Self-potential Signals Research Articles

Groundwater flow paths using combined self-potential, electrical resistivity, and induced polarization signals

SUMMARY The dam of Lampy (Black Mountain, Aude, France) is considered as one of the oldest dams in France. A geophysical survey is performed to better understand the pattern of groundwater flow downstream of this dam in the granitic substratum. Induced polarization is first used to image both electrical conductivity and normalized chargeability. Eight core samples of granite from this site are measured and analysed in the laboratory. Their electrical conductivity and normalized chargeability are expressed as a function of the porosity and cation exchange capacity (CEC). The field data and the petrophysical results are used to image the water content, the CEC and the permeability distribution of the substratum. Then, self-potential is used as a complementary passive geophysical technique, which, in absence of metallic bodies, is directly sensitive to groundwater flow through the so-called streaming potential effect. Indeed, the excess of electrical charges in the vicinity of the solid grains, in the so-called double layer, is dragged by the ground water flow generating in turn an electrical (streaming) current and therefore an electrical field. A map of the resulting self-potential signals is done over the area covered by the induced polarization profiles. This map shows a large positive anomaly with an amplitude of ∼80 mV possibly associated with upwelling groundwater in an area where the soil is water-saturated. A groundwater flow simulation is performed to model this anomaly. This is done in two steps. A preliminary groundwater flow model is built using the permeability and water content distributions obtained from the induced polarization data. Then, this groundwater flow model is updated using the information contained in the self-potential data including the electrical conductivity distribution obtained through resistivity tomography. The algorithm for the inversion of the self-potential data is validated through a 2-D numerical test. This analysis yields a groundwater flow model with the flow being focused through a high permeability zone. This study shows how three geoelectrical methods (self-potential, induced polarization and electrical resistivity) can be efficiently combined to image groundwater flow in the vicinity of a dam.

Time-lapse self-potential signals from microbial processes: A laboratory perspective

Microorganisms play a critical role in hydrocarbon degradation, contaminant sequestration, and pollution monitoring. However, the complex relationships between microbial processes and geological media's physical and chemical properties remain ambiguous. The self-potential (SP) is an efficient, low-cost, and nonintrusive passive geophysical technique suitable for monitoring dynamic activities. Herein, we conducted the 3D monitoring experiments to obtain time-lapse SP signals generated from cultivating typical microorganisms (Shewanella oneidensis MR-1) under laboratory-controlled conditions. The 3D multi-channel SP experimental devices enable dynamic monitoring and measurement of weak signals. At the beginning of the experiment, we observed a rapid increase in SP signals that consist mainly of the streaming potential and the redox potential. The peak values of negative anomalies monitored in the two experiments were − 75.9 mV and − 59.5 mV, respectively. During subsequent monitoring, the abnormal potential signal gradually decreased. After a sufficient period, the amplitude of the SP generated solely by the Shewanella oneidensis MR-1 activities ranged from −45 to −35 mV. Our laboratory research paves the way for developing dynamic model data to link the self-potential response with microbial processes. Then, we inverted the measured SP data to obtain the current source density distribution. The consistency of current density results and anomalous potentials shows that SP data collected by pre-buried non-polarizable electrodes can be utilized as a direct indicator signal for spatiotemporal monitoring of microbial activities. The SP method shows promise in environmental bioremediation and biodegradation.

Compact source inversion of self-potential data generated by geomicrobes

The self-potential (SP) method is a classical geophysical exploration method which has a wide application prospect in underground pollutant monitoring and other fields. However, due to the complexity of the formation mechanism and the lack of prior information, there are still quite a few difficulties in the precise quantitative inversion of the SP sources, and qualitative interpretation is frequently adopted in practical applications. In this work, we carry out inversion research on the SP data of geomicrobes to accurately invert and locate the spatial distribution of the SP sources which is closely relevant to microbial activities. The resistivity-based depth weighting matrix is added to the inversion algorithm to promote the migration of the SP sources from the earth surface to their original depth. And to conform to the actual distribution of the SP sources, the minimum support stabilizing function is introduced to impose additional compact constraint. Two synthetic models are firstly designed to verify the effectiveness and accuracy of the proposed algorithm. On this basis, the sandbox experiment that continuously observes and records the SP signals generated by the typical organism: Shiwanella Oneida MR-1 breaking down the organic matter is carried out. Then the observed data is inverted to locate the SP sources. The inversion results demonstrate that with the addition of Shiwanella Oneida MR-1 into the humus, the negative SP source immediately appear on the top of the humus, which increase sharply, then remain stable and then slowly decay over time. The negative SP sources are concentrated on the top of the humus, which is consistent with the theoretical analysis of the biogeobattery model.

