@article{MTMT:34760235, title = {Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters}, url = {https://m2.mtmt.hu/api/publication/34760235}, author = {Mohammed, Musaab Adam Abbakar and Flores Carpio, Yetzabbel Gerarda and Szabó, Norbert Péter and Szűcs, Péter}, doi = {10.1038/s41598-024-57435-x}, journal-iso = {SCI REP}, journal = {SCIENTIFIC REPORTS}, volume = {14}, unique-id = {34760235}, issn = {2045-2322}, abstract = {This research presents an unsupervised learning approach for interpreting well-log data to characterize the hydrostratigraphical units within the Quaternary aquifer system in Debrecen area, Eastern Hungary. The study applied factor analysis (FA) to extract factor logs from spontaneous potential (SP), natural gamma ray (NGR), and resistivity (RS) logs and correlate it to the petrophysical and hydrogeological parameters of shale volume and hydraulic conductivity. This research indicated a significant exponential relationship between the shale volume and the scaled first factor derived through factor analysis. As a result, a universal FA-based equation for shale volume estimation is derived that shows a close agreement with the deterministic shale volume estimation. Furthermore, the first scaled factor is correlated to the decimal logarithm of hydraulic conductivity estimated with the Csókás method. Csókás method is modified from the Kozeny-Carman equation that continuously estimates the hydraulic conductivity. FA and Csókás method-based estimations showed high similarity with a correlation coefficient of 0.84. The use of factor analysis provided a new strategy for geophysical well-logs interpretation that bridges the gap between traditional and data-driven machine learning techniques. This approach is beneficial in characterizing heterogeneous aquifer systems for successful groundwater resource development.}, year = {2024}, eissn = {2045-2322}, orcid-numbers = {Flores Carpio, Yetzabbel Gerarda/0000-0003-0365-8951} } @article{MTMT:34753099, title = {Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary}, url = {https://m2.mtmt.hu/api/publication/34753099}, author = {Mohammed, Musaab Adam Abbakar and Szabó, Norbert Péter and Szűcs, Péter}, doi = {10.1007/s40808-024-01986-5}, journal-iso = {MESE}, journal = {MODELING EARTH SYSTEMS AND ENVIRONMENT}, unique-id = {34753099}, issn = {2363-6203}, abstract = {In this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of the Quaternary aquifer system in the Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) is used to map lithological variations within the aquifer system. Additionally, the Csókás method is used to discern both vertical and horizontal fluctuations in hydraulic conductivity. MFV-CA is introduced to cope with the limitation of the conventional Euclidean distance-based k-means clustering known for its low resistance to outlying values, resulting in deformed cluster formation. However, the computational time and demands of MFV-CA are evident, making them costly and time-consuming. As a result, Deep Learning (DL) methods are suggested to provide fast characterization of the groundwater aquifers. These methods include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), which are implemented for classification and regression. The classification categorized the inputs into three distinct lithologies trained initially by the results of MFV-CA. At the same time, the regression model offered a continuous estimations of hydraulic conductivity trained by the results of the Csókás model. The results demonstrated significant compatibility between the outcomes derived from the clustering and Csókás approaches and DL algorithms. Accordingly, the lithofacies and hydraulic conductivity variations across the main hydrostratigraphical units are mapped. This integration enhanced the understanding of the groundwater system, offering promising inputs for groundwater and development and management.}, year = {2024}, eissn = {2363-6211} } @article{MTMT:34729421, title = {Geospatial modeling for groundwater potential zoning using a multi-parameter analytical hierarchy process supported by geophysical data}, url = {https://m2.mtmt.hu/api/publication/34729421}, author = {Mohammed, Musaab Adam Abbakar and Mohammed, Sarkhel and Szabó, Norbert Péter and Szűcs, Péter}, doi = {10.1007/s42452-024-05769-6}, journal-iso = {DISCOV APPL SCI}, journal = {DISCOVER APPLIED SCIENCES}, volume = {6}, unique-id = {34729421}, abstract = {Groundwater plays a crucial role in Hungary sustaining ecosystems and meeting the growing demand for freshwater to fulfill domestic and agricultural needs. This study employs the analytical hierarchy process (AHP) methodology to delineate groundwater potential zones in the Debrecen area, Hungary. To ensure the robustness and reliability of the potential zoning, geophysical data are utilized for validation purposes. In the AHP modeling seven groundwater