Self-potential Data Research Articles

Time‐lapse inversion of self‐potential data through particle filtering

AbstractIn environmental sciences, comprehending the movement of subsurface contaminants is crucial for formulating effective remediation measures. The self‐potential (SP) method has become a common tool for delineating landfill contamination plumes. Contaminant diffusion or migration represents dynamic processes, with corresponding SP responses evolving over time. However, conventional SP interpretation approaches have predominantly relied on static single‐frame inversion, overlooking the temporal correlation in time‐series SP data and resulting in cumulative errors. To tackle this challenge, we introduce a novel method for time‐lapse inversion of SP data leveraging particle filtering. This approach recursively refines the priori state model through posteriori observations to achieve precise estimations of dynamic models. Specifically, a spherical polarization model is deployed to establish the state equations of underground contaminant diffusion and transport models, whereas the observation model is derived through forward modeling. The proposed method is validated using two synthetic examples and one lab‐measured dataset. The findings demonstrate the efficacy of the time‐lapse inversion algorithm in precisely estimating dynamic models, outperforming static single‐frame inversion based on the particle swarm optimization algorithm. The posteriori distribution of particles approximates a bell‐shaped distribution, with the true state closely positioned near the peak probability. Therefore, we affirm that conducting time‐lapse inversion of time‐series SP data through particle filtering is an effective and dependable approach for accurately estimating dynamic model states.

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

The structural elements controlling the subsurface mineralization as deduced from the integration of magnetic and self-potential methods, Wadi Khosh El-Daba area, southern Sinai, Egypt

Significant copper mineralization are observed to be associated, in most cases, with some radioactive anomalies related to increased uranium and thorium contents in Southern Sinai, Egypt. These mineralizations are related to intense post-magmatic, structurally controlled hydrothermal activities in many localities. Wadi Khosh El-Daba area is one of these locations which is mainly composed of monzogranites dissected by andesite dyke and pegmatite vein. This work deals with the application of ground magnetic and self-potential methods to establish the magnetic sources governing the mineralization, to interpret the significant trends that affected the study area, and to delineate the mineralized zones. The magnetic data were processed, enhanced and interpreted using advanced techniques, such as the first-order vertical derivative (FVD), the tilt derivative (TD), Euler deconvolution (ED), and source parameter image (SPI). The main structural lineaments/contacts that control the distribution of hydrothermal alterations and mineral distributions are oriented to the NW–SE, NE–SW, and NNW–SSE directions. The self-potential (SP) data show that there are numerous mineralized zones; most of them are distributed mainly along the structural lineaments deduced from the magnetic study. The quantitative interpretation revealed that the mineralized bodies are at shallow depths ranging from 5.6 m to 12.7 m, with half-width from 5 m to 13 m. These bodies are shallow to moderate dipping towards the south and north directions. Based on this study an anomaly map is originated to locate the preferred structural elements that may be controlling the mineralization in the area for further future exploration.

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.

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.

Study on the characteristics of self-electric field of adjacent multiple leakage paths embankment dams and dikes under variable water levels

ABSTRACT The mastery of the distribution characteristics of the self-electric field of leaking embankment dams and dikes will impose positive effects on both detect and monitor leakage paths by self-potential method. We use numerical simulation and model experiment to investigate the self-electric field of embankment dams and dikes with adjacent multiple leakage paths under fluctuating water levels. The distribution characteristics of self-electric field in embankment dams and dikes with leakage paths at different spatial positions are researched by numerical simulation. The variation of self-potential data of horizontal and vertical survey lines on the surface are analysed. We establish a physical model and confirm that the numerical simulation results are reliable. The results show that as the water-level falls and rises, the self-potential of embankment dams and dikes correspondingly reduces and intensifies. During the water level’s descent, a low self-potential region appears above the leakage path’s exit, and the magnitude of the self-potential of this region is proportional to the leakage amount. The number and features of the spatial distribution of leakage paths within the dam are understood based on the peak self-potential of the vertical and horizontal survey lines. The findings will further promote the application of self-potential method.

