Geophysical Well Research Articles

Improving the accuracy of density logging results considering mineral composition for evaluation of high-level radioactive waste disposal sites

ABSTRACT Site selection and characterisation are key factors influencing the safe, stable disposal of spent nuclear fuel. Site selection can be based on geophysical surveys, and geophysical well logging is performed at the detailed survey stage. Typically, gamma – gamma density logging is conducted to continuously obtain in situ density information regarding the well depth. However, gamma – gamma density logging is often influenced by the geological characteristics of the site. The ratio of atomic number to atomic weight is required to convert the electron density obtained through density logging counts into bulk density. Because it is difficult to calculate these ratios for the entire depth, an equation based on water-filled limestone is typically used for conversion. Therefore, as the difference in the ratio of the atomic number and atomic weight increases relative to that of limestone, the difference between the converted bulk density and the actual bulk density increases. In this study, equations were derived for various mineral compositions and applied to the density logging results. Matrix density was analyzed using a pycnometer, and the ratio between the atomic number and weight was calculated according to X-ray fluorescence analysis results. This approach improved the accuracy of the density logging data and reduced density errors. The proposed method is expected to be particularly useful for estimating in situ density at high-level radioactive waste disposal sites without complex geological formations.

Pore structure characterization and reservoir quality prediction in deep and ultra-deep tight sandstones by integrating image and NMR logs

Pore structure and fracture determine reservoir quality in deep and ultra-deep tight sandstones, however, the limited availability of core data makes it challenging to describe the complexity of pore-throat structure and characterize the wide range of fractures. To fill this gap, a comprehensive analysis was conducted to evaluate pore structure and fractures from multiple perspectives. Integration of core, thin sections, scanning electron microscopy (SEM), high pressure mercury injection (HPMI) and nuclear magnetic resonance (NMR) tests are used to evaluate pore structure and characterize fracture of deep and ultra-deep tight sandstones in the Cretaceous Bashijiqike Formation in the Kuqa Depression. Pore structure and reservoir quality types can be divided into dominantly three types according to characteristics of NMR transverse relaxation time (T2) distribution and HPMI curves. Correlation analysis among HPMI and NMR parameters with petrophysical parameters indicate that maximum pore throat size (rmax), logarithmic mean of T2 (T2gm), irreducible water saturation (Swi), and reservoir quality index (RQI) are the most sensitive parameters for pore structure characterization. The Type Ⅰ pore structure is composed of intergranular and intragranular pores, and NMR T2 spectrum shows the highest magnitude, with the calculated mobile fluid saturation content also being the highest. The Type II and III pore structures are composed of intergranular pores, intragranular dissolved pores and intercrystalline micropores in clay minerals. T2gm of Type II and III are smaller, with the calculated mobile fluid saturation content being the lower.The fracture features and parameters including fracture density, porosity, aperture, and length are analyzed using image logs and core. The pore structure characteristics are quantificationally and qualitatively analyzed by NMR logs. Integration of pore structure and fractures by image logs and NMR logs are used for prediction of high quality reservoir and hydrocarbon productivity. High hydrocarbon productivity is obtained in well intervals with abundant natural fractures, and favorable pore structure will also contribute to high matrix porosity. Therefore, NMR logs and image logs are crucial for evaluating reservoir quality and predicting productivity when calibrated with core and analysis data. The comprehensive analysis integrating core data with geophysical well logs provide important insights for reservoir quality prediction of deep and ultra-deep tight sandstones.

The estimation of the parameters of the layers according to the data of the GWS in the “Bulla-Deniz” offshore field

The article is devoted to the analysis and interpretation of the data of the geophysical well surveys (GWS) using modern water saturation models to assess the strata properties of the studied field. At the first stage, reservoir layers and their clay content, porosity value, saturation character and oil-gas saturation coefficient are identified over the section by studying petrophysical properties of well section. The reservoirs of the studied section are represented by sandy-silty-clay deposits. Some difference was observed during comparing oil-gas saturation coefficients evaluated by core and the interpretation results (Archi-Dakhnov method) of well log data. In this regard, various existing methods were used to estimate oil-gas saturation.