Hydrothermal fluid circulation within the restless structural frame of Hasandağ volcanic system (Central Anatolia, Türkiye) inferred from Self-potential, CO2, and temperature measurements

Hasandağ is an active composite volcanic system located in the Central Anatolian Volcanic Province (CAVP). A comprehensive field survey was conducted to reveal the hydrothermal activity within the Hasandağ volcanic system, with particular emphasis on Self-Potential (SP) mapping. The Hasandağ system is characterised by the presence of twin stratovolcanoes that arise from pre-existing partially buried calderas. In conjunction with the SP measurements, carbon dioxide concentration (CO2) and surface temperature (ST) measurements were taken. The temperature measurements were elaborated with thermal infrared remote (TIR) sensing methods. The SP results, with a peak-to-peak magnitude of 3.8 Volts, revealed the presence of a significant hydrothermal input in both of the twin cones, characterised by a typical W-shaped anomaly commonly observed in active volcanoes. The highest SP signal coincides with the active fumarole zone at the western flank of G. Hasandağ summit, where we measured ∼70 °C vapour temperatures and relatively high CO2 output (>100,000 ppm). The SP/elevation (Ce) gradient assisted in revealing the hydrothermal and hydrogeological zonation, providing substantial evidence of the relationship between hydrothermal circulation and the structural frame of the volcano. Integrated evaluation of SP, CO2, and temperature data revealed the structural control on the hydrothermal and hydrogeological circulation, with the contribution of Hasandağ, Karacaören, and Karkın Faults as major structural components. The partially buried rim of the Hasandağ caldera was revealed through the detection of a ‘double Ce-low’ signal, providing valuable insights on the dimensions of the structure and its role in the hydrogeological cycle of the system. The extent and magnitude of the hydrothermal activity observed, the Holocene eruptive history of the volcano, and its proximity to populated areas denote the requirement of further geophysical and geochronological research and the necessity of hazard assessment and instrumental monitoring.

Application of Non-negative Matrix Factorization in Processing Self-potential Signals Caused by Geo-microbe

Microorganisms play a significant role in the evolutionary process of the Earth and are closely related to the modification and evolution of the Earth’s surface circles at different spatial and temporal scales. Given geological microbiology in the self-potential signal data can be represented with non-negative matrix, which makes use of non-negative matrix factorization method to deal with the data become possible. This paper introduces the basic principle of non-negative matrix factorization method, based on non-negative matrix factorization method is discussed to isolate the self-potential signal data in geological microbes may and effect. By separating two natural potential signals containing noise with blind sources, the separation effect is good and the non-negative matrix factorization method is found to be an effective method for extracting their self-potential signal data. Although this numerical simulation is the self-potential signal is introduced in the work of geological microbiology, but this method also has reference significance for other signal data processing, can also be used to other geophysical data processing, the implementation of the research on environmental protection, to improve the cognitive complex biological geological process of shallow earth environment has important significance.

