Self-potential Anomalies Research Articles

Hydrogeological structure of a seafloor hydrothermal system deduced from a pair of positive and negative self-potential anomalies observed at the Oomuro-dashi hydrothermal field in the Izu-Ogasawara Arc, south of Japan

This paper presents and interprets two new self-potential data measured over a hydrothermally active field associated with a Quaternary rhyolitic volcano, Oomuro-dashi, in the northern Izu-Ogasawara Arc, south of Japan. The measured data show a pair of positive and negative anomalies of the order of one millivolt at 5 m above the seafloor. The observation of a positive self-potential near a seafloor hydrothermal system is new, in spite that negative self-potential anomalies have been regularly reported in various studies for different locations. Determining the dominant mechanism(s) is therefore key to further understanding the subseafloor structure of seafloor hydrothermal systems. To this end, we also conducted long-term observations of subseafloor temperatures at two sites in the area of the self-potential anomaly to estimate the Darcy velocity. We found a downward fluid flow of the order of tens of metres per year at both sites. The flow in the area of the negative self-potential anomaly is stronger than in the area of the positive anomaly. Based on these observations, we propose two end-member models to explain the paired self-potential anomaly. The first model considers a horizontal geo-battery, in which part of a subhorizontal electrically conductive body is crossed by a subvertical redox front. In this model, the oxidised part of the geo-battery causes a negative self-potential anomaly, as in the previous observations, while the reduced counterpart of the geo-battery, which is normally buried, is exposed near the seafloor and causes a positive anomaly. In this case, a conductive body is expected to lie beneath both anomalies, and we could access the reduced part of the geo-battery. This model is consistent with the results of the Darcy velocity estimation if the strong hydrothermal circulation would cause the redox horizon to deepen. The second model is a combination of the thermal and streaming potentials causing both positive and negative self-potential anomalies. This model does not necessarily require a buried conductive body beneath the self-potential anomalies. These end-member models could be distinguished by resistivity imaging, which identifies the distribution of conductive bodies beneath self-potential anomalies, although they would overlap in natural systems.Graphical

Self-potential Anomalies Associated with Subsurface Electrokinetic and Electric Current Density Coupling in Parts of Southern Nigeria

Self-potential Anomalies Associated with Subsurface Electrokinetic and Electric Current Density Coupling in Parts of Southern Nigeria

Global Optimization of Self-Potential Anomalies Using Hunger Games Search Algorithm

Global Optimization of Self-Potential Anomalies Using Hunger Games Search Algorithm

Modified Barnacles Mating Optimizing Algorithm for the Inversion of Self-potential Anomalies Due to Ore Deposits

The self-potential method (SP) has been used extensively to reveal some model parameters of various ore deposits. However, estimating these parameters can be challenging due to the mathematical nature of the inversion process. To address this issue, we propose here a novel global optimizer called the Modified Barnacles Mating Optimizer (MBMO). We improved upon the original approach by incorporating a variable genital length strategy, a novel barnacle offspring evolving method, and an out-of-bounds correction approach. The MBMO has not been previously applied to geophysical anomalies. Prior to inversion of real data sets, modal and sensitivity Analyzes were conducted using a theoretical model with multiple sources. The Analyzes revealed that the problem is modal in nature, model parameters have varying levels of sensitivity, and an algorithm that can well balance global exploration with local exploitation is required to solve this problem. The MBMO was tested on theoretical SP anomalies and four real datasets from Türkiye, Canada, India, and Germany. Its performance was compared to the original version under equal conditions. Uncertainty determination studies were carried out to comprehend the reliability of the solutions obtained via both algorithms. The findings indicated clearly that the MBMO outperformed its original version in estimating the model parameters from SP anomalies. The modifications presented here improved its ability to search for the global minimum effectively. In addition to geophysical datasets, experiments with 11 challenging benchmark functions demonstrated the advantages of MBMO in optimization problems. Theoretical and field data applications showed that the proposed algorithm can be used effectively in model parameter estimations from SP anomalies of ore deposits with the help of total gradient anomalies.