Characterization of onshore hydrocarbon reservoirs in the Amazonas Basin using well logging data

Reservoir characterization is extremely important for understanding and determining the behavior of hydrocarbon reservoirs. The geophysical well logging, widely applied in the oil industry, helps to obtain essential physical properties (acoustic, electrical, mechanical, radioactive and thermal) by deploying measurement devices in the drilled well. This project aims to carry out the geological characterization of hydrocarbon reservoirs in the Amazonas Basin through the analysis of well geophysical logs. Despite the oil-producing potential of the basin, there are few published papers that use geophysical well logging for reservoir characterization. For this study, composite log data publicly provided by ANP were used. Six exploratory wells drilled in AM-T-84 and AM-T-85 exploratory blocks in the Amazonas Basin were selected. By analyzing the geophysical logs of gamma ray, resistivity, density and neutron from these wells, it was possible to identify the hydrocarbon reservoir interval within the Monte Alegre formation and obtain estimates of thickness, shale volume and porosity. The identified reservoir is relatively thin, with an average thickness of 16 m. The obtained shale volume values were relatively high, due to the influence of shale layers present in the Monte Alegre formation. The effect of clay content affected the interpretation process of the well logs; however, it did not significantly impact the reservoir porosity estimation, which ranged between 10.4 and 23.4 %.

Application of geophysical well logs in solving geologic issues: Past, present and future prospect

Geophysical well logs are widely used in geological fields, however, there are considerable incompatibilities existing in solving geological issues using well log data. This review critically fills the gaps between geology and geophysical well logs, as assessed from peer reviewed papers and from the authors’ personal experiences, in the particular goal of solving geological issues using geophysical well logs. The origin and history of geophysical logging are summarized. Next follows a review of the state of knowledge for geophysical well logs in terms of type of specifications, vertical resolution, depth of investigations and demonstrated applications. Then the current status and advances in applications of geophysical well logs in fields of structural geology, sedimentary geology and petroleum geology are discussed. Well logs are used in structural and sedimentary geology in terms of structure detection, in situ stress evaluation, sedimentary characterization, sequence stratigraphy division and fracture prediction. Well logs can also be applied in petroleum geology fields of optimizing sweet spots for hydraulic fracturing in unconventional oil and gas resource. Geophysical well logs are extending their application in other fields of geosciences, and geological issues will be efficiently solved via well logs with the improvements of advanced well log suits. Further work is required in order to improve accuracy and diminish uncertainties by introducing artificial intelligence. This review provides a systematic and clear descriptions of the applications of geophysical well log data along with examples of how the data is displayed and processed for solving geologic problems.

Universal apparatus module of radioactivity logging for the investigation of oil-and-gas reservoirs while drilling

Logging-while-drilling (LWD) is the most advanced technology in geophysical well logging. It is widely used for determining the petrophysical and other parameters of oil-and-gas reservoirs in vertical, deviated, and horizontal boreholes.
 The LWD is particularly important for horizontal boreholes, obtained by directional drilling from vertical boreholes into predetermined hydrocarbon reservoirs. Horizontal boreholes allow multiplying the yield of hydrocarbons, increasing overall production, and using effectively both new vertical boreholes and exploited ones, as well as old boreholes. The opportunity of horizontal drilling to local (isolated) deposits, which are at a certain distance from vertical boreholes, is of also essential importance. All these factors are favourable for increased hydrocarbon production, which is of great significance for Ukraine.
 This paper concentrates on the apparatus developments aimed at creating a new module of radioactivity logging for LWD; the module is universal in the sense that it can be used in drill collars, which are employed while drilling all types of boreholes. The tool implements neutron-neutron logging, neutron-gamma logging, gamma-gamma logging, and gamma-ray logging. It allows a direct and combined determination of a broad set of petrophysical reservoir parameters.
 The advantages and disadvantages of the known nuclear logging modules for the LWD have been analyzed, and the features and merits of the proposed one are shown. During the laboratory and borehole operations with a pilot sample of the module, trends for its improvement were outlined.
 As an example of using the new module for LWD, the results of determining the petrophysical parameters of oil reservoirs of varying lithology in three horizontal boreholes are given. The process of LWD measurements demonstrated high technologicness and efficiency of the module. Comparison of the obtained parameters of the reservoirs with the data of independent measurements carried out in the open hole of the same boreholes using the PEX tool (Schlumberger) showed a qualitative consistency and a quantitative convergence of the results.