conditioning factors are integrated, including geology, topography, slope, land use/land cover, precipitation, drainage density, and lineament density. The integration of the normalized weights for each factor identified three groundwater potential zones (GWPZs) assigned as moderate, high, and very high potential. The result of the AHP model is further validated with geophysical data of gravity and wireline logging. Gravity data is subjected to spectral analysis and forward modeling to map the lineaments and detect the thickness of the sedimentary sequences. The forward modeling indicated that the thickness of these sequences varies between 1.25 and 2.7 km, with a deep local basin delimited by normal faults situated in the eastern part of the study area. Additionally, the analysis of the well-logging data using the Csókás method provided a continuous estimation of petrophysical and hydrogeological parameters along the main hydrostratigraphical units. Accordingly, a high and uniform distribution of hydraulic conductivity is observed in the eastern part of the study area due to the presence of coarse-grained incised valley deposits. The results of geophysical modeling showed a close agreement with that of AHP models. This interdisciplinary approach advanced the mapping of potential groundwater zones and provided valuable insights into the hydrogeological characteristics of the groundwater aquifers in the Debrecen area.}, year = {2024}, eissn = {3004-9261} } @article{MTMT:34717098, title = {Geophysical characterization of groundwater aquifers in the Western Debrecen area, Hungary: insights from gravity, magnetotelluric, and electrical resistivity tomography}, url = {https://m2.mtmt.hu/api/publication/34717098}, author = {Mohammed, Musaab Adam Abbakar and Szabó, Norbert Péter and Alao, Joseph O. and Szűcs, Péter}, doi = {10.1007/s40899-024-01062-x}, journal-iso = {SUST WATER RES MANAG}, journal = {SUSTAINABLE WATER RESOURCES MANAGEMENT}, volume = {10}, unique-id = {34717098}, issn = {2363-5037}, abstract = {The recent study followed a multi-methodological approach integrating gravity, magnetotelluric (MT), and electrical resistivity tomography (ERT) to investigate the geometry and hydrological characteristics of the main hydrostratigraphical units in the Western Debrecen area, Eastern Hungary. The integration of these methods aims to delineate potential zones for groundwater development and guide effective extraction strategies. In the gravity investigation, the Bouguer anomaly map undergoes spectral analysis for the separation of shallow and deep features, offering a preliminary indication of basement rock depth. Subsequently, gravity data inversion is employed to map variations in basement rock topography, revealing a basin structure, with sediment thicknesses extending up to 2 km. On the other hand, the MT data are modeled using the 1D Occam inversion algorithm to validate the results of the gravity data analysis. This inversion, constrained with lithological logs is further utilized to delineate the main hydrostratigraphical units in the study area. Accordingly, four units are identified, including the Nagyalföld Aquifer, Algyő and Endrődi Aquitards, the Badenian Aquifer, and the Pre-Neogene Aquitard. Consequently, Dar Zarrouk parameters based transmissivity and the hydraulic conductivity of the aquifer units are measured. The Nagyalföld aquifer showed a hydraulic conductivity that ranged between 7.9 and 11.9 m/day, while the Badenian aquifer showed an average hydraulic conductivity of 13.1 m/day. The ERT data are employed to map the spatial distribution of the depth to the water table. The shallow water table is observed in regions characterized by an elevated thickness of sedimentary rocks, attributed to their high specific capacity. Integrating these hydrogeophysical methods provided a comprehensive understanding of the subsurface hydrology and enabled better-informed decision-making for groundwater development.}, year = {2024}, eissn = {2363-5045} } @article{MTMT:34570001, title = {Joint interpretation and modeling of potential field data for mapping groundwater potential zones around Debrecen area, Eastern Hungary}, url = {https://m2.mtmt.hu/api/publication/34570001}, author = {Mohammed, Musaab Adam Abbakar and Szabó, Norbert Péter and Szűcs, Péter}, doi = {10.1007/s40328-023-00433-8}, journal-iso = {ACTA GEOD GEOPHYS}, journal = {ACTA GEODAETICA ET GEOPHYSICA}, volume = {59}, unique-id = {34570001}, issn = {2213-5812}, abstract = {The Debrecen area, as part of the Great Hungarian Plain (GHP), is associated with a multi-aquifer system that is overly exploited to fulfill the development plans. This research aims to jointly interpret and model gravity and magnetic data to map the subsurface geology and structures that govern groundwater occurrence. Various potential field techniques, including spectral analysis, anomaly