Neglected flow direction detection in landfill water cycle: Precise characterization of leachate distribution through joint inversion of electrical resistivity and self-potential data

The leakage of leachate is a crucial but often overlooked hydrological process in the landfill water cycle. The concealed leakage of leachate not only leads to soil and groundwater pollution in surrounding areas but also affects the distribution of water and the metabolism of organic matter within the landfill. To accurately quantify this concealed hydrological process, we propose a method for detecting leachate leakage based on joint inversion of multi-source geophysical exploration data. By integrating multiple geophysical exploration data (resistivity and self-potential information), we reconcile the spatial differences in different exploration data to improve the accuracy of leachate and its pollution plume imaging. Additionally, we introduce an efficient alternating iteration technique within the joint inversion framework to ensure convergence of separately inverted models toward similar spatial structures. Simulation results indicate that: (1) for the early detection of small-scale high-concentration leachate pollution, the proposed confidence-induced joint inversion framework (CI-JIF) improves precision by 15.6 % compared to separate inversions. (2) for the detection of leachate long-term diffusion, CI-JIF accurately delineates the distribution of widespread high-concentration leachate, improving precision by 17.4 % compared to separate inversions. Further on-site experiments demonstrate that CI-JIF can more accurately reconstruct the distribution of leachate.

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.

Self-potential variations associated with the slip of Huangnibazi Landslide

The electrical self-potential (SP) responds to the relative fluid flow in porous materials caused by the electrokinetic mechanism, also known as the streaming potential. This characteristic can be used to study landslides induced by rainfall, particularly when subsurface flows cannot be directly observed from the ground surface or landslide scars. The study focuses on the Huangnibazi Landslide, which occurred in 2017 and continued to slide slowly until early 2018 at an average rate of 60 mm/d. SP monitoring was implemented on the slope during the post-failure period to study the characteristics of streaming current. In addition to the diurnal variations of the geoelectric field, localized electric field variations were observed on the morning of Jan. 9, 2018. To examine the spatial distribution and the temporal variation of the streaming current, we processed the measured SP data using a weighted upward continuing method, namely the multi-scale wavelet tomography (MWT). Based on the processing results obtained with the MWT method, we observed variations in the estimated SP sources concentrated in a bulge area. To further investigate these variations, we conducted a numerical modeling test by deforming the geometrical structure of the estimated source. The results suggested that extrusion within the sliding process could be responsible for the variations in SP sources.

Combining Electrical Resistivity, Induced Polarization, and Self-Potential for a Better Detection of Ore Bodies

Electrical resistivity (ER), induced polarization (IP), and self-potential (SP) are three geophysical methods that have been broadly used in the realm of mineral exploration. These geophysical methods provide complementary information, each exhibiting a distinct sensitivity to various types of mineral deposits. Considering the relationship among these three methods, we propose an integrated approach that merges their respective information to offer an improved localization technique for ore bodies. First, we invert the electrical conductivity distribution through electrical resistance tomography (ERT). Then, we use the inverted conductivity distribution to invert the IP and SP data in terms of chargeability and source current density distributions. Then, we normalize the inverted chargeability and source current density distributions and we combine them to obtain an ore body index (ORI) χ used to delineate the potential locations of ore deposits. We design this index to be sensitive to the presence of ore bodies, which are reflected by either strong and localized source current density (SP) and/or strong chargeability values (IP). The proposed method is first validated using a synthetic model with two distinct anomalies characterized by different properties. The results show the limitation of individual inversion, as each method exclusively detects one of these anomalies. The combined approach allows a better characterization of the target. Then, the approach is applied to a sandbox experiment in which two metallic bodies are buried in water-saturated sand used as the background. Again, the proposed methodology is successfully applied to the detection of the metallic targets, improving their localization compared with individual methods.