Adsorbed residual oil saturation and phase permeability relationship for oil in Western Siberia productive formations

Relevance. Relative phase permeabilities determine oil by water displacement mechanism, efficiency of productive formations flooding, dynamics of producing wells flooding. Relative phase permeabilities curves allow us to estimate the inflow nature according to geophysical well studies. Currently, relative phase permeabilities curves are constructed according to core samples laboratory studies. They are used to select a mathematical model describing the nature of the curves for a given productive reservoir. The most optimal option is to justify the individual relative phase permeabilities curve parameters. This option allows transition from the core sample level to the entire productive reservoir characteristics using geophysical well studies data. Aim. To substantiate a choice of a model describing the change in the relative phase permeability curves using field geophysics data based on the adsorbed residual oil saturation and phase permeability to oil relationship. Objects. Productive layers of individual deposits of the West Siberian oil and gas province, confined to the Lower Cretaceous deposits. Methods. Statistical processing of capillarimetric research data, analysis and substantiation of mathematical models describing relative phase permeability. Results. The paper shows that the permeability to oil at residual water saturation (the starting point of the relative phase permeabilities curve to oil) is determined by the adsorbed residual reservoir oil saturation. The authors have obtained the formula, linking the adsorbed residual oil saturation coefficient with the phase permeability to oil with residual water saturation. The adsorbed residual oil saturation is also closely related to the residual reservoir water saturation. Such relation is carried out through the reservoir clay content. The authors proposed the technique that allows residual oil saturation by type structuring and mobility degree. This technique allows as well as finding out the residual reserves of mobile oil distribution to justify the recovery techniques.

A 3D thermal conductivity prediction method for deep strata based on temperature field estimation

Accurate predictions of earth’s interior thermal conductivity are essential for interpreting the mechanisms involved in geothermal systems and delineating geothermal resource targets. Existing thermal conductivity prediction methods, which typically involve measurements of rock samples and predictions based on geophysical well logging, cannot accurately predict regional thermal conductivity distributions. We develop a 3D thermal conductivity prediction based on temperature field estimation. First, the finite-element method is used for temperature forward modeling. Subsequently, the inexact Gauss-Newton method is implemented in the prediction algorithm. Synthetic studies indicate that the method can recover the true model well. The subsurface temperature distribution of the Xiong’an New Area is predicted using the coefficient correction method of the optimal temperature. Next, we obtain the 3D distribution of thermal conductivity of deep formation in the Xiong’an New Area with the predicted temperature field. The distribution of terrestrial heat flow also is estimated. In addition, the law of thermal accumulation of strata at different depths is analyzed, and the internal relation among resistivity, temperature, and thermal conductivity is studied. Thus, the 3D thermal conductivity prediction method provides the theoretical basis for interpreting mechanisms for the origin of geothermal systems and heat accumulation patterns. It could have significant utility for the analysis of geothermal fields and the sustainable development and use of geothermal resources.

Biostratigraphy v. geophysics; correlation of Middle Turonian chalks in the Anglo-Paris Basin

High-resolution correlations between boreholes are commonly based on a combination of geophysical well-log data and biostratigraphy, and when these conflict resolution can be contentious and difficult. Such a situation exists in the Middle Turonian chalks of the Anglo-Paris Basin, where electrical resistivity logs, registering thin but seemingly laterally continuous beds of clay-rich chalk (marls) in mostly uncored boreholes, provide apparently straightforward correlations across broad regions. In contrast, detailed biostratigraphical analysis using microcrinoids provides very different results, showing the presence of a major hiatus associated with a hardground and differing significantly from the geophysical correlations. Detailed re-examination of this contentious problem, utilizing exposures adjacent to boreholes, demonstrates the supremacy of detailed biostratigraphical analysis, independently supported by regional thickness patterns, cyclostratigraphy and geochemistry. Although closely spaced geophysical well logs can afford convincing correlations, their use in correlation over broader geographical regions leads to erroneous and misleading conclusions.