Geophysical research of underground hydraulic structures, old Glubochinsky water tunnel case study

Research objective is to study the features of geophysical fields and parameters in the area of the artificial underground water tunnel and estimate the capabilities of geophysical methods of identifying hidden underground industrial facilities. Methods of research. Measurements of self-potential signals (SP) were carried out using nonpolarizing electrodes and an electrical exploration receiver. The magnetic exploration was carried out by a proton magnetometer. Electrotomography was carried out using multielectrode electrical survey equipment with a Schlumberger symmetrical scheme of surveys. The microseismic background was recorded using an autonomous seismic station. The georadar survey was carried out using the SIR-3000 ground penetrating radar and antennas with the frequencies of 100 MHz and 270 MHz. Results. Based on the survey results, graphs of magnetic and self-potential fields, electrotomographic and microseismic sections, and radarogram were built on the research profile. The research has shown different levels of the magnetic field and the SP in the area of volcanic rocks and dikes of gabbro-dolerites occurrence. A significant increase in microseismic noise was observed with an increase in the weathering crust thickness. A local decrease in the SP potential, abnormally high values of specific electrical resistivity and intensive reflections of radio waves from the tunnel top were recorded above the underground water tunnel. Conclusions. Qualitative and quantitative geophysical characteristics were obtained in the area of the old underground water tunnel. The research showed different levels of the magnetic field and spontaneous polarization potentials in the occurrence area of rocks of different composition. A significant increase in microseismic noise was recorded with an increase in the weathering crust thickness. Geophysical signs of the boundaries between geological structures and artificial underground objects are revealed. The exact position and depth of the old underground tunnel of Glubochinsky hydraulic structures was determined.

A review on theory, modeling, inversion, and application of self-potential in marine mineral exploration

The self-potential (SP) method is one of the passive geophysical exploration techniques, which employs measurements of naturally occurring electric potential differences on the ground surface and in boreholes or (sea-)water due to causative sources from electrochemical, electrokinetic, and thermoelectric mechanisms. SP signals are directly related to groundwater flow and (electro-)chemical gradient. There has been increasing interest in the application of SP measurements in mineral exploration, environmental surveys, and hydrogeophysical problems. This review focuses primarily on the theory concerning the causative source mechanism, numerical modeling, and inversion and interpretation of SP signals related to ore bodies and applications in mineral exploration. Three field examples focusing on seafloor sulfide deposits exploration are summarized to show the application effect of SP measurements in marine mineral exploration. This study would be helpful to investigating the use of SP surveys in ore prospecting, especially in marine environments.

Statistical analysis for biogeochemical processes in a sandy column with dynamic hydrologic regimes using spectral induced polarization (SIP) and self-potential (SP)

SUMMARYThe capillary fringe (CF) is characterized by transient and steep redox gradients and is thought to be a hot spot for biogeochemical processes. Understanding chemical fate and transport in the CF is significant, however, biogeochemical dynamics at the CF are poorly understood because of the difficulty to measure representatively with high spatio-temporal resolution at depths under dynamic hydrologic regimes. Hydrogeophysics is a developing field that uses minimally intrusive and quick response methods to monitor hydrological properties. Two geoelectrical methods [spectral induced polarization (SIP) and self-potential (SP)], which are sensitive to the solid–liquid interfaces (SIP) and biogeochemical processes (SP) can address the above difficulty. The challenge lies on linking the geoelectrical responses with biogeochemical processes, where many different processes contribute to the signals. We conducted a soil column experiment under five hydrologic regimes focusing on nitrogen transformations with SIP and SP measurements: (1) a static regime with a stable water level; (2) an infiltration regime with periodic pulse infiltration events with a constant water level and (3) fluctuating regimes with water level fluctuations under three drying-wetting frequencies (6/12/18-day-cycle). This is the first large lab-scale work in a well-controlled and highly instrumented soil column. The dynamic hydrologic conditions stimulated complex biogeochemical processes at the CF, and therefore the SIP and SP signals result from many physical and biogeochemical processes. Therefore, we relied on statistical analysis in this study for a novel interpretation. Spearman correlation analysis supported water content played the most important role in real conductivity (σ′) dynamics in the vadose zone, whereas fluid conductivity dominated σ′ in the saturated zone. Both correlation analysis and spatial moment analysis implicated that water content was the driving factor for both σ′ and imaginary conductivity (σ″). A multiple linear regression model indicated the gradient of redox potential, the gradient of soil matric potential and water content were the three main influencing factors for the SP signals. We proposed that the water level fluctuation can efficiently facilitate microbial electron transfer through ions transport between the different redox zones, and aggregate redox processes to create SP signal gradients. Depth zonation analysis, using six environmental indexes (Eh and nitrogen species; water content; real conductivity; imaginary conductivity; SP signal; microbial community composition), suggested that water content induced by soil hydrology was the most dominant factor, captured by all the indexes. In turn, it led to indirect inference on biogeochemical processes and resultant geoelectrical signals. Applying geoelectrical methods to such biogeochemical processes will not only lead to a better understanding of the mechanistic meanings of the geoelectrical signals, but also build relationships between geoelectrical signals and biogeochemical parameters to facilitate a novel way to monitor biogeochemical processes.