Characterization of seepage in an earthfill dam by the integration of geophysical surveys and geotechnical data

Seepage is a common phenomenon in earthfill dams, and one that typically warrants episodic assessment and monitoring by regulatory agencies. Geophysical surveys provide a convenient, cost-effective, and convenient means for assessing seepage, but only if they are applied in effective combinations and if the data are analyzed properly. In the present study, a self-potential survey of streaming potential and a 2D electrical resistivity tomography survey were notably successful in detecting seepage under the embankment of the nearly 90-year-old Standing Rock Dam No. 1 in South Dakota, USA. Self-potential (SP) measurements show a localized negative anomaly of up to 27 mV on the upstream side of the dam, which we interpret to be the inlet or recharge zone for seepage, and a positive anomaly of up to 20 mV on the downstream side, which we interpret to be the outlet or discharge zone. The spatial correlation between our resistivity models, SP data, and topography was excellent. Water-saturated, conductive deposits in the dam's embankment match a negative SP amplitude in the inlet or recharge area. Similarly, water-saturated electrically conductive sediments are characterized by a positive SP amplitude in the discharge area where surface seepage occurs in a topographic low. Six years of water-level measurements in the existing piezometers interpreted relative to the properties and spatial distribution of coarser-grained alluvium (sand and gravel) underneath the dam's embankment fill, suggest that most seepage occurs under the dam. Our approach to assessing seepage in this project should be widely applicable to earthfill dams worldwide, and our modeled results constitute a valuable case study.

2D Source Inversion of Self-potential Data Based on Particle Swarm Optimization and Gradient Method

The difficulty of accurately inverting the self-potential (SP) source has always been a major factor hindering the wide application of the SP method. Considering that particle swarm optimization has poor accuracy when in the face of high-dimensional SP inversion, while the gradient method depends on the selection of the initial solution, we try to combine these two algorithms to prompt the inversion result to jump out of local optimum.

Detecting gas upwelling hazards in coastal areas through integration of active and passive electrical and seismic methods (Fiumicino, Central Italy)

The accurate location of gas upwelling flows is still an open problem for non-invasive imaging techniques in populated areas. Gas blowouts of deep origin may represent a serious threat to human health in urban areas and should be correctly imaged with high-resolution for assessing the related hazards. In this work, we propose an integration of active (electrical resistivity tomography and high-resolution sub-bottom profiling complemented with the multibeam bathymetry) and passive (self-potential and ambient noise recordings) geophysical methods to image gas upwelling flows in the coastal area of Fiumicino (Central Italy), where the gas presence is well-documented by previous works. We demonstrate that merging seismic sub-bottom profiling and electrical resistivity tomography has enormous diagnostic potential for gas detection, since they combine the high resolution needed to correctly image the subsurface and the interfaces between different media with the high diagnostic capability of electrical methods to detect anomalies associated with the gas emissions. Passive seismic methods complement the analysis enabling an estimation of the shear-wave velocity through array measurements. Finally, the reconstruction of the natural electrical sources, inferred from the inversion of self-potential data, confirms the location of the near-surface gas upwelling flows assessed through the resistivity model. This work demonstrates that the integration of high-resolution active and passive seismic and electrical methods can be an effective choice for the accurate location of risk-prone areas by imaging the near surface gas pathways where borehole drilling is strongly limited if not forbidden.

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.

New Insights into the Gold Mineralization in the Babaikundi–Birgaon Axis, North Singhbhum Mobile Belt, Eastern Indian Shield Using Magnetic, Very Low-Frequency Electromagnetic (VLF-EM), and Self-Potential Data

The North Singhbhum Mobile Belt (NSMB) in the eastern Indian shield is an excellent example of a diverse lithological domain with multiphase shear/fracture zones. It is a well-acknowledged prospective region known for various mineralizations, e.g., Cu, Au, U, and Fe. The present study was conducted in the Babaikundi–Birgaon Axis (a shear and fracture zone within NSMB) within Babaikundi village. The study suggests that anomalous zones are possibly related to gold-associated sulfide mineralization using photomicrography and geophysical methods such as magnetic, self-potential (SP), and very low-frequency (VLF) electromagnetic (EM) methods. Photomicrography on quartz samples and Scanning Electron Microscope (SEM) Backscattered-Electron (BSE) images show that gold particles are present in the quartz reef vein in Babaikundi. Magnetic data are presented in the total magnetic intensity (TMI), upward continuation, and analytical signal maps. VLF-EM data were analyzed using different processing techniques to delineate anomalous auriferous zones. Furthermore, the SP data were inverted using the Particle Swarm Optimization (PSO), Very Fast Simulated Annealing (VFSA), and Genetic Algorithm (GA) approaches for comparative study of the resultant model parameters and their suitability considering a 2D inverted resistivity section derived using VLF-EM. The photomicrography study indicates the existence of gold/ pyrite/pyrrhotite within the Babaikundi–Birgaon axis, which corresponds to a low magnetic anomaly based on a magnetic study; a high current density, a high Fraser value, and a low resistivity based on the VLF-EM study; and a negative SP value was found based on the SP study. The combined study generally supports mapping auriferous zones and demarcates the Babaikundi–Birgaon axis within the Babaikundi–Birgaon area.

