Search

This study introduces a rapid and efficient inversion algorithm designed for the interpretation of self-potential responses originating from mineralized and ore sources and hydrothermal activity, specifically addressing spherical, vertical, and horizontal cylindrical structures. The algorithm leverages local wavenumber and correlation imaging techniques to enhance accuracy in modeling. The correlation factor (Cf value) is crucial in this approach, calculated as the correlation between the local wavenumber of the measured self-potential field and that of the computed field. The algorithm identifies the maximum correlation Cf value (CF-max) as indicative of the optimal true model parameters. To validate the proposed algorithm, it was applied to three theoretical examples—one with contamination from regional background and another with multiple sources with and without different types of noises (random Gaussian and white Gaussian noises). Additionally, the approach was tested on three distinct real field cases related to mining, ore investigation and hydrothermal activity in India, Germany and USA. Through a comprehensive analysis of results from theoretical and real-world scenarios, including comparisons with different available data and literature information, the study concludes that the method is effective, applicable to multiple sources, accurate, and does not necessitate prior knowledge of the source shape. This algorithm presents a promising advancement in the field of self-potential interpretation for mineral exploration and geothermal exploration. [ABSTRACT FROM AUTHOR]

The Bat optimizing algorithm (BOA) is one of the metaheuristic algorithms and applied here to interpret self-potential (SP) data. The BOA is depending upon a bat echolocation behavior for global optimization, which the global optimum solution reached at the suggested minimum value of the objective function. The best interpretive source parameters for the subsurface structures occurred at the minimal the objective function value (global best solution). The BOA is applied to 2D SP anomaly data to estimate the characteristic source parameters (i.e., the depth to center, amplitude coefficient, origin location, geometric shape factor, and polarization and inclination angle of the causative buried structure). The BOA can be applied to single and multiple source structures in the restricted class of simple geometric shapes, which these bodies help in the validation of the subsurface ore and mineral targets. The stability and efficiency of the proposed BOA have been examined by several synthetic examples. In addition, three different real field examples from Germany and Indonesia have been successfully applied to ore and mineral investigation and geological structure studies. In general, the achieved results are in good agreement with the available borehole data and results mentioned in the literature. [ABSTRACT FROM AUTHOR]

Metaheuristic algorithms are increasingly being utilized as a global optimal method in the inversion and modeling of magnetic data. We proposed the Bat Algorithm Optimization (BAO) technique that is based on bat echolocation performance to find the global optimum solution. The best-estimated source parameters that correspond to the objective function minimum value are obtained after achieving the global optimum (best) solution. The suggested BAO technique does not require any prior knowledge; rather, it is a global search method that provides an effective tool for scanning the space of data to appraise sources parameters. The BAO technique is applied to magnetic data in the class of dipping and vertical dikes along 2D profiles to estimate the dimensional source parameters that include the depth to top, origin location, amplitude coefficient, index angle of magnetization, and width of the dipping dikes. The BAO technique has been used for single and multiple dikes structures. The accuracy and stability of the BAO technique are achieved on different synthetic examples of free and noisy data for single and multiple cases. Furthermore, the presented BAO technique was effectively utilized in three field examples from China and Egypt for iron ore deposits and metavolcanics basalt rock investigations. Overall, the BAO technique recovered inversion outcomes are in good agreement with borehole, geology, and published literature results. [ABSTRACT FROM AUTHOR]

We have developed an algorithm to obtain the model parameters for two co-axial structures from selfpotential data. The method uses the first numerical horizontal derivatives calculated from the observed self-potential anomaly employing filters of sequential window lengths (s-values) so as to gauge the model constraints for the shallow and deep structures. In addition, this algorithm uses a standard inversion method for solving a non-linear equation based on the lowest root-mean-square (RMS) error of the estimated model parameters. The body constraints are the depth, polarization angle and electric dipole moment of each structure. Our approach models the self-potential dataset as an aggregation of spheres, horizontal cylinders, and vertical cylinders. These simple bodies are used to approximate, without a priori expectations, the furthermost plausible position and/or area of intersection. In other words, the bodies are used to estimate the true values of the source parameters for the two-co-axial bodies at different s-values. Minimizing the RMS error has the advantage of optimizing all model factors. The proposed technique is tested using a numerical model with and without noise and on self-potential field data acquired at a site in Germany. In all cases, the assessed body parameters are reasonable approximations of the known values. [ABSTRACT FROM AUTHOR]

