Interpretation Of Self-potential Data Research Articles

Seepage identification of Sidoarjo mud embankment via 2D resistivity and self-potential methods

Assessment of embankment stability is one of the ways to discover the embankment condition. Several factors can affect the strength of the embankment body including seepage, leakage, deformation (vertical and horizontal), and overtopping. Hence, identification of seepage in the subsurface of the embankment is important to provide early information about the threat of embankment failures. Sidoarjo mud (LUSI) embankment has been collapsed several times since it built in 2006. Most of the failures are mainly caused by the existing water seepage in the subsurface of the embankment. To identify the seepage pathways of the embankment body, two non-destructive geo-electricity methods were applied in the LUSI embankment. Direct current resistivity (DCR) and self-potential (SP) methods were carried out to reconstruct subsurface conditions at lines P76-P79. Therefore, seepage interpretation was conducted to identify the presence of water flows through the embankment body. 2D tomography of resistivity data revealed the indication of water seepage in some measurement areas. This information was strengthened by the numerical interpretation of self-potential data, recognizing water seepage through the embankment body in each line.

A fast imaging method for the interpretation of self-potential data with application to geothermal systems and mineral investigation

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.

Penentuan Kedalaman dan Sudut Kemiringan Sesar Grindulu di Pacitan Menggunakan Metode Crow Search Algorithm (CSA) pada Data Self-Potential (SP)

Self-Potential (SP) is a geophysical survey method that is relatively easy and inexpensive. Interpretation of SP data can be used for various purposes such as the detection of landslide-prone areas, exploration of various types of minerals, and identification of the parameters of a fault or crack. In this study, SP data acquisition was carried out in Tambakrejo Village, Pacitan District with a total of 102 measurement data which aims to determine the depth and dip of the Grindulu Fault. SP data acquired in the field needs to be corrected for reference, namely corrections caused by a displacement of the starting point of measurement. This data is then filtered to increase the signal-to-noise ratio (SNR) and sharpen the resulting anomalies. This filtering process is carried out using the ICEEMD (Improved Complete Ensemble Empirical Mode Decomposition) method which is a development of the EMD method. Furthermore, the SP data inversion process to obtain model parameters is carried out by utilizing the CSA (Crow Search Algorithm) method. Based on the anomaly model generated from the SP data inversion process, it can be concluded that the Grindulu Fault was identified at a distance of 803,8 meters from the starting point of measurement with depths ranging from 11,06 to 102,74 meters. Furthermore, based on distance, depth, and anomaly shape data, the dip value can be calculated. The calculation results show that the dip of the Grindulu Fault in the study area is 75.58o. Identification of the Grindulu Fault in the form of depth and dip is very important in efforts to model the fault comprehensively.

An efficient global optimization method for self-potential data inversion using micro-differential evolution

Self-potential (SP) method has many applications, where the interpretation of SP data can be used for qualitative and quantitative interpretation. However, inversion of SP data in this paper is of quantitative interpretation and consists of highly non-linear, multimodal data and deploys global optimum method (GOM). Micro-differential evolution (MDE) is a GOM with small or micro-population size (5–8 populations) for each iteration. Consequently, this approach involves small numbers of forward computation in the inversion process. Two MDE variants, including adaptive MDE ( $$ \mu $$ JADE) and vectorized random mutation factor (MVDE) were tested first for different level of noises containing synthetic SP data with single anomaly and applied to synthetic SP data of multiple anomalies. The MDE variants are reliable and effective for inverting noisy SP data. Furthermore, in order to check the rationality of MDE variants, the algorithm is applied to seven field data from different applications, including groundwater exploration, shear zone tracing, water accumulation in landslides and embankment stability assessment. The model parameters revealed by MDE variants are accurate and show good agreement with the previous results estimated using other approaches. In addition, MDE variants also require fewer forward modelling calculations than other optimization approaches.

