionmentioning

confidence: 99%

Measurement of Peat Soil Shear Strength Using Wenner Four-Point Probes and Vane Shear Strength Methods

Afip

Taib

Jusoff

et al. 2019

International Journal of Geophysics

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The general objective of this research was to measure the peat soil shear strength using Wenner four-point probes and vane shear strength methods. Specifically, the objective of this study was two-fold, namely, (a) investigating the relationship between laboratory soil resistivity and undrained shear strength and (b) determineing the relationship between in-situ soil resistivity and undrained shear strength. Data were randomly collected over six locations in Meranek, Sarawak, for in-situ test and three repetitions for each data were set based on three parameters. The selected parameters were soil density, moisture content, and salinity for both laboratory and in-situ test using Wenner four-point probes and vane shear method. The soil resistivity and vane shear strength readings for laboratory test were correlated with soil salinity, moisture content, and density. The R2 values showed a good correlation for soil salinity (R2 =0.8468) and density (R2 =0.9475), respectively. However, a weak correlation of R2 =0.1205 was observed for soil moisture. The R2 value for in-situ correlation between soil resistivity and three parameters (soil salinity, moisture content, and density) was R2 =0.8916. It can be concluded that the peat soil shear strengths of the study area using Wenner four-point probes from in-situ were (4.38 ohm.m) and laboratory was (2.47 ohm.m) and when using the vane shear strength method, in-situ was (23 kPA) and laboratory was (5 kPA). This study implies that the peat soil of the study area can be categorized as texture (soft loamy soil) and it is suitable for agriculture instead of construction. The relationship established between Wenner four-point probes and vane shear method can be beneficial for ground engineering design to enhance investigation on site suitability. Future work on DUALEM-421 technique should be emphasised for better subsurface exploration accuracy and resolve peat depth for an in-situ test.

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“…In this paper, we used data collected during recent electrical tomography and seismic refraction surveys [5]. The same data sets were used for simultaneous subsurface imaging using algorithm for improved near-surface characterization.…”

Section: Seismic and Resistivity Characterization By Merge-optimizatimentioning

confidence: 99%

“…It is possible that Figures 5 and 6 have physical implications from the external factors. Thus, before this merge-optimization method was applied, we have did a study on the physical characterizations of the soils (moisture content W, cohesion C , friction angle Ø , porosity n, void ratio e, and saturation degree S) at various locations along the survey lines at different periods [5,6].…”

Section: Seismic and Resistivity Characterization By Merge-optimizatimentioning

confidence: 99%

Merge-Optimization Method of Combined Tomography of Seismic Refraction and Resistivity Data

Bery

2012

ISRN Geophysics

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This paper discussed a novel application called merge-optimization method that combines resistivity and seismic refraction data to provide a detailed knowledge of the studied site. This method is interesting because it is able to show strong accuracy of two geophysical imaging methods based on many of data points collected from the conducted geophysical surveys of disparate data sets based strictly on geophysical models as an aid for model integration for two-dimensional environments. The geophysical methods used are high resolution methods. The resistivity imaging used in this survey is able to resolve the subsurface condition of the studied site with low RMS error (less than 2.0%) and 0.5 metre electrodes interval. For seismic refraction method, high resolution of seismic is used for correlation with resistivity results. Geophones spacing is 1.0 metre and the total number of shot-points is 15, which provides very dense data point. The algorithms of merge-optimization have been applied to two data sets collected at the studied site. The resulting images have been proven to be successful because they satisfy the data and are geometrically similar. The regression coefficient found for conductivity-resistivity correlation is 95.2%.

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Clayey Sand Soil's Behaviour Analysis and Imaging Subsurface Structure via Engineering Characterizations and Integrated Geophysicals Tomography Modeling Methods

Cited by 16 publications

References 14 publications

Linear regression models for estimating true subsurface resistivity from apparent resistivity data

Linear regression models for estimating true subsurface resistivity from apparent resistivity data

Measurement of Peat Soil Shear Strength Using Wenner Four-Point Probes and Vane Shear Strength Methods

Merge-Optimization Method of Combined Tomography of Seismic Refraction and Resistivity Data

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