Laboratory simulations of self-potential signals to assist groundwater studies

We present a brief history of experimental simulations with electrokinetic potential signals observed when common porous geological media are subjected to water flow regimes. The laboratory simulations at Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG) of the Universidade de São Paulo (USP) had to overcome several challenges over years of research work, by developing experimental design, choice of materials, and software development to guide real data interpretation and definition of acquisition procedures to be implemented in practice. In this commemorative issue honouring the IAG/USP graduate program, we discuss some of our former results, including a set of original data for two laboratory experiments developed. The first experiment characterizes electrokinetic signals under controlled pumping regimes to illustrate the sensitivity of such potentials to structures with contrasting properties. The second study discusses model response for discrete fractures to guide field data interpretation to determine the hydraulic head in unconnected fractured systems by monitoring the variation of the electrokinetic potential after a borehole is pumped. In both cases, the experimental simulations are useful to understand the electric potentials of electrokinetic origin, pointing out their advantages in characterizing the subsurface hydraulic conditions when a borehole is pumped.

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Geochemistry and reactive transport play a critical role in many fields. In particular, calcite dissolution and precipitation are chemical processes occurring ubiquitously in the Earth’s subsurface. Therefore, understanding and quantifying them are necessary for various applications (e.g., water resources, reservoirs, geo-engineering). These fundamental geochemical processes can be monitored using the self-potential (SP) method, which is sensitive to pore space changes, water mineralization, and mineral–solution interactions. However, there is a lack of physics-based models linking geochemical processes to the SP response. Thus, in this study, we develop the first geochemical–geophysical fully coupled multi-species numerical workflow to predict the SP electrochemical response. This workflow is based on reactive transport simulation and the computation of a new expression for the electro-diffusive coupling for multiple ionic species. We apply this workflow to calcite dissolution and precipitation experiments, performed for this study and focused on SP monitoring alternating with sample electrical conductivity (EC) measurements. We carried out this experimental part on a column packed with calcite grains, equipped for multichannel SP and EC monitoring and subjected to alternating dissolution or precipitation conditions. From this combined experimental investigation and numerical analysis, the SP method shows clear responses related to ionic concentration gradients, well reproduced with electro-diffusive simulation, and no measurable electrokinetic coupling. This novel coupled approach allows us to determine and predict the location of the reactive zone. The workflow developed for this study opens new perspectives for SP applications to characterize biogeochemical processes in reactive porous media.

