Samsudin Taib

Using artificial neural networks to invert 2D DC resistivity imaging data for high resistivity contrast regions: A MATLAB application

MATLAB is a high-level matrix/array language with control flow statements and functions. MATLAB has several useful toolboxes to solve complex problems in various fields of science, such as geophysics. In geophysics, the inversion of 2D DC resistivity imaging data is complex due to its non-linearity, especially for high resistivity contrast regions. In this paper, we investigate the applicability of MATLAB to design, train and test a newly developed artificial neural network in inverting 2D DC resistivity imaging data. We used resilient propagation to train the network. The model used to produce synthetic data is a homogeneous medium of 100@Wm resistivity with an embedded anomalous body of 1000@Wm. The location of the anomalous body was moved to different positions within the homogeneous model mesh elements. The synthetic data were generated using a finite element forward modeling code by means of the RES2DMOD. The network was trained using 21 datasets and tested on another 16 synthetic datasets, as well as on real field data. In field data acquisition, the cable covers 120m between the first and the last take-out, with a 3m x-spacing. Three different electrode spacings were measured, which gave a dataset of 330 data points. The interpreted result shows that the trained network was able to invert 2D electrical resistivity imaging data obtained by a Wenner-Schlumberger configuration rapidly and accurately.

Time lapse chemical fertilizer monitoring in agriculture sandy soil

Geoelectrical resistivity, hydrogeochemical and soil properties analysis methods were used for chemical fertilizer monitoring in sandy soil at a palm oil plantation in Machang, Malaysia. The time lapse monitoring was done using these methods five times within a three-month period. The hydrogeochemical analysis was conducted over three auger holes to a depth of 1 m and sampled at 25 cm intervals. Chemical fertilizer was applied to the 21 × 21 m2 area after the first data set measurement. The areas outside of this fertilized zone are considered a nonfertilized zone. The other four data sets were acquired at about equal time intervals, thus giving a four-post fertilization data set. The hydrogeochemical measurements indicate that the cations content are relatively similar for every time lapse measurement. However, relatively higher changes of anions content occur at the surface level to a depth of 1 m. The nitrate concentration above the limit for safe human consumption as it returns to the initial value about 100 days after fertilization. The geoelectrical model prior to fertilization showed similar resistivity values at near surface to a depth of about 75 cm with no significant occurrences of low resistivity values. Lower resistivity values were obtained during the second, third, fourth and fifth measurements within the chemically fertilized zone. In the last measurement, the resistivity values in the fertilized zone are almost similar to the nonfertilized zone. This indicates that the contaminant has dissolved into the surrounding environment within this time period.

Evaluating freshwater lens morphology affected by seawater intrusion using chemistry-resistivity integrated technique: a case study of two different land covers in Carey Island, Malaysia

Freshwater lenses are vital to small island communities but are susceptible to seawater intrusion due to the physical changes in the shoreline land cover. The effect of seawater intrusion and irrigation water on a coastal unconfined aquifer beneath naturally preserved mangrove and deforested mangrove-barren belt was investigated in Carey Island. Analysis of the total dissolved solids (TDS) and earth resistivity (ER) using a geochemistry-electrical integrated technique gave a TDS–ER relationship capable of predicting freshwater lens morphology affected by sea-irrigation water. The study result shows freshwater was fourfold thicker in close proximity of the mangrove forest than the mangrove barren area; the further the shoreline from the mangrove thickest section, the less vulnerable was the seawater intrusion and the more fresh the irrigation water, and hence the greater the freshwater availability potential.

Comparison of Wenner and dipole–dipole arrays in the study of an underground three-dimensional cavity

The objective of this paper was to compare Wenner and dipole-dipole configurations in delineating an underground cavity at a site near the University of Malaya, Malaysia. A three-dimensional electrical resistivity imaging survey was carried out along seven parallel lines using Wenner and dipole-dipole arrays. A three-dimensional least-squares algorithm, based on the robust inversion method, was used in the inversion of the apparent resistivity data. In the inverted model, both the horizontal and vertical extents of the anomalous zones were displayed. Results indicate the superiority of the Wenner array over the dipole-dipole array for determining the vertical distribution of the subsurface resistivity, although the dipole-dipole array produced a better lateral extent of the subsurface features. The results show that the three-dimensional electrical resistivity imaging survey using both the Wenner and dipole-dipole arrays, in combination with an appropriate three-dimensional inversion method and synthetic model analysis, can be highly useful for engineering and environmental applications, especially for underground three-dimensional cavity detection.

Use of Artificial Neural Networks to Invert 3D Electrical Resistivity Imaging Data

The artificial neural network approach has presented to solve 3D resistivity inverse problems included in complex subsurface structure. The 3D synthetic data sets were generated to train the neural network using a finite element forward modeling code. Several artificial neural network algorithms have been tested on a basis of trial and error for training data set. The resilient back propagation paradigm was efficient in training stage. After 1340 epochs, the MSE error as a function of epochs for the combined training data reduced a threshold value (0.00034) and the network was converged. To test the trained network with real field data, the 3D electrical resistivity data was conducted on certain structure with known resistivity and was acquired with the Pole‐Pole configuration. The interpreted results showed, the artificial neural network approach was capable to invert 3D electrical resistivity data as well as synthetic data. The main advantage of this approach for resistivity inversion is that, once the ...