Innovative hydrogeophysical approach for detecting the spatial distribution of hydraulic conductivity in Bahri city, Sudan: A comparative study of Csókás and Heigold methods

Hydraulic conductivity is one of the crucial parameters used to identify the potentiality and productivity of groundwater aquifers. This research employs an integrated approach using geophysical well logging, exploratory factor analysis and surface electrical resistivity methods to detect the vertical and horizontal variation of hydraulic conductivity in Bahri city, Sudan. Based on the geophysical well logs of Spontaneous potential (SP), natural gamma ray (GR), and electrical resistivity (RS), Csókás method is used to determine the continuous variation of hydraulic conductivity along the aquifer. Csókás method is an experimentally modified version of the Kozeny–Carman equation and is based on the formation factor of the groundwater aquifer and the effective grain size. This approach is performed in three groundwater boreholes, and the obtained hydraulic conductivities showed a close agreement with that of the pumping test analysis. Furthermore, the hydraulic conductivity is measured using multivariate statistical factor analysis. This statistical approach relies on the correlation between the extracted factors and petrophysical and hydrogeological parameters. In this research, a strong negative linear correlation between the first factor and hydraulic conductivity is indicated. Consequently, a site-specific equation is suggested for continuous estimation of hydraulic conductivity along the aquifer. In the last stage, the results obtained from the Csókás method are interpolated with vertical electrical sounding (VES) measurements using to detect the horizontal variation of hydraulic conductivity throughout the studied area. This was achieved by combining the hydraulic conductivities of geophysical well logging and vertical electrical soundings to obtain a consistent estimation. As a result, the variation of hydraulic conductivity is obtained, and the average was 1.9 m/day which shows a close agreement with the average of the previous investigations (1.5 m/day). This approach is highly recommended since it can enhance data coverage, cutting down the expense of hydrogeological investigations and lowering the uncertainty of the hydrogeological models.

Pore structure characterization and deliverability prediction of fractured tight glutenite reservoir based on geophysical well logging

Pore structure characterization and deliverability prediction of fractured tight glutenite reservoir based on geophysical well logging

Effect of External Magnetic Fields on the Amplitude‒Time Characteristics of Penning Ion Sources

The operation modes of pulsed Penning ion sources under the action of external magnetic fields corresponding to the operating conditions of geophysical well survey equipment are discussed. The obtained dependences of the amplitude‒time characteristics of the ion sources on the magnetic field value and configuration are reported. Based on the data obtained, options of neutron tube magnetic systems are proposed, which ensure an increase in the operation stability of neutron generators.

Permeability prediction using logging data in a heterogeneous carbonate reservoir: A new self-adaptive predictor

Accurately predicting permeability is critical for oil deposit exploitation and high-quality reservoir identification. However, the substantial heterogeneity in carbonate reservoirs has significantly challenged the accurate permeability prediction. In this study, 325 core samples with logging data from the Sinian carbonate reservoirs of the second member of the Dengying Formation were collected to establish a reliable predictor for permeability prediction in the Gaoshiti-Moxi block, Sichuan Basin. Three typical machine learning algorithms and three population-based optimization algorithms were applied to the core samples and logging data to evaluate the applicability and prediction performance of different methods. Two types of objective functions are well designed to obtain a more satisfactory result for permeability prediction. By comparison, the multi-objective mayfly algorithm (MMA) combined with gradient boosting decision tree (LGB) among all the algorithms had a more vital ability to predict permeability. Therefore, a new self-adaptive predictor was developed by combining the MMA-LGB algorithm with the low-pass filters that were applied as a noise filtering method from the original geophysical well logs with Fourier transform (FT). Filtered logs were tested by using Fractal statistics. Through comparisons, the self-adaptive predictors significantly improved the prediction accuracy with the lowest MSE of 0.239 and the highest R2 of 0.831, well demonstrating that combining the machine learning algorithm with low-pass filters could mitigate the adverse effects of heterogeneity on permeability prediction. The excellent prediction performance of the proposed self-adaptive predictor lays a sound theoretical foundation for logging interpretation and identifying high-quality carbonate reservoirs in the target field.