ANALISIS SINYAL SEISMIK DAN SELF POTENTIAL (SP) DARI FENOMENA SEIMOELEKTRIK DI GUNUNG LUMPUR BLEDUG KUWU JAWA TENGAH

Abstarct Bledug Kuwu is one of the mud volcano (gunung lumpur) in Java. Bledug Kuwu eruption periodically occured with a frequency of more than five times in one minute, pointed by the release of gas bubbles and mud. This study aims to observe the signals of the seismic and self potential (SP) from seismoelectric phenomenon generated by Bledug Kuwu eruption. Measurements were performed by placed seismic sensor around the main crater point of Bledug Kuwu mud volcano, while the SP sensor placed in the vertical, the radial and tangential direction from the point of the main crater of a Bledug Kuwu mud volcano.. The result of analysis shows that the dominant frequency of seismic events is 0,2 Hz, while dominant frequency of SP signals is 48,0 Hz. The arrival time difference between seismic and SP signals predominantly in the range of time (0,0 to 1,5 second) which indicates that the appears of the seismic signal causes the appearance of the signal SP as a result of the transfer fluid as described in the seismoelectric phenomenon.The average value of the amplitude of seismic events for Z, NS and EW component is 0,6694, 0,4848 and 0,5158 Count/Volt. The average value of the amplitude of SP events for Z, NS and EW component is 1,338, 1,249 and 0,909 mVolt. SP events will appear if amplitude of seismic events more than 0,2 Count value. Amplitude of sesmic events proportional to the amplitude of the SP event with value of the correlation coefficient between the both is more than 80.0%, the seismic events caused the material in its path have excessive pressure that pore fluid in the material move and cause the separation of charge is the source of the appear of SP signal, the greater the amplitude of the seismic event the pressure exerted on the material so that the larger the amplitude of the SP events formed also getting bigger, this is in accordance with the theory of the seismoelectric phenomenon by electrokinetic effect mechanismKeyword: Bledug Kuwu, Self Potential (SP), seismic, dominant frequency, different arrival time, amplitude and seismoelectric effect.

Characterization of the non-Gaussian hydraulic conductivity field via deep learning-based inversion of hydraulic-head and self-potential data

Accurate characterization of the spatial heterogeneity of hydraulic properties such as hydraulic conductivity (K) is essential for understanding groundwater flow and contaminant transport processes. Deep learning-based ensemble smoother methods have proven to be effective in estimating non-Gaussian K fields by assimilating hydrodynamic measurements. However, traditional hydrogeological investigations (e.g., hydraulic tomography) often suffer from the limited number of invasive borehole data (e.g., hydraulic head), making the non-Gaussian K inversion problem strongly underdetermined. As a non-invasive and high-sampling-density geophysical approach, the self-potential (SP) method can measure fluctuations of the electrical field caused by subsurface fluid movement. Thus, the recorded SP signals are electro-kinetic responses of the groundwater flow and can provide complementary information for delineating non-Gaussian heterogeneity. In this paper, we performed a joint hydrogeophysical inversion of hydraulic-head and SP data to characterize the non-Gaussian K field within a deep learning-based inversion framework. We conducted three synthetic cases in a 3-D non-Gaussian aquifer with 16,000 unknown K, to assess the ability of the proposed joint inversion framework for K imaging by assimilating different types of data. The results show that using limited hydraulic-head data alone may capture the large-scale features of the non-Gaussian reference field but might lose fine features. By integrating the hydraulic-head and SP data, the non-Gaussian K field can be reconstructed with an improved accuracy and reduced estimation uncertainty. The low-cost SP method opens up new opportunities for non-Gaussian K characterization and fluid-dynamic monitoring.

Numerical modeling of self-potential in heterogeneous reservoirs

Monitoring water movement toward production wells through downhole measurements of self-potential (SP) is a promising new technology. However, there are uncertainties about its applicability in heterogeneous, multilayered reservoirs. Using numerical modeling, we investigated the likely magnitude and behavior of SP during oil production supported by water injection in two different models of such reservoirs. We found that the magnitude of the SP signal that would be measured along a production well increased as water approached the well, exceeding an assumed noise level of 0.1 mV before water breakthrough. We also found that, in the reservoir models tested, the maximum value of SP at the well skewed toward the fastest waterfront before water breakthrough. The trend of SP increasing at the well with time, together with the shape of the SP profile, were the prime indicators used to investigate water movement. In the reservoir models tested, before water breakthrough the fastest approaching waterfront could be detected approximately 20 m away from the well. However, subsequent waterfronts approaching the well in other layers could not be detected before breakthrough. The effect of these later waterfronts on the SP profile at the well was only detectable at breakthrough. We attributed this to the fact that the SP generated in these layers is masked by the high SP created by the fastest waterfront. Our findings emphasized the importance of an enhanced understanding of reservoir geology and rock electrical properties for better prediction and interpretation of SP.

