Self-potential inversion based on Attention U-Net deep learning network

Landfill leaks pose a serious threat to environmental health,risking the contamination of both groundwater and soil resources.Accurate investigation of these sites is essential for implementing effective prevention and control measures.The self-potential(SP)stands out for its sensitivity to contamination plumes,offering a solution for monitoring and detecting the movement and seepage of subsurface pollutants.However,traditional SP inversion techniques heavily rely on precise subsurface resistivity information.In this study,we propose the Attention U-Net deep learning network for rapid SP inversion.By incorporating an attention mechanism,this algorithm effectively learns the relationship between array-style SP data and the location and extent of subsurface contaminated sources.We designed a synthetic landfill model with a heterogeneous resistivity structure to assess the performance of Attention U-Net deep learning network.Additionally,we conducted further validation using a laboratory model to assess its practical applicability.The results demonstrate that the algorithm is not solely dependent on resistivity information,enabling effective locating of the source distribution,even in models with intricate subsurface structures.Our work provides a promising tool for SP data processing,enhancing the applicability of this method in the field of near-subsurface environmental monitoring.

Investigation of fractured rock aquifer in South China using electrical resistivity tomography and self-potential methods

Assessment of fractured rock aquifers in many parts of the world is complicated given their strong heterogeneity. Delineation of the subsurface geological formation in the weathered terrain is essential for groundwater exploration. To achieve this goal, 2D electrical resistivity tomography(ERT) and self-potential(SP) in combination with joint profile method(JPM) and boreholes have been carried out to delineate the subsurface geological units, detect the fracture/fault zones in hard rock, monitor the groundwater flow, and estimate the groundwater reserves contained within the weathered terrain at a complex heterogeneous site of Huangbu, South Guangdong of China. The integration of resistivity images with the borehole lithology along three profiles delineates three subsurface distinct layers namely topsoil cover, weathered and unweathered layers. The incorporation of ERT and SP with JPM reveal five fractures/faults, i.e., F_1, F_2, F_3, F_4 and F_5. 2D ERT models interpret the less resistive anomalies as the fractures/faults zones, and high resistive anomalies as the fresh bedrock. The inversion program based on the smoothness-constraint is used on the resistivity field data to get more realistic three layered model. SP measurements are obtained along the same electrical profiles which provide the negative anomalies clearly indicating the groundwater preferential flow pathways along the fracture/fault zones. Hydraulic parameters namely hydraulic conductivity and transmissivity were determined to estimate the groundwater resources contained within the fractures/faults. The integrated results suggest that the fractures/faults zones are most appropriate places of drilling for groundwater exploration in the investigated area. Geophysical methods coupled with the upfront borehole data provides better understanding about the conceptual model of the subsurface geological formations. The current investigation demonstrates the importance of the integrated geophysical methods as a complementary approach for groundwater assessment in the hard rock weathered areas.

Dynamic imaging of metallic contamination plume based on self-potential data

A dynamic imaging method for monitoring self-potential data was proposed.Based on the Darcy’s law and Archie’sformulas,a dynamic model was built as a state model to simulate the transportation of metallic ions in porous medium,and theNernst equation was used to calculate the redox potential of metallic ions for observation modeling.Then,the state model andobservation model form an extended Kalman filter cycle to perform dynamic imaging.The noise added synthetic data imaging testshows that the extended Kalman filter can effectively fuse the model evolution and observed self-potential data.The further sandboxmonitoring experiment also demonstrates that the self-potential can be used to monitor the activities of metallic ions and exactlyretrieve the dynamic process of metallic contamination.

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

Prticle swarm optimization(PSO)is adopted to invert the self-potential anomalies of simple geometry.Taking the vertical semi-infinite cylinder model as an example,the model parameters are first inverted using standard particle swarm optimization(SPSO),and then the searching behavior of the particle swarm is discussed and the change of the particles’distribution during the iteration process is studied.The existence of different particle behaviors enables the particle swarm to explore the searching space more comprehensively,thus PSO achieves remarkable results in the inversion of SP anomalies.Finally,six improved PSOs aiming at improving the inversion accuracy and the convergence speed by changing the update of particle positions,inertia weights and learning factors are introduced for the inversion of the cylinder model,and the effectiveness of these algorithms is verified by numerical experiments.The inversion results show that these improved PSOs successfully give the model parameters which are very close to the theoretical value,and simultaneously provide guidance when determining which strategy is suitable for the inversion of the regular polarized bodies and similar geophysical problems.

Performance evaluation for intelligent optimization algorithms in self-potential data inversion

The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.

An Assessment of the Groundwater Potential of Bayero University Kano Permanent Site Using Induced Polarization and Self-potential Methods

This paper centers on the investigation of the subsurface condition of Bayero University Kano Permanent Site with the aim of understanding the lithology and also mapping out the groundwater patterns within the area. To achieve this, time domain IP （induced polarization） and SP （self-potential） methods were adopted using VES （vertical electrical sounding） technique with 49 stations sounded. The result of the interpreted and analyzed measured data shows that the area is underlain by two to five subsurface layers. These layers are top soil, laterite, weathered basement complex rocks, fractured basement complex rocks and fresh basement complex rocks. The aquiferous zone of the study area occurs in the weathered and fractured basements and its thickness ranges from 1.44 m to 70.157 m while the overburden thickness lies between 1.6 m and 72.104 m. SP values were plotted against depths of investigation in order to identify areas with greater depth of flow in the study area. From the analysis of the overburden thickness, aquifer thickness and SP values, the most favorable regions for groundwater exploitation were found around VES 6, 11, 13, 19, 26, 38, 44 and 48. The investigation also provides information about the subsurface condition with regards to engineering construction and safe place for refuse dumping in order to avoid groundwater contamination.