A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques

A better estimation of the effective porosity of the reservoir rock is a critical task for petrophysicist and well logs analyst. A majority of the current approaches to estimate the effective porosity of the reservoir rocks from well logs are based on the information of the Density-Neutron logs. These approaches usually resulted in the inaccurate estimation of the rock porosity particularly in the naturally fractured carbonates or dolomite rocks. The Nuclear Magnetic Resonance (NMR) based effective porosity is independent of the rock matrix and mineralogy, on contrary it depends on the number of hydrogen nuclei in the pore spaces of the rock. In this study, we have used six machine learning (ML) techniques to predict the NMR based effective porosity in carbonate rocks. The ML models to predict the effective porosity includes deep neural networks (DNN), random forest regressor (RF), decision trees (DT), K-Nearest Neighbors algorithm (KNN), extreme gradient boosting (XGB), and adaptive gradient boosting (AdaBoost). These models were trained on the geophysical well logs such as Gamma ray log (GR), caliper log (Cali), neutron porosity log (NPHI), photoelectric factor log (PE), and bulk density log (RHOB). A total of 4002 data points were obtained from the five wells located in the carbonate field. The tuning of ML models hyperparameters were conducted using a ‘GridSearchCv’ method. Furthermore, the K-fold cross-validation criterion was implemented to improve the accuracy of the ML models. The ML models performances were evaluated using multiple graphical and goodness of fit tests including prediction cross-plots, average absolute percentage error (AAPE), root means square error (RMSE), and coefficient of determination (R2) methods. The prediction results showed that the DNN, RF, and XGB models performed better than the other implemented ML techniques. These methods resulted in a significantly low error and high (R2). The achieved accuracy was above 85% when validated on a blind dataset. This study also offered an empirical model that can be used to quickly estimate the NMR based effective porosity using afore-mentioned well logs. The model can also be used as a standalone package that can be coupled with any logging software for quick evaluation of NMR based effective porosity.

Method for oil and water relative permeability calculating in Western Siberia formations according to capillarimetric and geophysical data

The most important filtration characteristics of productive formations are the oil and water phase and relative permeability. Methods for obtaining relative phase permeabilities can be divided into laboratory and analytical. Currently, the main source of information about RFP are techniques based on laboratory core studies. However, for each productive reservoir, it is desirable to have analytical models describing experimental data on RFP with an accuracy sufficient for practical purposes. The existence of such models will make it possible to increase the accuracy of development computer modeling. The analytical expressions obtained in this study allow us to take into account the influence of the pore channels heterogeneity in size on the relative phase permeabilities magnitude. It is shown that the pore channels heterogeneity in size can be estimated by the residual water saturation amount, which in turn can be determined from the geophysical well studies. Keywords: relative permeability; residual water saturation; pore channels; capillarimetric and geophysical studies.

Geological Structure Features of Carbonate Formations and Their Impact on the Efficiency of Developing Hydrocarbon Deposits

The development of deposits with a complex geological structures is often accompanied by a set of problems associated with optimal decision making. The efficiency of the entire development system depends on the completeness and the quality of the analysis of reservoir parameters. This paper presents methodological approaches for the study of carbonate deposits, and the development of further steps to increase the efficiency of reserve recovery. The secondary transformation of reservoir rocks, resulting in channels of increased conductivity, cracks, and caverns, plays a special role in the nature of the recovery of hydrocarbon reserves from such deposits. Secondary cavernosity leads to violations of the linear laws of fluid filtration in a porous medium, and complicates the field performance prediction based on geological and hydrodynamic modeling. The studied geological structure was detailed using the example of carbonate deposits composed of oil and water- saturated formations, taking into account the results of core studies and the interpretation of geophysical well studies. Furthermore, the parameters of production wells made it possible to confirm that the oil saturated and underlying water saturated formations have hydrodynamic connectivity due to the presence of vertical micro cracks. At the same time, the thickness of the bridge between the reservoirs directly affects the initial water cutting of well production, and further growth dynamics of the water ratio are associated with the structural factors determining the initial oil content of the reservoir. The combination of the obtained dependencies and the distribution model of the reservoir properties along the area made it possible to build a complex map reflecting the predicted development efficiency in certain areas. The integration of the results of various field studies on the injection well stock established that a significant part of the water flows was injected into the water saturated formation, which reduces the efficiency of formation pressure maintenance in the target formation. As a result, in order to reduce the low efficiency injection volume, switching to a more rigid waterflooding system, in terms of the ratio of production and injection wells, is proposed with a further decrease in the injection pressure inside the wells.

Sequence Stratigraphy of Miocene Mixed Carbonate-Siliciclastic in Fold and Thrust Belt System, Banggai Basin