Laboratory Measurements of Zeta Potential in Fractured Lewisian Gneiss: Implications for the Characterization of Flow in Fractured Crystalline Bedrock

Despite the broad range of interest and possible applications, the controls on the electric surface charge and the zeta potential of gneiss at conditions relevant to naturally fractured systems remain unreported. There are no published zeta potential measurements conducted in such systems at equilibrium, hence, the effects of composition, concentration and pressure remain unknown. This study reports zeta potential values for the first time measured in a fractured Lewisian gneiss sample saturated with NaCl solutions of various concentrations, artificial seawater and artificial groundwater solutions under equilibrium conditions at confining pressures of 4 MPa and 7 MPa. The constituent minerals of the sample were identified using X-ray diffraction and linked to the concentration and composition dependence of the zeta potential. The results reported in this study demonstrate that the zeta potential remained negative for all tested solutions and concentrations. However, the values of the zeta potential of our Lewisian gneiss sample were found to be unique and dissimilar to pure minerals such as quartz, calcite, mica or feldspar. Moreover, the measured zeta potentials were smaller in magnitude in the experiments with artificial complex solutions compared with those measured with NaCl, thus suggesting that divalent ions (Ca2+, Mg2+ and SO42−) acted as potential determining ions. The zeta potential was also found to be independent of salinity in the NaCl experiments, which is unusual for most reported data. We also investigated the impact of fracture aperture on the electrokinetic response and found that surface electrical conductivity remained negligibly small across the range of the tested confining pressures. Our novel results are an essential first step for interpreting field self-potential (SP) signals and facilitate a way forward for characterization of water flow through fractured basement aquifers.

Towards the development of an automated electrical self-potential sensor of melt and rainwater flow in snow

AbstractTo understand snow structure and snowmelt timing, information about flows of liquid water within the snowpack is essential. Models can make predictions using explicit representations of physical processes, or through parameterization, but it is difficult to verify simulations. In situ observations generally measure bulk quantities. Where internal snowpack measurements are made, they tend to be destructive and unsuitable for continuous monitoring. Here, we present a novel method for in situ monitoring of water flow in seasonal snow using the electrical self-potential (SP) geophysical method. A prototype geophysical array was installed at Col de Porte (France) in October 2018. Snow hydrological and meteorological observations were also collected. Results for two periods of hydrological interest during winter 2018–19 (a marked period of diurnal melting and refreezing, and a rain-on-snow event) show that the electrical SP method is sensitive to internal water flow. Water flow was detected by SP signals before it was measured in conventional snowmelt lysimeters at the base of the snowpack. This initial feasibility study shows the utility of the SP method as a non-destructive snow sensor. Future development should include combining SP measurements with a high-resolution snow physics model to improve prediction of melt timing.

Coupled inversion of hydraulic and self‐potential data from transient outflow experiments to estimate soil petrophysical properties

AbstractHydraulicproperties of soils could play an important role in affecting the partitioning of precipitation in the critical zone. In addition to traditional approaches, in the last two decades, many geophysical methods have been used to aid the hydrologic characterization and measurement of geological materials. In particular, the self‐potential (SP) method shows great potential in these hydrogeophysical applications. The objective of this study is to evaluate whether the addition of SP data can improve the estimation of hydraulic properties of soils in an outflow experiment. A stochastic, coupled hydrogeophysical inversion was developed, in which the governing equations were solved using the finite volume method and the parameter estimation was conducted using a Bayesian approach associated with the Markov chain Monte Carlo technique. The results show that the addition of SP data in the inversion could reduce the uncertainty related to the estimated hydraulic parameters of soils and the length of the associated 95% confidence interval can be shortened by ∼1/3. It is also shown that the electrical properties of soils at saturated and unsaturated conditions may also be estimated from the outflow experiment when SP data are available. Compared with hydraulic parameters, the accuracy of the estimated electrical properties is slightly lower. Among them, the saturated streaming potential coupling coefficientCsathas the highest accuracy and lowest uncertainty sinceCsatdirectly influences the magnitude of SP signals. The accuracy of other electrical parameters is lower than that ofCsat(and hydraulic parameters), and the associated uncertainty can be one order of magnitude larger.