derivatives, analytical signal, and Euler deconvolution were employed to map the distribution and depth of the buried geological structures. The combination of the potential field techniques enabled the construction of a detailed lineament map, providing valuable insights into the distribution of the subsurface structural features. It was indicated that the main structural trend is NW–SE and NE–SW, that coincides with the main structural trends in Hungary. Subsequently, a lineament density map is derived, indicating that the eastern, central, and northwestern parts of the area form the most promising zones for groundwater prospection. The joint inversion of gravity and magnetic data has further enhanced the understanding of subsurface geology. The depth to the basement rock varied between 1.18 and 2.2 km. The highest depth to the basement meets with thick sedimentary sequences bounded by normal faults forming graben and horst structures. Moreover, the distribution of these sediments is investigated using lithological logs indicating the thickness of the main hydrostratigraphic units in the Debrecen area. These units include Nagyalföld Aquifer, Algyő Aquitard, Endrőd Aquitard, and Miocene Badenian Aquifer units, which mainly consist of sand, silt, marl, and gravel. The recent study demonstrated the effectiveness of the joint interpretation in enhancing the knowledge of lithology and geological structures. However, a detailed geophysical survey is recommended to characterize the hydrostratigraphic units in the Debrecen area.}, year = {2024}, eissn = {2213-5820} } @article{MTMT:34544315, title = {A case study of petrophysical prediction using machine learning integrated with interval inversion in a tight sand reservoir in Egypt}, url = {https://m2.mtmt.hu/api/publication/34544315}, author = {Abdelrahman, Moataz and Szabó, Norbert Péter}, doi = {10.1088/1755-1315/1295/1/012008}, journal-iso = {IOP CONF SER EARTH AND ENVIRON SCI}, journal = {IOP CONFERENCE SERIES: EARTH AND ENVIRONMENTAL SCIENCE}, volume = {1295}, unique-id = {34544315}, issn = {1755-1307}, abstract = {This study presents a new algorithm for reservoir characterization using borehole logging data, which integrates unsupervised machine learning techniques and interval inversion to automatically determine layers’ boundaries and petrophysical parameters. The research aims to reduce the time and manual input required for borehole inversion to estimate petrophysical parameters. The algorithm was used to predict different layer boundaries of sand-shale intercalations for both synthetic and field wireline log data. Field well logging measurements were obtained from an oil and gas field in Egypt, specifically the Jurassic reservoir. The reservoir is composed of a dense sandstone layer with significant heterogeneity due to diagenesis, which converts kaolinite into illite. The algorithm was used to predict petrophysical parameters, resulting in a decrease in porosity and permeability. The field data from the well reveals that the reservoir is made up of varying-quality sandstone, impacting storage capacity and hydrocarbon saturation. The algorithm demonstrates consistent convergence of the data at 7.5%. Overall, the integration of the new cluster technique and interval inversion can improve the time-intensive and laborious process of borehole data inversion to estimate petrophysical parameters.}, year = {2024}, eissn = {1755-1315} } @article{MTMT:34527979, title = {Combined inversion and statistical workflow for advanced temporal analysis of the Nile River’s long term water level records}, url = {https://m2.mtmt.hu/api/publication/34527979}, author = {Szűcs, Péter and Dobróka, Mihály and Turai, Endre and Szarka, László Csaba and Ilyés, Csaba and Hemida, Mohamed Hamdy Eid and Szabó, Norbert Péter}, doi = {10.1016/j.jhydrol.2024.130693}, journal-iso = {J HYDROL}, journal = {JOURNAL OF HYDROLOGY}, volume = {630}, unique-id = {34527979}, issn = {0022-1694}, year = {2024}, eissn = {1879-2707}, orcid-numbers = {Dobróka, Mihály/0000-0003-3956-2070; Ilyés, Csaba/0000-0002-5328-8023} } @article{MTMT:34500289, title = {Multi-well clustering and inverse modeling-based approaches for exploring geometry, petrophysical, and hydrogeological parameters of the Quaternary aquifer system around Debrecen area, Hungary.