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.

3D Multicomponent Self-Potential Inversion: Theory and Application to the Exploration of Seafloor Massive Sulfide Deposits on Mid-Ocean Ridges

The marine self-potential (SP) method is currently playing an increasing role in the exploration and resource evaluation of seafloor massive sulfide (SMS) deposits. SP surveys are conducted using autonomous underwater vehicles (AUV), which yield multicomponent electric field datasets. By comparing with the single-component electrical field data used to date, the inversion of these multicomponent data is expected to provide a more accurate description of the 3D structure of SMS deposits beneath the seafloor (like gradiometry in gravity surveys). We introduce an inversion algorithm specifically adapted to multicomponent SP data. A synthetic model demonstrates that the inversion of multicomponent datasets allows us to better recover the amplitude of the current density and the morphology of the ore bodies compared to using a single component of the electrical field. Next, we apply our approach to a multicomponent SP dataset collected during the DY58 oceanic cruise at the Yuhuang hydrothermal field on the Southwest Indian Ridge. Subsequently, we reconstruct the three-dimensional (3D) geometry of the SMS deposits beneath the seafloor. The AUV-based SP system with the collection of multicomponent SP data inversion appears to be a powerful tool in the exploration and evaluation of seafloor sulfide resource and, in the future, could be used in concert with induced polarization data.

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.

Inversion of self-potential data by a hybrid DE/PSO algorithm

Inversion of self-potential data by a hybrid DE/PSO algorithm

Multi-parametric observations of intermittent hydrothermal water discharge in West Crater of Iwo-Yama volcano, Kirishima Volcanic Complex, Japan

From April to July 2021, West Crater at Iwo-Yama, Kirishima Volcanic Complex, Japan, was repeatedly filled with hydrothermal water and subsequently evacuated. The overall cycle lasted 14–70 h, and the course of a single cycle followed this sequence of phases: (i) steam effusion disappeared 20–40 min before hydrothermal water discharge; (ii) hydrothermal water discharge occurred, generating a hydrothermal water pool; (iii) steam effusion resumed and gradually increased; and (iv) drain-back (evacuation) of the hydrothermal water occurred 1–1.5 h before the onset of the next hydrothermal water discharge. We used multi-parametric observations (optical camera, thermometer, electric self-potential (SP) electrodes, seismometer, acoustic sensor, and tiltmeter) to investigate the cause of the cyclic hydrothermal water discharge. A change in SP data occurred approximately 2 h before the onset of hydrothermal water discharge. However, the change in SP was small when hydrothermal water discharge did not occur. The temporal change in SP is inferred to have been caused by groundwater flow through the region below West Crater, implying that groundwater flow was occurring 2 h before hydrothermal water discharge. The polarity of SP change suggests that groundwater flowed toward the region underlying the vents. Seismic signals in the frequency range of < 20 Hz decreased 15–45 min after the onset of change in SP. This seismic signal pattern is inferred to have been caused by bubble activity in boiling fluid. We interpret that the inflow of cold groundwater inhibited boiling activity in the conduit, which in turn caused the cessation of both steam effusion and seismic activity. SP data suggest that the inflow of cold groundwater gradually decreased before hydrothermal water discharge. Pressurization sufficient to force the water in the upper part of the conduit to ascend could have built up in the lower part of the conduit owing to a decrease in the input of groundwater into the upper part of the conduit and the continuing supply of steam bubbles and hot water. This increase in pressure finally led to hydrothermal water discharge at the surface. We suggest that the inflow of cold groundwater into the geyser conduit was the key control on the occurrence and cyclicity of hydrothermal water discharge in West Crater at Iwo-Yama.Graphical