Modeling of Self Potential (SP) Anomalies over a Polarized Rod with Finite Depth Extents

Modeling is a powerful tool used by Geoscientists to provide pre-knowledge about the expectations of any geophysical field measurements. This study generates Self Potential (SP) anomalies over a typical dike-like structure to observe the influence of depth of burial and dip on SP anomalies. A computer program was developed from the potential distribution equation of an inclined polarized rod with a limited depth extent using Visual Basic (VB) programming language to produce synthetic data for potential distribution. The potential distribution data were used to generate theoretical SP anomaly curves for a polarized rod for varying depth of burial and dip. Twenty SP anomaly curves were generated with different dip values and depth of burial and from these curves, superimposed curves were also generated. The anomalies were analyzed for the effect of depth of burial and attitude or dip. The SP anomaly curves generated show that an increase in depth of burial causes a reduction in the peak negative amplitude of SP anomaly curves. For inclined polarized rod at relatively shallow depth (<2.0 m), the peak negative amplitude remains virtually the same with a positive shoulder over the down dip side of the target. Also as the dip angle decreases from 90o for a fixed depth of burial, the anomaly curves become asymmetrical. At 0o, the distance between the peak negative and peak positive amplitude of the anomaly curve is equal to the linear extent of the rod. Therefore, this study shows that the depth of burial inversely influences the amplitude of self-potential (SP) anomalies while the dip angle affects the form or symmetry of anomaly curves.

Inversion of self-potential anomalies from regular geometric objects by using whale optimization algorithm

Inversion of self-potential anomalies from regular geometric objects by using whale optimization algorithm

Self-Potential as a Tool to Monitor Redox Reactions at an Ore Body: A Sandbox Experiment

Ore bodies generate natural electrical fields that are measurable at the ground surface. The ground surface signature of this electrical field is called a self-potential anomaly. We developed a sandbox experiment to monitor the evolution of a self-potential anomaly associated with redox processes mediated by bacterial activity at the surface of a buried metallic object crossing the water table. A Bio-Electrochemical Cell (BEC) is formed by a metal bar connecting the upper, oxygen-rich, part of the tank and an aquifer containing an electron donor in the form of acetate. The self-potential response was observed during a period of 327 days. The tomography of the self-potential signature confirms that self-potential tomography is able to locate the metallic target acting as a BEC. In addition, we performed redox potential, pH, and electrical potential measurements over a vertical cross-section of the tank at several time steps to obtain an idea of where the redox front is located. The distributions of the redox potential and pH further demonstrated the development of the oxidation-reduction chemical processes facilitated by the BEC as bacterial communities developed around the metallic bar. The electrical potential anomaly shows that the bacterial communities followed a short period of exponential growth, then a longer period of a sustained population. These results demonstrate the usefulness of the self-potential method in monitoring redox processes at the surface of a buried ore body. Further works will need to combine such self-potential anomalies with induced polarization anomalies through joint inversion.

Estimating model parameters from SP anomaly of sheet-shaped sources using differential search and particle swarm optimization algorithms

Abstract In this study, the efficiency of estimating the model parameters of sheet-shaped single and multiple sources of the self-potential (SP) anomaly using the differential search algorithm (DSA) is investigated. First, noise-free and noisy synthetic anomalies are calculated for a single sheet-shaped source, and its model parameters estimated by DSA. The DSA inversion is also done for a model consisting of three inclined sheets. To test the effectiveness of the method, the same processes are repeated with a more conventional algorithm, particle swarm optimization (PSO), and the solutions of both methods are compared. The results of synthetic anomaly analyses show that DSA can predict the parameters as accurately as PSO. Then, both algorithms are also applied to two field SP anomalies (Surda and Beldih) that have been evaluated by different algorithms in the literature. The source of the Surda anomaly is modelled as one sheet, whereas the source model of the Beldih anomaly is assumed to consist of three sheets. The five model parameters for each model are estimated using both algorithms and it is determined that they are in good agreement with the findings of the previous studies. The contribution of the regional background anomaly to the synthetic and field anomalies are also included and regional coefficients are estimated. Finally, we conclude that DSA can solve the source parameters without the need for the initial values required in conventional iterative inversion methods and is an efficient and promising algorithm for determining the parameters of SP sources.