Reconnaissance Geophysical Study on the Southeastern Part of Al-Qashah Aera, KSA

The investigated study area locates about 72 km from Jeddah City, Makkah District, Kingdom of Saudi Arabia. The study mainly aimed to define the most significant zones of possible mineralization and outline their subsurface parameters (location and strike) in the southeast of Jabal Al-Qashah. Several geophysical methods have been conducted to carry out the goal, including ground magnetic, self-potential (SP), and induced polarization (IP) methods. Integrating these methods aims to help delineate the possible mineralization in the study area. The magnetic survey was conducted along 17 profiles where these profiles were chosen to be perpendicular to the strike of the quartz shear zone. Self-potential was applied along with five profiles covering the study area. At the same time, induced polarization was used along with one profile located at the western side of the study area corresponding to some magnetic and SP profiles. The most interesting zones of mineralization were successfully determined by comparing the results of residual magnetic profile (3), SP profile (1), and IP profile, where geological structures control some mineralization.

ULF electric and magnetic anomalies accompanying the cracking of rock sample

The anomalies of electric-magnetic field and self-potential before earthquakes are important precursory phenom-ena. A simulating experiment study on the variations in ultra-low frequency (ULF) magnetic field and self-poten-tial during rock cracking was carried out in a magnetic field-free space. The results revealing in detail the whole process of the occurrences of electric and magnetic anomalies are significant for understanding the microscopic mechanism of ULF electric and magnetic signals. The experiment indicated that at the initial stage the slow changes in strain, self-potential and magnetic field with small amounts appeared firstly near the source of initial cracking, and then extended as the crack developed on. In the time domain, the self-potential anomaly emerged first and ULF magnetic field changes arose then. The shape of the ULF electric and magnetic anomaly varied ob-viously in early-, mid- and late-term of the test. The authors attributed the pulse-like changes of self-potential to the generation and movement of the accumulated electric charges during the cracking caused by charge separation on the crack tips within the sample. While the magnetic pulses of shorter-period at the last stage of the test, may be induced by instantaneous electric current of the accumulated charge during the cracking acceleration. The technical method and the observational results of this experiment are given in detail and the microscopic mechanism of elec-tric and magnetic precursors before earthquake are discussed in the present paper as well.

Confirming Ground Geophysical Survey for Mineralization in Al Bayda Area,Yemen

The Jabal Mabal-prospect of Al Bayda area is covered by meta-volcano sedimentary rocks. The importance of the study area comes from previous studies, which proved that the area has mineralization zones at the periphery of Jabal Al-Mabal. These mineralized zones lie along northwest-southeast shear zones, which occur inside the meta-volcanic rocks. The previous studies concluded that the mineralization was mostly associated with sulphides, especially at the reduction zones. These sulphides give a good response to electrical or electromagnetic techniques. The present study uses electrically induced polarization and Genie electromagnetic surveys to explore the extension of the mineralization zones at the subsurface.The self-potential (SP) technique shows numerous of mineralized zones. Most of these zones are distributed in the southern area along the contact between the quartz and gabbro. The induced polarization (IP) method has been applied on the selected profiles to delineate the subsurface contact between calcite, gabbro and quartz in Al-Jarra Valley and to calculate the shape and depth of the mineralization zones in the subsurface along these profiles. The Genie electromagnetic survey, which has been applied on selected profiles, delineated some weak mineralization occurrences corresponding to the shear zones. The integration of the results obtained using these three techniques, in addition to the different ground geophysical methods previously used, makes it possible to determine the most appropriate zones for development of exploration at the area of investigation.

Detection of the Possible Buried Archeological Targets Using the Geophysical Methods of Ground Penetrating Radar (GPR) and Self Potential (SP), Kom Ombo Temple, Aswan Governorate, Egypt

Kom Ombo temple is one of temples which were belted over high plateau close to the River Nile, near to Aswan in Egypt in the Greek-Roman period. The expected archaeological remains in the selected area are the hidden tunnels of the mummified crocodiles. The aim of the present work is to detect any of these tunnels by the application of the (GPR) and (SP) methods. The interpretation of the 10 GPR profiles revealed some locations of possible hidden tunnels. These locations show different contrasts and high amplitudes of the reflected signals, compared to the enclosing soil;also the scattering of the signals is higher than the bed layer in these locations, which may reveal the possible buried mummified crocodile tunnels in the study area. The depths of the possible targets range from 2.0 m to 2.5 m. The SP electric map shows that the study area possesses a range of about 135 mV of the potential differences between the measured stations. The positive response of the SP data is mainly concentrated at the central part of the study area. The relatively weak, negative SP anomalies may be related to moisture in the soil. The positive SP anomalies on the SP electric map display possible significant correlation between them and the inferred tunnel locations from the GPR data. The calculated depths from the SP profiles show significant agreement with that estimated from GPR data depths, which indicate that the SP electric method can be used as a successful tool in detecting buried archaeological remains in support of GPR.