Geophysical methods, especially the gravity method, are very helpful in ore and mineral explorations. Here, gravity modeling and interpretation for the subsurface geologic structures generally assumes either homogenous or spatially varying densities within target source rocks and surrounding structures. Therefore, the use of simple-geometric bodies helps in the validation of the subsurface ore and mineral targets. A Bat optimization algorithm is a recently developed metaheuristic algorithm that is used in various geophysical applications to explore and explain the parameters of buried ore and mineral targets. Using the Bat optimization algorithm, we were elucidating gravity anomaly profiles for ore and mineral cases. To perform global optimization, the Bat optimization algorithm is based on the echolocation behavior of bats. The global optimum solution in the Bat optimization algorithm reached the suggested minimum value of the objective function. The Bat optimization algorithm is applied to gravity data to estimate the target parameters (e.g., amplitude coefficient, depth, origin location, and geometric shape). The stability and efficiency of the introduced optimizing algorithm have been checked on two synthetic models represented in a spherical model and an infinitely horizontal cylinder model using two different kinds of noise. Furthermore, successful applications of the proposed algorithm for discovering the ore and minerals in Canada, Cuba, and India were presented. The results match well with the available geological and borehole information and other results from the published literature. [ABSTRACT FROM AUTHOR]

We describe a rapid imaging approach for the interpretation of self-potential data collected along profile by some geometrically simple model of cylinders and spheres. The approach calculates the correlation coefficient between the analytic signal (AS) of the observed self-potential measurements and the AS of the self-potential signature of the idealized model. The depth, electric dipole moment, polarization angle, and center are the inverse parameters we aim to extract from the imaging approach for the interpretative model, and they pertain to the highest value of the correlation coefficient. The approach is demonstrated on noise-free numerical experiments, and reproduced the true model parameters. The accuracy and stability of the proposed approach are examined on numerical experiments contaminated with realistic noise levels and regional fields prior to the interpretation of real data. Following that, five real field examples from geothermal systems and mineral exploration have been successfully analyzed. The results agree well with the published research. [ABSTRACT FROM AUTHOR]

The near-surface groundwater aquifer that threatened the Great Pyramids of Giza, Egypt, was investigated using integrated geophysical surveys. A total of 10 electrical resistivity imaging, 26 shallow seismic refraction, and 19 ground-penetrating radar surveys were conducted in the Giza Plateau. Collected data for each method were evaluated by state-of-the art processing and modeling techniques. A three-layer model depicts the subsurface layers and better delineates the groundwater aquifer and water table elevation. The resistivity of the aquifer layer and seismic velocity vary between 40 and 80 Ω m and between 1500 and 2500 m s -1 , respectively. The average water table elevation is about + 15 m, which is safe for the Great Sphinx, but it is still subjected to potential hazards from the Nazlet El-Samman suburb where the water table elevation reaches 17 m. A shallower water table at the Valley Temple and the tomb of Queen Khentkawes, with a low topographic relief, represents severe hazards. It can be concluded that a perched groundwater table is detected in the elevated topography to the west and southwest that might be due to runoff and capillary seepage. [ABSTRACT FROM AUTHOR]

Geophysical studies were performed along selected locations across the Pyramids Plateau to investigate the groundwater table and the near aquifer, which harmfully affected the existed monuments of the Giza Pyramids and Sphinx. Electrical Resistivity Imaging (ERI), Shallow Seismic Refraction (SSR) and Ground Penetrating Radar (GPR) techniques were carried out along selected profiles in the plateau. Ten ERI, twenty six SSR and nineteen GPR profiles were performed at the sites. The ERI survey shows that, the groundwater table is at elevations varying from 13 to 18 m above the sea level (asl) and low resistivity values near the surface at the Great Sphinx. ERI profiles, which were applied southeast of the Middle Pyramid (Khafre), show high resistivity values near the surface, and water table is located at elevations ranging from 22 to 40 m asl, while the ERI profiles conducted south of Menkaure, show almost high resistivity near the surface. The groundwater table is located at elevations ranging between 45 and 58 m asl. The aquifer layer shows electrical resistivities ranging between 10 and 50 Ohm.m. The considerable high change in the groundwater table is due to the rapid increases of topography from the Great Sphinx towards the Small Pyramids (Menkaure), where this part looks-like a scarp. The SSR Survey is transmitted to know the different velocities and types of the layers, which can help in knowing the saturated layers in the area. The GPR Survey is performed to delineate the water table, which gives good matching with the ERI results. [ABSTRACT FROM AUTHOR]

• The R-parameter imaging technique for interpreting gravity data. • The method is based on the analytic signal of observed and synthetic responses. • The maximum R-parameter value is the criterion in determining the true parameters. • The accuracy of this technique is verified on numerical and real data sets. This paper describes a fast imaging technique, the so-called here the "R-parameter imaging technique", for the interpretation of gravity data measured along profile. The technique calculates the R-parameter (a statistical parameter called the correlation coefficient) between the analytic signal of the measured gravity field and that of the synthetic response of an assumed interpretive model in the restricted class of spheres and cylinders. The characteristic source parameters (depth, shape, origin point of the gravity profile, and amplitude factor) of the model correspond to the maximum R-parameter value. The method has been verified on noise free numerical examples. Following that, the accuracy of the method has been carefully assessed on both noisy numerical examples and numerical examples with interference effects. Finally, the technique has been successfully applied to five field data examples from Canada, Sweden and Cuba for mineral exploration, and it is found that the obtained results are in good agreement with those reported in the published literature. [ABSTRACT FROM AUTHOR]