A Novel Approach to Self-potential Data Interpretation in Support of Mineral Resource Development

A new efficient technique has been developed to interpret self-potential data from different mineralized sources (horizontal cylinder, vertical cylinder, sphere, and 2-D inclined sheet). This technique is based on the first horizontal gradient filter and particle swarm optimization algorithm. This suggested method can be used for single-source and multiple-source interpretation. In this study, the developed technique was applied to five different synthetic examples (vertical cylinder model, horizontal cylinder model, sphere model, 2-D inclined sheet model, and multi-source model), using a real case from Canada—the multi-source field example—and two real cases from India. The results obtained from the synthetic and real data show that the method is fast, accurate, and effective in removing the regional background and does not require information regarding body shape. The results of the real data cases match well with the results obtained from other published methods.

THERMAL COUPLING MODELLING WITH THE VES AND SP DATA OF BURSA-ACEMLER REGION

Doğada, basınç, sıcaklık ve derişim farklılığı nedeniyle uçlaşma akımları meydana gelir. Doğal potansiyel (DP) yöntemi, yorumlama çalışmalarında geleneksel olarak kullanılagelen popüler jeofizik araç olup, bu yöntem uçlaşma akımlarının yarattığı doğal potansiyel farklarının ölçülmesine dayanır. Bu çalışmada, ısıl uçlaşma problemi kümelenmiş elemanlar ağı modeli ile çözülerek bir jeotermal alana uygulanmıştır. Bu yöntemin diğer geleneksel jeofizik yöntemlere kıyasla temel üstünlüğü, incelenen sistemin karmaşık doğası hakkında daha detaylı bilgi verebilmesidir. Bursa ili Çekirge Mahallesi’nin kuzeybatısında yer alan Acemler Mevkiinden toplanan düşey elektrik sondaj (DES) ve DP verileri öncelikle geleneksel yöntemlerle(ters çözüm) değerlendirilmiş, elde edilen parametreler kullanılarak alanın ısıl uçlaşma modeli kurulmuştur. Böylece jeotermal alan için en uygun termal ve jeofizik parametre değerleri, kaynak yerleri ve sayıları ile jeolojik birimlerin geometrik yapıları saptanmıştır. Bu çalışma ile elde edilen sonuçlar, ısıl uçlaşma yönteminin DP verilerinin yorumlanmasında güçlü bir araç oluşturduğunu ve jeotermal sistemlerin çeşitli özelliklerinin belirlenmesinde etkin şekilde kullanılabileceğini göstermiştir.

Estimating Model Parameters from Self-Potential Anomaly of 2D Inclined Sheet Using Whale Optimization Algorithm: Applications to Mineral Exploration and Tracing Shear Zones

The use of spontaneous potential (SP) anomalies is well known in the geophysical literatures because of its effectiveness and significance in solving many complex problems in mineral exploration. The inverse problem of self-potential data interpretation is generally ill-posed and nonlinear. Methods based on derivative analysis usually fail to reach the optimal solution (global minimum) and trapped in a local minimum. A new simple heuristic solution to SP anomalies due to 2D inclined sheet of infinite horizontal length is investigated in this study to solve these problems. This method is based on utilizing whale optimization algorithm (WOA) as an effective heuristic solution to the inverse problem of self-potential field due to a 2D inclined sheet. In this context, the WOA was applied first to synthetic example, where the effect of the random noise was examined and the method revealed good results using proper MATLAB code. The technique was then applied on several real field profiles from different localities aiming to determine the parameters of mineralized zones or the associated shear zones. The inversion parameters revealed that WOA detected accurately the unknown parameters and showed a good validation when compared with the published inversion methods.

Analysis of Self-Potential Response beyond the Fixed Geometry Technique

The self-potential (SP) method is one of the oldest geophysical methods that are still available for today’s application. Since its early days SP data interpretation has been done qualitatively until the emerging of the fixed geometry analysis that was used to characterize the orientation and the electric-dipole properties of a mineral ore structure. Through the expansion of fundamental theories, computational methods, field-and-lab experiments in the last fifteen years, SP method has emerge from its low-class reputation to become more respectable. It became a complementary package alongside electric-resistivity tomography (ERT) for detecting groundwater flow in the subsurface, and extends to the hydrothermal flow in geothermal areas. As the analysis of SP data becomes more quantitative, its potential applications become more diverse. In this paper, we will show examples of our current SP studies such as the groundwater flow characterization inside a fault area. Lastly we will introduce the application of the "active" SP method - that is the seismoelectric method - which can be used for 4D real-time monitoring systems.