Discussions on landslide types and seismic signals produced by the soil rupture due to seepage and retrogressive erosion

Seismic signals are usually generated during landslides or movement of soil mass due to collisions and friction among the soil particles and masses. The seismic signals will be different when different sliding (movement) types occur. This study discusses the landslide process and seismic signals produced by soil ruptures to understand the nature of the signals, which could help in predicting landslides as well as understanding different landslide processes. Physical model tests were performed to record the seismic signals generated during the sliding processes. The self-potential (SP), pore water pressure (PP), and volumetric water content (VWC) were also measured to assist the interpretation of the failure processes. Based on the characteristics of the seismic signals recorded, three slide types were identified: intermittent slide, successive slide, and single slide. Precursor signals prior to the single slide event were found in both the seismic and SP signals and therefore the monitoring of these two kinds of precursors has the potential for real-world application in landslide prewarning. In addition, the landslide areas of the tests were correlated with Arias intensities (IA) in a linear relationship. The relationship has the potential to be implemented in estimating a landslide’s scale for a fast landslide response decision.

Autonomous-underwater-vehicle-based marine multicomponent self-potential method: observation scheme and navigational correction

Abstract. Marine self-potential (SP) investigation is an effective method to study deep-sea hydrothermal vents and seafloor sulfide deposits. At present, one of the commonly used marine self-potential systems is a towed array of electrodes. Large noises are recorded when great changes in electrode distance and array attitude occur due to the complex seafloor topography. In this paper, a new multicomponent electrical field observation system based on an autonomous underwater vehicle (AUV) was introduced for the measurement of seafloor self-potential signals. The system was tested in a lake, and the multicomponent self-potential data were collected from there. Observed data involve the navigational information of the AUV, which could be corrected using a rotation transform. After navigational correction, measured data can recover the location of the artificial source using self-potential tomography. The experimental results showed that the new SP system can be applied to marine SP observations, providing an efficient and low-noise SP acquisition method for marine resources and environmental investigations.

A practical approach for self-potential data acquisition, processing, and visualization

We have developed a comprehensive methodology for the acquisition and processing of self-potential (SP) data, as well as some keys for the interpretation of the results. The wide applicability of the SP method and its low cost make it a popular method to use in a variety of natural environments. Despite its versatility and the fact that various published journal papers describe the method and its applications, we believe that there is an important need for a dedicated, peer-reviewed SP acquisition, processing, and visualization/interpretation paper in the scientific literature. We have identified great interest from the scientific community for such a journal paper as a guide for existing and new practitioners with their SP survey design, data acquisition, robust processing, and initial interpretation steps. We have developed a step-by-step methodology for SP data acquisition and processing, combined with practical guidance for the interpretation of collected and processed SP data, including an evaluation of common errors and typical sources of uncertainty. Our examples are based on studies in volcanic environments (e.g., hydrothermal systems); however, the processing steps and methodology are fully applicable and transferable across disciplines to SP data acquired in any environment, and for a wide variety of applications. We evaluated the field acquisition method and the low-cost equipment, the reference and closure corrections, their meaning for the SP signal, and their effect on the data set. The benefits of interpolating SP data in two steps are examined. Combining map visualization, SP versus distance, and SP versus elevation graphs appears to be a highly effective strategy to interpret the signal in terms of hydrogeologic and hydrothermal domains and to highlight structural limits in volcanic contexts as well as in other environments.

Numerical modelling of self-potential in subsurface reservoirs

We report a new, open-source, MATLAB-based 3D code for numerically simulating the self-potential (SP) in subsurface reservoirs. The code works as a post-processor, using outputs from existing reservoir flow and transport simulators at a selected timestep to calculate the SP throughout the reservoir model. The material properties required to calculate the SP are user defined and may be constant or vary in each cell. The code solves the equations governing flow and transport of electrical charge and global charge conservation using a control-volume-finite-difference scheme. Electrical currents associated with the SP may spread beyond the reservoir model domain, and the code allows for the domain to be extended vertically and laterally to account for this. Here, we present the governing equations and the numerical method used and demonstrate application of the code using an example in which we predict the SP signals associated with oil production from a subsurface reservoir supported by water injection.