Self-Adaptive Bare-Bones Teaching–Learning-Based Optimization for Inversion of Multiple Self-Potential Anomaly Sources

Self-Adaptive Bare-Bones Teaching–Learning-Based Optimization for Inversion of Multiple Self-Potential Anomaly Sources

Multiphysics Modeling of Volcanic Unrest at Mt. Ruapehu (New Zealand)

AbstractPre‐eruptive signals at the crater lake‐bearing Mt. Ruapehu (New Zealand) are either absent or hard to identify. Here, we report on geophysical anomalies arising from hydrothermal unrest (HTU) and magmatic unrest (MU) using multiphysics numerical modeling. Distinct spatio‐temporal anomalies are revealed when jointly solving for ground displacements and changes in gravitational and electrical potential fields for a set of subsurface disturbances including magma recharge and anomalous hydrothermal flow. Protracted hydrothermal injections induce measurable surface displacements (>0.5 cm) at Ruapehu's summit plateau, while magmatic pressurization (5–20 MPa) results in ground displacements below detection limits. Source density changes of 10 kg/m3 (MU simulations) and CO2 fluxes between 2,150 and 3,600 t/d (HTU simulations) induce resolvable residual gravity changes between +8 and −8 μGal at the plateau. Absolute self‐potential (SP) anomalies are predicted to vary between 0.3 and 2.5 mV for all unrest simulations and exceed the detection limit of conventional electric surveying. Parameter space exploration indicates that variations of up to 400% in the Biot‐Willis coefficient produce negligible differences in surface displacement in MU simulations, but strongly impact surface displacement in HTU simulations. Our interpretation of the findings is that monitoring of changes in SP and gravity should permit insights into MU at Ruapehu, while HTU is best characterized using ground displacements, residual gravity changes and SP anomalies. Our findings are useful to inform multiparameter monitoring strategies at Ruapehu and other volcanoes hosting crater lakes.

Inversion and Uncertainty Estimation of Self-Potential Anomalies over a Two-Dimensional Dipping Layer/Bed: Application to Mineral Exploration, and Archaeological Targets

Self-Potential data have been widely used in numerous applications. The interpretation of SP data from subsurface bodies is quite challenging. The advantages of geophysical inversion for interpreting non-linear geophysical problems have gained a great deal of attention over conventional interpretation. The efficiency of the present inversion approach in interpreting SP anomalies from a thin dipping layer/bed is presented in the study. The inversion approach was applied to interpret synthetic model parameters such as the self-potential of the layer (k), depth to the body top (h), location of the body (x0), dip angle (θ), and the upper and lower end of the sheet (δ1 and δ2). The interpretation of the results showed that the parameters Δh, δ1, and δ2 exhibited a wide range of results. The estimated parameter values lay within the limit of uncertainty. The inversion approach was also applied to two field datasets obtained from polymetallic deposits in Russia and Azerbaijan for mineral exploration purposes and one from a buried ancient Roman limestone construction in Halutza, Israel, for the purposes of archaeological study. The field investigation results demonstrate a good agreement with previous works of literature. The efficiency of the present approach for interpreting SP anomalies from thin layer/bed-like structures is shown in this study.