A new approach for the interpretation of self-potential data by 2-D inclined plate

A new accurate technique has been developed to interpret self-potential (SP) data (d) measured along a profile by a two-dimensional (2-D) inclined plate-like body. The technique solves for the depth (z) to top and half-width (w) of the body, and is based on the second horizontal gradient (SHG) that is calculated at a number of window lengths. Using points symmetrically distributed about the origin point of the SP profile, the scheme derives and evaluates a function F at various window lengths from the measured SP anomaly profile. At a fixed window length (s), the depth corresponding to an assumed half-width is determined by solving a nonlinear equation in the form φ (d, s, w, z)=0. The depths corresponding to all considered windows are then obtained at the assumed width. The standard deviation of these depths is calculated for this width. This process is repeated for various widths. The final solution (the depth and half-width) of the interpretive buried structure is that which achieves the least standard deviation. The validity and accuracy of the new scheme has been demonstrated on theoretical noise free and noisy SP data. It has been successfully applied to two real data, and it is found that the parameters estimated from the scheme described here are in good agreement with those reported in the published literature.

Integrated geophysical studies to elicit the subsurface structures associated with Uranium mineralization around South Purulia Shear Zone, India: A review

South Purulia Shear Zone in India is an important zone that hosts uranium mineralization. Since detailed geophysical studies have not been carried out in this region, an integrated geophysical study using self-potential, resistivity, very low frequency electromagnetic and radiometric methods was performed to identify the subsurface structures that could host the hydrothermally altered uranium deposits in the area. The study reveals the wide and large magnitude of negative self-potential anomaly across the South Purulia Shear Zone. The peak negative self-potential anomalies are correlated with the low gravity and low resistivity anomalies measured along various profiles. The low self-potential, gravity and low resistivity anomaly zones are also correlated with conducting zones inferred from very low frequency electromagnetic measurements. Interpretation of self-potential data reveals multiple thick sheet-type vertical and/or inclined structures which might be associated with uranium mineralization. Schlumberger resistivity sounding data reveals an increasing trend of apparent resistivity with current electrode separations/depth. Apparent conductance measured simultaneously with resistivity measurement reveals an increase in current flow of current as depth increases. This exhibits the presence of thin conducting layers at these depths, which is not reflected in resistivity sounding data due to suppression problem. Also this conducting layer is consistent in various soundings and is connected from Raghunathpur to the South Purulia Shear Zone. Correlation of very low frequency and self-potential data shows that the structures are comparable and a radiometric profile also advocate that the conducting structure is associated with radioactive minerals. These structures are likely to be mineralized zones as hydro-uranium anomaly has also been reported from various locations in the area. Moreover, drilling results at a specific mine near the study area also confirms the presence of uranium mineralization. The hydrothermal activity associated with uranium mineralization seems to be still active in the area. Such combined geophysical studies are essential to understand this highly complex shear zone for the economic exploitation of its natural resources.

Interpretation of self-potential anomaly over a 2D inclined structure using very fast simulated-annealing global optimization — An insight about ambiguity

A very fast simulated-annealing (VFSA) global optimization procedure is developed for the interpretation of self-potential (SP) anomaly measured over a 2D inclined sheet-type structure. Model parameters such as electric current dipole density ([Formula: see text]), horizontal and vertical locations of the center of the causative body ([Formula: see text] and [Formula: see text]), half-width ([Formula: see text]), and polarization/inclination angle ([Formula: see text]) of the sheet are optimized. VFSA optimization yields a large number of well-fitting solutions in a vast model space. Even though the assumed model space (minimum and maximum limits for each model parameter) is appropriate, it has been observed that models obtained by the VFSA process in the predefined model space could also be geologically erroneous. This offers new insight into the interpretation of self-potential data. Our optimization results indicate that there exist at least two sets of solutions that can fit the observed data equally well. The first set of solutions represents a local optimum and is geologically inappropriate. The second set of solutions represents the actual subsurface structure. The mean model estimated from the latter models represents the global solution. The efficacy of the developed approach has been demonstrated using various synthetic examples. Field data from the Surda area of Rakha Mines, India and the Bavarian woods, Germany are also interpreted. The computation time for finding this versatile solution is very short (52 s on a simple PC) and the proposed approach is found to be more advantageous than other approaches.