This study was specifically analyzed in the southern part of the Banggai Basin, precisely in the TKA Field. In the Tertiary, regional stratigraphy reveals, the Banggai Sula microplate comprises carbonate shelf and siliciclastic sequence. Several previous studies had been concluding, the tertiary limestone was deposited during the Early Eocene to Middle Miocene. Carbonate formations which has been known by Tomori and Minahaki Formation. Meanwhile, their siliciclastic dominated is Matindok Formation and Celebes Mollase. These sequences formed a distinct stratigraphic style in the geophysical well log and seismic data. Four cycles are distinguished, the lower part of Tomori Formation at the outer shelf and directly overlying by the upper part of inner shelf Tomori Formation. it was superimposed by siliciclastic sediments that have been deposited in the outer litoral during regressive phase. Whereas during rising sea level or highstand, the litoral system migrated to basinward wherein Minahaki Formation was deposited. Sequence stratigraphy provides a reliable methodology for correlate both carbonate and siliciclastic successions. It was analyzed based on 4 wells, 2D, and 3D seismic data which has been available. Sequence stratigraphy analysis using T-R sequence concept by Embry and Johanessen. Trasngressive and regressive phases were obviously determined by lithofacies, coral colony and foram that were recorded on biostratigraphic analyses. In this study, cyclic sea-level change will be recognized as system tract record of mixed carbonate-siliciclastic sequence.

Petrophysical characterization of the Bahariya Oasis Nubian Sandstone Aquifer using geophysical well logging

Petrophysical characterization of the Bahariya Oasis Nubian Sandstone Aquifer using geophysical well logging

Petroelastic modeling of carbonate reservoirs in the view of different void types

Background. Fractures present in carbonate rocks facilitate fluid flow within void spaces. Each type of voids can have a different effect on rock elastic properties, which, in turn, allow the characteristics of voids to be estimated by assessing the velocity of elastic waves. In this paper, an effect of pores and fractures on the velocity of elastic waves is analyzed by petroelastic modeling. An example of solving an inverse problem is presented, involving the determination of fracture porosity and relative fracture opening using the data on elastic wave velocity and hydrocarbon reservoir density obtained during geophysical well logging.Aim. To increase the accuracy of experimental data on the velocity of elastic waves that propagate across hydrocarbon carbonate reservoirs by assessing the pore and fracture characteristics of voids.Materials and methods. The effective medium theory was used as an efficient way to evaluate physical, including elastic, properties based on rock composition and microstructure. Using Berryman’s self-consistent method, we created a model of rock elastic properties, or a petroelastic model, the void space in which was represented by isometric pores and fractures. This model was applied to a well in a petroleum province in West Siberia.Results. The effect of characteristics determining the void space of porous-fractured rocks on the velocity of elastic waves was defined. Velocity surfaces were constructed in accordance with changing parameters of the model, i.e. fracture porosity and fracture aspect ratio. The obtained theoretical and experimental data were compared in order to determine fracture development zones and to evaluate volume concentration and relative fracture opening in these zones.Conclusion. The effect of pores and fractures on elastic wave velocity in porous-fractured carbonate reservoirs was studied by petroelastic modeling. The zones of excessive fracturing were defined and the parameters of volume concentration and relative fracture opening were determined using the data obtained by geophysical well logging in a petroleum province in West Siberia.

Applications of well logging techniques to evaluate the groundwater aquifers in the area between southwest Bani Sweif and west Asyoute governorate, upper Egypt.

The relevance of detecting aquifer characterization and aquifer potential has risen with the application of well logging techniques as the demand for water has increased. Apart from pumping data, 16 geophysical well logs (resistivity, gamma ray, self-potential, and nuclear logs) are utilized to achieve the main goal of estimating petrophysical parameters (porosity (∅), effective porosity (∅𝑒𝑓𝑓), hydraulic conductivity (k), permeability (K) and shale volume (𝑉𝑠ℎ)) of the Apollonia (Eocene fractured limestone aquifer), Upper and Lower Bahariya (Nubian sandstone aquifer) formations. The findings show that the Eocene fractured limestone aquifer has a carbonate in soft chalk with high K and ∅ as well as high k of 4974.39 mD at well ST-188 (a highly productive aquifer), whereas the Lower Bahariya formation is mostly fine to medium-grained sandstone and clay, suggesting that it formed in shallow marine environments with low K. On the other hand, Upper Bahariya was noted that having poor sand succession. As results shown, K of the most examined wells ranges from 2609.69 to 1486.812 mD at ST-258 and ST-38 wells respectively. The study appears that 𝑉𝑠ℎ, along with ∅ and K features, is regarded as an important attribute in aquifer evaluation where, estimated 𝑉𝑠ℎ over the studied area is ranges between 5.96% and 31.7% at ST-48 and WBS1 wells respectively. Overall, this study provides an important insight into the importance of evaluating groundwater aquifers over time to help in making decisions to save and protect groundwater aquifers in the future.