Cuckoo Search Algorithm for model parameter estimation from self-potential data

The use of the Cuckoo Search Algorithm (CSA) is introduced for estimating the model parameters from both synthetic and field self-potential (SP) anomalies in this study. The CSA offers a simple and efficient way to optimization studies as a popular nature-inspired metaheuristic algorithm because it requires only two algorithm-based parameters (the number of population and probability of recognition of the egg), and instead of isotropic random walks, it employs Lévy flights for search. This work presents the first application of the CSA for inversion of SP anomalies in geophysics. The test studies with the synthetic data included the cases of the noise-free and noisy data. Additionally, the Bavarian (Germany), Süleymanköy (Turkey) and Malachite (Colorado, USA) anomalies, which are the well-studied benchmark field data sets in the literature, were tested with the field data. An uncertainty appraisal analysis was performed for each model parameter via the Metropolis-Hastings algorithm. Also, the estimated parameters from the CSA were compared with the previous studies used a variety of metaheuristic methods to invert the same field data sets. According to the results, the CSA can be integrated into the inversion of SP anomalies as an efficient alternative method.

A Fast Method for Interpretation of Self-Potential Anomalies Due to Buried Bodies of Simple Geometry

A Fast Method for Interpretation of Self-Potential Anomalies Due to Buried Bodies of Simple Geometry

Inversion of self-potential anomalies caused by simple polarized bodies based on particle swarm optimization

Inversion of self-potential anomalies caused by simple polarized bodies based on particle swarm optimization

Investigation of Scale-Dependent Groundwater/Surface-water Exchange in Rivers by Gradient Self-Potential Logging: Numerical Modeling and Field Experiments

Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.

Review of Processing and Interpretation of Self-Potential Anomalies: Transfer of Methodologies Developed in Magnetic Prospecting

The self-potential (SP) method is one of the most inexpensive and unsophisticated geophysical methods. However, its application is limited due to the absence of a reliable interpreting methodology for the complex geological-environmental conditions. To exclude disturbances appearing in the SP method, a few ways for their removal (elimination) before quantitative analysis are presented. A brief review of the available interpretation methods is included. For the magnetic method of geophysical prospecting, special quantitative procedures applicable under complex physical-geological environments (oblique polarization, uneven terrain relief and unknown level of the normal field), have been developed. The detected common peculiarities between the magnetic and SP fields make it possible to apply the advanced procedures developed in magnetic prospecting to the SP method. Besides the reliable determination of the depth of anomalous targets, these methodologies enable the calculation of the corrections for non-horizontal SP observations and to determine the orientation of the polarization vector. For the classification of SP anomalies, is proposed to use a new parameter: the ‘self-potential moment’. The quantitative procedures (improved modifications of characteristic point, tangent techniques and the areal method) including the determination of the SP vector and SP moment, have been successfully tested on models and employed in real situations in mining, archaeological, environmental and technogenic geophysics. The obtained results indicate the effectiveness of the presented methodologies.

Numerical Modeling of Marine Self-Potential from a Seafloor Hydrothermal Ore Deposit

The redox field generated by electrically conductive minerals is one of the main constituents of self-potentials. It can be explained by electrochemical reactions in which conductors participate. The location and outline of seafloor hydrothermal ore deposits can be detected using marine self-potential anomalies that can be approximated through a marine geobattery model. The numerical modeling of marine self-potentials could be the foundation of corresponding data inversion and interpretation and improving the application effect of the self-potential method in detecting seafloor hydrothermal ore deposits. In this study, the inert electrode model and the on-land geobattery model are introduced to build the marine geobattery model, and the finite-infinite element coupling method is derived to deal with the truncated boundary problem effectively. Also, two tests are conducted to study the effect of model parameters on ground self-potential anomalies. A seafloor sulfide deposit model is built to study the self-potential characteristics. The numerical modeling results suggest that the precision and efficiency of the coupled method are superior to that of the traditional finite element method. Self-potential anomalies are greatly affected by medium resistivity, complex terrain, and amplitudes of embedded redox fields. Gradient changes in embedded redox fields do not cause significant self-potential anomalies but lead to mutations of current sources. The self-potential anomaly from the sulfide deposit model shows that the self-potential method can be effectively used to explore seafloor hydrothermal deposits that accompany negative self-potential anomalies above the ore bodies. The coupled method is quite suitable for multi-source models such as self-potential models.

