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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]

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 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]

A fast effective inversion algorithm is proposed herein to interpret gravitational responses caused by mineralized/ore sources (sphere, vertical and horizontal cylinders). The algorithm relies on local wavenumber and correlation imaging techniques. The correlation factor (R) between the local wavenumber of observed gravitational field and that of computed field was calculated, and the maximum Rmax was considered to correspond to the best true model (parameters). The proposed algorithm was applied to two theoretical examples, including an example contaminated with regional background and another multisource example. Besides, the proposed approach was used on three different real field cases for mining/ore investigation from Canada and Cuba. From the results obtained from the theoretical and real examples and by comparing the results with drilling and literature information, it was concluded that the method is effective, is applicable even for more than one source, is accurate, and does not necessitate any prior knowledge of the source shape. [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]

A new imaging method has been developed for elucidating the observed magnetic data gauged along profile. The method is based on the calculation of the correlation factor (the R-parameter) between the analytic signal of the measured magnetic anomaly and the analytic signal of the calculated response of some geometrically simple interpretive models in the confined category of sheets, cylinders, and spheres. The characteristic parameters (amplitude coefficient, depth, location, approximative shape of the buried structure, and effective angle of magnetization) of the interpretive model correspond to the maximum R-parameter value. The scheme has been verified on a number of noise-free synthetic examples and recovered the actual model parameters. Prior to applying the developed scheme to real-field examples, the accuracy of it has been carefully investigated on synthetic examples which are contaminated with realistic noise levels, interference effects, and regional field. Finally, the method has been successfully applied to three real-field data examples from the USA, Senegal, and Egypt for mineral exploration, and it is found that the obtained results are in good concordance with those obtained from drilling and/or the published literature. [ABSTRACT FROM AUTHOR]