A fast interpretation of self-potential data using the depth from extreme points method

We used a fast method to interpret self-potential data: the depth from extreme points (DEXP) method. This is an imaging method transforming self-potential data, or their derivatives, into a quantity proportional to the source distribution. It is based on upward continuing of the field to a number of altitudes and then multiplying the continued data with a scaling law of those altitudes. The scaling law is in the form of a power law of the altitudes, with an exponent equal to half of the structural index, a source parameter related to the type of source. The method is autoconsistent because the structural index is basically determined by analyzing the scaling function, which is defined as the derivative of the logarithm of the self-potential (or of its [Formula: see text]th derivative) with respect to the logarithm of the altitudes. So, the DEXP method does not need a priori information on the self-potential sources and yields effective information about their depth and shape/typology. Important features of the DEXP method are its high-resolution power and stability, resulting from the combined effect of a stable operator (upward continuation) and a high-order differentiation operator. We tested how to estimate the depth to the source in two ways: (1) at the positions of the extreme points in the DEXP transformed map and (2) at the intersection of the lines of the absolute values of the potential or of its derivative (geometrical method). The method was demonstrated using synthetic data of isolated sources and using a multisource model. The method is particularly suited to handle noisy data, because it is stable even using high-order derivatives of the self-potential. We discussed some real data sets: Malachite Mine, Colorado (USA), the Sariyer area (Turkey), and the Bender area (India). The estimated depths and structural indices agree well with the known information.

Application of Differential Evolution Algorithm on Self-Potential Data

Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces, and has been successfully used to solve several kinds of problems. In this paper, differential evolution is used for quantitative interpretation of self-potential data in geophysics. Six parameters are estimated including the electrical dipole moment, the depth of the source, the distance from the origin, the polarization angle and the regional coefficients. This study considers three kinds of data from Turkey: noise-free data, contaminated synthetic data, and Field example. The differential evolution and the corresponding model parameters are constructed as regards the number of the generations. Then, we show the vibration of the parameters at the vicinity of the low misfit area. Moreover, we show how the frequency distribution of each parameter is related to the number of the DE iteration. Experimental results show the DE can be used for solving the quantitative interpretation of self-potential data efficiently compared with previous methods.

Application of particle swarm optimization on self-potential data

Particle swarm optimization (PSO) is a global search method, which can be used for quantitative interpretation of self-potential data in geophysics. At the result of this process, parameters of a source model, e.g., the electrical dipole moment , the depth of the source, the distance from the origin, the polarization angle and regional coefficients are estimated. This study investigates the results and interpretation of a detailed numerical data of some simple body responses, contaminated and field data. The method is applied to three field examples from Turkey and the results are compared with the previous works. The statistics of particle swarm optimization and the corresponding model parameters are analyzed with respect to the number of generation. We also present the oscillations of the model parameters at the vicinity of the low misfit area. Further, we show how the model parameters and absolute frequencies are related to the total number of PSO iterations. Gaussian noise shifts the low misfit area region from the correct parameter values proportional to the level of errors, which directly affects the result of the PSO method. These effects also give some ambiguity of the model parameters. However, the statistical analyses help to decrease these ambiguities in order to find the correct values. Thus, the findings suggest that PSO can be used for quantitative interpretation of self-potential data. Particle swarm optimization (PSO) has been investigated on self-potential data. PSO has been applied to some synthetic, noise added, and field data. A model response of a cylinder and its fitness can be seen in Fig. 1a–b. Fig. 2 shows the low misfit regions. Oscillations of the model parameters are displayed in Fig. 3. Fig. 4 illustrates frequency distribution of the cylinder model for all parameters. ► Particle swarm optimization. ► Effect of errors and low misfit region. ► Frequency distribution of model parameters. ► PSO application on SP data.