Integration of shallow geoelectrical investigations for delineating the hidden water springs, case study: Ayun Mousa, Northern Gulf of Suez, Egypt

Ayun Mousa area lies at the northern part of the Eastern Gulf of Suez. It has a world-wide reputation for its touristic, historical and religious concepts for the skyey believers (Muslims, Christians and Jewfishes). The already known Ayun (water springs) Mousa are seven, while the hidden are five. Therefore, it is planned to adapt these geoelectrical surveys to explore the five concealed ayun. The used shallow geoelectric methods are: the natural self-potential, the artificial vertical electrical sounding and two-dimensional electrical resistivity tomography. This is to trace these ayun laterally and vertically. The self-potential measurements were done using high impedance voltmeter and porous pots containing saturated solution of copper sulfate through four parts of the study area (A, B, C and D). Also, the vertical electrical resistivity measurements were acquired, using Eleric-T instrument, through Schlumberger array for six VESes, three to the north and three to the south directions. Moreover, the two-dimensional electrical resistivity tomography measurements were been accomplished, using Eleric-T instrument through six profiles, based on the results of the spontaneous polarization positive anomalies. However, the self-potential anomalies succeeded to outline the SP anomalies around seven of these ayun and other number of positive SP anomalies, defining the ambiguous ayun. Both types of these ayun were affected by a major NNW-SSE normal fault throwing westward and dissected by a number of ENE-WSW strike-slip faults. The VES results succeeded to subdivide the shallow section into five layers of varying rock and water contents, consequently defined the layers saturated with water and those barren, without any indication about the sites of known and unknown ayun. Finally, the ERT results succeeded to follow the seven already discovered ayun and other seven unknown ones. By this way, it is recommend to carryout GPR profiles, to reduce the seven unknown ayun into five.

Model parameter estimation and its uncertainty for 2-D inclined sheet structure in self-potential data using crow search algorithm

Fracture or fault can control several geological or geophysical events and exploration, where the fault associated with mineralization or fluid flow can be used as a source for Self-Potential (SP) anomaly. The 2-D inclined sheet can be used for modeling for fault interpretation using SP data. In this paper, the improved crow search algorithm (ICSA) using Levy flight is proposed for SP data inversion in determining SP model parameters. In order to evaluate ICSA, the ICSA is compared with standard crow search algorithm (CSA) for determining synthetic SP data that contains multiple anomalies with inclined sheet type structures. It was found that CSA is more explorative than ICSA, and both algorithms can estimate the posterior distribution model (PDM) of SP data. Using uncertainty analysis within the applied threshold in the objective function, both algorithms are reliable to determine PDM. Furthermore, ICSA is tested and implemented to both synthetic and field of SP anomalies for providing the posterior distribution model of SP parameters. The experimental results demonstrate that the ICSA is feasible and effective for determining model parameters and its uncertainty of mono- and multi-SP anomalies. Furthermore, estimating both model parameter and its uncertainty are sufficient for validation with previous researchers. Finally, the interpretation of multiple anomalies in SP anomaly crossing the Grindulu Fault in Pacitan, East Java, Indonesia, is analyzed.

Modeling shallow self-potential anomalies over electronic conductors

Field measurements of self-potential indicate that anomalies may be divided in a shallow anomaly and a deep anomaly. This paper presents a new understanding of the current flow causing SP-anomalies, and how this can be modeled by using the analogy between magnetic flux density lines and electric current lines. Mathematical models are presented for shallow SP-anomalies. Several older models may be applied for the deep part of the anomaly. The new model is applied for interpretation of an SP-anomaly from the KTB drilling site in Oberpfalz in Germany. The deep part was interpreted using a plate model which has been known for years. The final curves of the measured anomaly and the calculated curves for the shallow part and the deep part of the anomaly are presented.