The Micro-resistivity imaging log is a crucial tool for measuring the heterogeneous features of a formation. It objectively and quantitatively describes various reservoir characteristics, including fine structures, thin strata, fissures, and sedimentary facies. In these imaging tools, measurements from button arrays create an electrical image of the wellbore. However, gaps between tool pads limit coverage, and damaged buttons may compromise image quality.In this study, we examine image log data for factors impacting data acquisition, followed by processing for basic correction, image enhancement, and static and dynamic image log creation. To achieve 100% coverage, the Minimum Weighted Norm Interpolation (MWNI) algorithm fills gaps between tool pads. Finally, the Anisotropic Diffusion Filter (ADF) reduces noise and enhances image log quality in MATLAB, providing a comprehensive image from logging tools. As image logs play a crucial role in illustrating the wellbore and reservoir, this study suggests a new workflow to successfully tackle the challenges linked with acquiring comprehensive image log coverage.

Electrical resistivity techniques are well-established and applicable to a wide range of geophysical problems. 2D resistivity measurements can give information about both the lateral and vertical variations of the subsurface resistivity and can be used in a qualitative fashion for the identification of the structure and depth of masses. The resistivity inverse problem involves constructing an estimate of a subsurface resistivity distribution, which is consistent with the experimental data. This is a fully non-linear problem and its treatment involves iterative full matrix inversion algorithms, which can give good quality results. The back-projection resistivity technique (BPRT) can be applied to a set of apparent resistivity measures to quickly obtain an approximate image of the resistivity distribution of the investigated volume. This technique is based on the consideration that a resistivity perturbation in a point element (voxel) of a bounded region produces a change in voltage thus an apparent resistivity anomaly at the surface of the region, according to a sensitivity coefficient. The value of the coefficient is dependent on the position of the voxel considered in respect of both the current and the voltage dipoles, in agreement with the sensitivity theorem of Geselowitz. This consideration suggests that it is possible to correlate all the measured resistivity values, weighted by the appropriate sensitivity coefficients to each voxel of the investigated volume and to estimate the resistivity value of each cell of the model using a weighted summation of the apparent resistivity measurements. The BPRT considering a two-step approach. Initially, a damped least squares solution is obtained after a full matrix inversion of the linearized geoelectrical problem. Furthermore, on the basis of the results, a subsequent filtering algorithm is applied to the Jacobian matrix, aiming at reducing smoothness, and the linearized damped least square inversion is repeated to get the final result. This fast imaging technique aims at increasing the resistivity contrasts, and practically, since it does not require a parameter set optimization, it can be used to easily obtain fast and preliminary results. The procedure proposed in this work consists of four steps: (1) Evaluation of sensitivity matrix B, (2) Inversion of matrix B using a damped LSQR solution, (3) Recalculation of a filtered Jacobian matrix B‘ obtained by means of a correlation filter, (4) Inversion of the filtered sensitivity matrix. The proposed technique is tested on resistivity synthetic data from the Schlumberger, Wenner, Dipole-dipole and Pole-pole arrays, the objective of which is to find the optimal parameter set. The synthetic tests carried out with 2D data suggested that a good compromise for 2D inversions is to choose 𝜆 for the Schlumberger, Wenner, Dipole-dipole and Pole-pole arrays, 0. 1, 20, 1 and 0. 5, respectively. Furthermore, all the synthetic tests carried out with 2D data suggested that a good compromise for 2D inversions is to choose 𝜒 ≈ 5. The approximate images using the BPRT inverse modeling for all synthetic data, with and without random noise, is compared with the least square inversion by RES2DINV software. Finally, a field case is discussed, and the comparison between the back-projection and inversion is shown.

Integrated geoelectrical data modeling aims to produce subsurface electrical models for mineral deposit exploration. These models improve understanding of subsurface lithology and structures. Quantitative interpretation using numerical inversion is crucial for accurate results. This study employs 2D inversion of time-domain electrical resistivity and induced polarization data from three profiles to investigate marble deposits in Iran's Fasa region. This research aims to identify and differentiate the bedrock from the marble deposit. The methods used in this study include electrical resistivity tomography through dipole-dipole and pole-dipole configurations. Based on the obtained results, the separation of the marble stone from the background is illustrated using electrical characteristics. Additionally, the boundaries and the greater continuity of the building stone mass are also discussed. The thickness of the marble layer was determined to range between 10 and 30 meters, In comparison, the surface sandstone/limestone layer displayed thickness variations from zero up to 30 meters, characterized by notably lower electrical resistivity. Furthermore, the induced polarization models revealed the existence of a limestone/marl bed containing marble at depths ranging from 30 to 40 meters. Additionally, the electrical resistivity models indicated that the marble layer located in the southern region is of superior quality compared to that found in the mountain ridge. In the modeling, an attempt has been made to minimize the difference between the observed and predicted apparent values, and accordingly, the RMS error rate was less than 2.

Kangavar city is located at Kermanshah province west of Iran and northern part of Zagros Mountains. Zagros is known to be the most seismic region in Iran. Thus, seismicity and geotechnical Micro-zonation of Kangavar are set the goals of this research. To do this, firstly, following a probabilistic seismic hazard analysis the peak ground acceleration and spectral acceleration on seismic bedrock is elaborated using the CRISIS2007 software. Secondly, to investigate the site conditions series of Microtremor measurements at 15 points in the vicinity of the city is carried out and the natural frequency map and shear wave velocity profile for the ground are determined using Geopsy software. This should note that the thickness of the alluvial is small in northern part of the city. Furthermore, the results of electrical resistivity tests are used to investigate the alluvium depth and discontinuity in ground profile. This analysis confirmed the existence of thicker alluvial in southeast part of the city. Finally, according to all findings of this research a general recommendation for urban planning and future building and construction is proposed according to Iranian national code for earthquake resistant buildings, as a function of three variables; Geo-hazards type, Importance, and lateral resistant structural system.

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where quality characteristic of interest is modelled using binary, multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpose, multinomial log it regression (MLR) is considered as the basis. Then, the MLR is converted to Poisson GLM with log link. Two methods including Multivariate exponentially weighted moving average (MEWMA) statistics, and Likelihood ratio test (LRT) statistics are proposed to monitor MLR profiles in phase II. Performances of these three methods are evaluated by average run length criterion (ARL). A case study from alloy fasteners manufacturing process is used to illustrate the implementation of the proposed approach. Results indicate satisfactory performance for the proposed method.