A new algorithm for gravity or self-potential data interpretation

An inversion algorithm is developed to estimate the depth and the associated model parameters of the anomalous body from the gravity or self-potential (SP) whole measured data. The problem of the depth (z) estimation from the observed data has been transformed into a nonlinear equation of the form F(z) = 0. This equation is then solved for z by minimizing an objective functional in the least-squares sense. Using the estimated depth, the polarization angle and the dipole moment or the depth and the amplitude coefficient are computed from the measured SP or gravity data, respectively. The method is based on determining the root mean square (RMS) of the depths estimated from using all s-values for each shape factor. The minimum RMS is used as a criterion for estimating the correct shape and depth of the buried structure. When the correct shape factor is used, the RMS of the depths is always less than the RMS computed using wrong shape factors. The proposed approach is applicable to a class of geometrically simple anomalous bodies, such as the semi-infinite vertical cylinder, the dike, the horizontal cylinder and the sphere, and it is tested and verified on synthetic examples with and without noise. This technique is also successfully applied to four real datasets for mineral exploration, and it is found that the estimated depths and the associated model parameters are in good agreement with the actual values.

Galvanic interpretation of self‐potential signals associated with microbial sulfate‐reduction

We have evaluated the usefulness of the self‐potential (SP) geophysical method to track the onset and location of microbial sulfate‐reduction in saturated sediments during organic carbon amendment. Following stimulation of sulfate‐reducing bacteria (SRB) by addition of lactate, anomalous voltages exceeding 600 mV correlated in space and time with the accumulation of dissolved sulfide. Abiotic experiments in which the sulfide concentration at the measurement electrode was systematically varied showed a positive correlation between the magnitude of the SP anomaly and differences in the half‐cell potential associated with the measurement and reference electrodes. Thus, we infer that the SP anomalies resulted from electrochemical differences that developed between sulfide‐rich regions and areas having higher oxidation potential. In neither experiment did generation of an SP anomaly require the presence of an in situ electronic conductor, as is required by other models. These findings emphasize the importance of incorporation of electrochemical effects at electrode surfaces in interpretation of SP data from geophysical studies. We conclude that SP measurements provide a minimally invasive means for monitoring stimulated sulfate‐reduction within saturated sediments.

Combined application of surface geoelectrical methods for groundwater flow modeling: A case history

Electrical methods [electrical profiling and sounding, induced polarization (IP), and self-potential (SP)], combined with geochemical and hydrochemical surveys, were applied to characterize shallow sediments at a site contaminated by oil-related brines. The site is located within the Romashkinskoye oil field (Tatarstan Republic, Russian Federation). Results of geochemical and hydrochemical surveys, as well as those of electrical profiling, revealed no individual haloes of contaminant in the soil and groundwater, which suggests that the entire site is contaminated. Vertical electrical IP soundings (VES-IP) allowed us to obtain the stratigraphic characteristics of the site and to distinguish a shallow aquifer among clayey aquitards. Interpretation of SP data on the basis of forward numerical modeling helped us to develop a groundwater-flow model of the site. To reduce ambiguities, we kept fixed the values of layer resistivity derived from the inverted VES-IP data. Boundary conditions on water head and water flow were based on drilling and sampling data. We varied only the values of hydraulic conductivity to fit the calculated SP values to the measured SP values. We found a strong misfit between the measured and calculated SP values for the one-aquifer model. By inferring a second, deeper-seated aquifer, we computed a two-aquifer model that produced a satisfactory SP fit.

Interpretation of self potential data for vertical and nearly vertical sheets of infinite horizontal extension

Quantitative interpretation of SP anomalies due to vertical and nearly vertical, thin sheets of infinite horizontal extension has been developed in this paper. The methods proposed utilise selective SP values at some selected points on the profile thus enabling us to get the different parameters of the causative body directly. Also, for the case of vertical sheet, an interpretation technique has been formulated when the base station is within the zone of influence of the potential field of the causative body.

NEW INTERPRETATION TECHNIQUES FOR TELLURIC AND SOME DIRECT CURRENT FIELDS

Since the normal derivative of the telluric potential at the ground surface is zero, the odd terms in the Taylor expansion disappear, resulting in a simple technique of computing the downward continued potentials. The top of the nonconducting basement is a flow surface and can, therefore, be determined by sketching in curves orthogonal to the (continued) equipotential lines in suitably chosen sections. A model tank example is given. The applicability of the method of continuation to the interpretation of self potential data is also illustrated. A discussion of the derivatives, two limiting formulas, and a method for calculating telluric anomalies are included.