Seismic refraction method is a geophysical method that has been developed for shallow subsurface investigation. It provides 2-dimensional profiles including depth and distance that simplified the characterization of relatively large volumes of the subsurface. Interpretation of seismic refraction data using seismic tomography involves continuous velocity gradient across a subsurface which is more effective for site characterization compared to conventional seismic refraction. Three parallel seismic refraction survey lines were conducted at Kaki Bukit, Perlis with the aim of characterizing the subsurface of the area. 2m geophone spacing was used with total length of 46m. The separation between lines is 20m. Weight drop of 20kg and steel plate were used as seismic source. A total of 20 shotpoints were performed for survey line L1, 23 shotpoints for survey line L2 and 22 shotpoints for survey line L3. The high quality seismic data obtained were then processed using SeisOptPicker and SeisOpt2D software to produce a seismic tomography section for each survey line. Results indicate that the study area is said to have 4 main layers with velocity increase fairly with depth. The first layer with velocity 300-500 m/s predominantly consists of top soil and form overburden. Second layer with velocity 500-800 m/s is suggested to be a highly weathered limestone. The third layer represents by highly fractured limestone with velocity 800-1500m/s. Limestone bedrock represent by the fourth layer with velocity > 2000m/s. Competent limestone bedrock is identified at survey line L3 with velocity > 3000m/s

The 2-D resistivity imaging with Enhancing Horizontal Resolution (EHR) technique is adopted to map and characterize the shallow subsurface (sedimentary, limestone and granite). A sedimentary case study was executed at Nusajaya, Johor, a limestone case study was conducted at Beseri, Kaki Bukit, Perlis while a granite case study was conducted at Masai, Johor (Malaysia). The survey lines 80m and minimum 2m electrode spacing was adopted in each of survey line at Nusajaya, Johor and Beseri, Kaki Bukit, Perlis using Pole-dipole array. The electrode spacing used in Masai, Johor is 5m with survey line 400m. After the data acquisition on the first survey line was complete, the electrodes were shifted to the right on the same line and the process of data acquisition was repeated. The set of data obtained for each line was combined during processing using Res2Dinv software. The inversion model resistivity at Nusajaya shows sandstone contains iron mineral (30-250 ohm-m) and weathered sandstone (500-1000 ohm-m). Beseri, Perlis gives three different layers with resistivity values of 1-50 ohm-m (clay), 125-500 ohm-m (weathered limestone) and 1200-3000 ohm-m (limestone). The results from Masai shows two main zone with resistivity value of 1000 ohm-m (fractured granitic bedrock). The stratigraphy and structure of the three case studies (sedimentary, limestone and granite) can be mapped effectively using 2-D resistivity imaging with EHR technique

We introduce a new seismic-electromagnetic (EM) projection (SEMP) attribute to improve the characterization of pay sands by integrating seismic P impedance and S impedance with electrical resistivity measurements leveraging on the high sensitivity of resistivity to fluid saturation and the capability of seismic data to delineate thin beds. Porosity is predicted using an extended elastic impedance (EEI) approach to reduce the risk of encountering SEMP anomalies related to low porosity. First, we determine the seismic-EM integration concept using well logs from a well that encountered hydrocarbons in a deepwater fold belt in offshore Borneo. The SEMP logs supported by the EEI log successfully delineate the pay zones in the well. Second, we extend the approach in three dimensions and evaluate its effectiveness using large-size seismic controlled-source EM (CSEM) and magnetotelluric (MT) data from the same area. The seismic data are inverted to produce P- and S-impedance volumes. EEI volume calibrated to total porosity also is produced. We then perform 3D anisotropic cross-gradient joint CSEM and MT inversion of a large-size survey comprising 647 receivers with receiver spacing of 1.5–3 km at prospect to regional scale. The SEMP volumes computed using the seismic and CSEM-MT inversion results are then interpreted with the EEI volume to identify possible geobodies of pay sand. Resistive geobodies with low porosity are assigned higher risks because they are likely due to compaction rather than hydrocarbon presence, whereas geobodies with high porosity are assigned lower risks and identified as potential sweet spots. The geobodies need to be corroborated with independent geologic studies to mature them into exploration prospects and assess their associated risk and potential. Although a vertical transverse isotropy approximation is used in our CSEM-MT study, the SEMP concept also is applicable to cases considering tilted transverse isotropy or arbitrary anisotropy where available and operational for such large-size exploration data.

Electrical resistivity technique has become a popular alternative tool by the geotechnical engineers in subsurface investigation. This study presents the influence of soil electrical resistivity value (ERV) due to the different types of electrical resistivity array used in practice. The dissimilarity of ERV was become a popular debate by the engineers which posses less fundamental knowledge in this area. In the past, the theory of electrical resistivity technique was less being discovered by the engineer which creates lots of black boxes during the utilization of electrical resistivity method (ERM) in engineering purposes. Hence, the result which produced from the ERM was difficult to deliver in a sound of definitive ways due to lack of knowledge and experienced of most engineers. Hence, this study presents the influence of soil ERV due to the different types of array used with particular reference to as Dipole-dipole and Pole-dipole. A line of electrical resistivity imaging was performed on small embankment of sandy and lateritic soil with different types of array using ABEM SAS (4000) equipment. Three in line of soil samples were tested for moisture content (w) test immediately after the electrical resistivity data acquisition was completely measured. Moreover, particle size distribution test also was performed for all soil samples in order to support the findings. It was found that the ERV was never be the same for each types of array used even on the same particular location of the survey line. However, it was found that there was a consistent relationship between ERV and moisture content for both types of soil tested which can be represent by ERV 1/w. Hence, it was found that ERV produced was relative to the types of array used during the field measurement. Each types of array were applicable to be used in subsurface profiling and its selection was subjected to the target of interest.

Soft soils pose abundant engineering issues due to its low bearing capacity and shear strength. Comprehensive study on soft soil’s physical properties such as shear strength and ability to store water (porosity) could help in devising the optimum ground improvements and foundations techniques. Therefore, physical properties of soft marine clay in Nibong Tebal were thoroughly studied using 2-Dimensional Resistivity Imaging (2-DRI) method in conjunction with porosity measurements, standard penetration test values (SPT-n) and particle size distribution (PSD) analysis. The 2-DRI profile depicts three lithologies, which are unsaturated topsoil, saturated soft clayey soil and saturated sandy soil in the area. The soft soil extends up to 32 m in thickness where it overlies the sandy layer and could be correlated back to lithology profile from borehole record. Additionally, soil samples were collected at three locations along the survey line for porosity measurements via saturation porosimetry method. The samples demonstrate that the clay layer has a very large porosity range and signifies that the soil will compress tremendously under load. On the other hand, SPT-N values of the soft clay is also very low; thus, could be classed as very soft to soft cohesive soil with very low shear strength as compared to a higher range SPT-n values of the sandy layer. The PSD result also compliments the 2-DRI, porosity and SPT results to show distinct differences between topsoil and the soft clay layer in terms of the presence of fine grains. These results further indicate that the thick upper layer is not capable of bearing immense loads such as high-rise infrastructures due to the soil’s high porosity and low shear strength. Hence, the area must undergo ground remediations prior to any infrastructure developments on the land.