}, url = {https://m2.mtmt.hu/api/publication/34500289}, author = {Mohammed, Musaab Adam Abbakar and Szabó, Norbert Péter and Flores Carpio, Yetzabbel Gerarda and Szűcs, Péter}, doi = {10.1016/j.gsd.2024.101086}, journal-iso = {Groundwater for Sustainable Development}, journal = {GROUNDWATER FOR SUSTAINABLE DEVELOPMENT}, volume = {24}, unique-id = {34500289}, issn = {2352-801X}, year = {2024}, orcid-numbers = {Flores Carpio, Yetzabbel Gerarda/0000-0003-0365-8951} } @article{MTMT:34450446, title = {Integrated workflow incorporating the Hurst exponent and interval inversion for evaluating groundwater formations}, url = {https://m2.mtmt.hu/api/publication/34450446}, author = {Abdelrahman, Moataz and Szabó, Norbert Péter}, doi = {10.1007/s10040-023-02752-0}, journal-iso = {HYDROGEOL J}, journal = {HYDROGEOLOGY JOURNAL}, volume = {32}, unique-id = {34450446}, issn = {1431-2174}, abstract = {A novel well-log-analysis approach is presented for an improved prediction of petrophysical properties in groundwater formations. Geophysical well logs are simultaneously processed for quantifying the lithology, storage capacity, and water flow parameters. A fully automated data processing workflow is proposed, the feasibility of which is assured by an appropriate starting model set by the joint application of factor analysis and the Hurst exponent, and a solution of a highly overdetermined inverse problem. The Hurst exponent is used for zone boundary detection, which assists the series expansion-based interval inversion method applied for estimation of the petrophysical parameters of clastic formations. The hydraulic conductivity as a well log is directly derived from the inversion results. The workflow is tested using both synthetic data contaminated with 5% Gaussian distributed noise and real data collected from a thermal water well in Baktalórántháza, eastern Hungary. At the test site, the Hurst exponent extracted from the wireline logs allows one to divide the processed interval into subzones around the Pleistocene-Miocene boundary. The observed wireline logs are inverted to estimate the volumetric parameters (porosity, shale content, water saturation, etc.) of the same zones. The predicted parameters, including hydraulic conductivity, reveal that Pleistocene sediments contain good aquifers with formation quality varying with depth. The shale volume and hydraulic conductivity logs show a proper match with the core data, which confirms the results of the comprehensive analysis. The suggested workflow is recommended for the evaluation of groundwater formations located in different depth domains, from unsaturated sediments to geothermal reservoirs.}, year = {2024}, eissn = {1435-0157}, pages = {487-507} } @article{MTMT:34500316, title = {Investigation of petrophysical and hydrogeological parameters of the transboundary Nubian Aquifer system using geophysical methods}, url = {https://m2.mtmt.hu/api/publication/34500316}, author = {Mohammed, Musaab Adam Abbakar and Mohamed, Ahmed and Szabó, Norbert Péter and Alarifi, Saad S. and Abdelrady, Ahmed and Alao, Joseph Omeiza and Szűcs, Péter}, doi = {10.3389/feart.2023.1295213}, journal-iso = {FRONT EARTH SC-SWITZ}, journal = {FRONTIERS IN EARTH SCIENCE}, volume = {11}, unique-id = {34500316}, abstract = {The recent research aims to investigate the petrophysical and hydrogeological parameters of the Nubian aquifer system (NAS) in Northern Khartoum State, Sudan, using integrated geophysical methods, including surface electrical resistivity and geophysical well-logging. The Nubian aquifer is a transboundary regional aquifer that covers vast areas in Sudan, Egypt, Libya and Chad. The well-logs, including self-potential (SP), natural gamma ray (GR), and long normal resistivity (RS), are integrated with Vertical Electrical Sounding (VES) measurements to delineate the hydrostratigraphical units. As a result, two aquifers are detected. An upper aquifer comprises coarse sand with an average thickness of 50 m and a lower aquifer of sandstone with more than 200 m thickness. For a thorough evaluation of the aquifers, in the first stage, the petrophysical and hydrogeological parameters, including formation factor, total and effective porosity, shale volume, hydraulic conductivity, and transmissivity, are measured solely from geophysical well-logs. In the second step, the results of geophysical well logs are combined with VES and pumping test data to detect the spatial variation of the measured parameters over the study area. As a result, the hydraulic conductivity of the Nubian aquifers ranged from 1.9 to 7.8 m/day, while the transmissivity varied between 120 and 733 m 2 /day. These results indicated that the potentiality of the Nubian formation is high; however, in some regions, due to the sediment heterogeneity, the aquifers have intermediate to high potential. According to the obtained results, it can be concluded that the Nubian Aquifer in Khartoum state is ideal for groundwater development. This research discovered that geophysical approaches can be used to characterize moderately heterogeneous groundwater systems by comparing the Nubian aquifer with similar aquifer systems that have similar hydrogeological settings. This study emphasized the application of universal principles in extrapolating hydraulic parameters in hydrogeophysical surveys. This approach aims to reduce the costs and efforts associated with traditional hydrogeological approaches.}, year = {2023}, eissn = {2296-6463} }