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Article

Geophysical Assessment of Structurally Controlled Mineral Resources at Wadi El-Nakheel, Eastern Desert, Egypt

by
Mohamed Al Deep
,
Arwa Sameer Ibrahim
and
Ahmed Saleh
*
National Research Institute of Astronomy and Geophysics (NRIAG), Cairo 11421, Egypt
*
Author to whom correspondence should be addressed.
Resources 2024, 13(6), 83; https://doi.org/10.3390/resources13060083
Submission received: 24 April 2024 / Revised: 12 June 2024 / Accepted: 13 June 2024 / Published: 18 June 2024
(This article belongs to the Special Issue Mineral Resource Management 2023: Assessment, Mining and Processing)

Abstract

:
It is of great importance to evaluate simple methods to identify mineral occurrence for the future development of society. Applying a reconnaissance magnetic data analysis can help detect the main structural trends mounted to the occurrence of minerals. In this study, geological and geophysical data were analyzed to evaluate the main structural trends affecting mineralization in the area of Wadi El-Nakheel. Geomagnetic data were processed to remove the earth’s magnetic field and reduce the magnetic pole. Some mathematical filters related to detecting and enhancing boundaries between rock units, depending on their magnetization affinity, were applied, including the first vertical derivative, the analytic signal, and 3D Euler deconvolution. After structural analysis of these data, we reached the following findings: The main structural trends from the surface and subsurface estimations were the northwest–southeast trend and the northeast–southwest trend. The orientation and origin of Wadi El-Nakheel are aligned with the main structural trend affecting the area that formed during the Red Sea Rift movement and the Pan-African orogeny. The depth of the deep-seated structure controlling the valley is 1500 m and all mineral occurrence is mainly structurally controlled in the studied area; phosphate ore outcrops are usually aligned with the northwest–southeast geological trend, and metallic ores are related to basement rock succession and the main dominant geological structures in the studied area. Finally, the magnetic method was demonstrated to be a reliable tool for detecting the subsurface boundary between geologic units.

1. Introduction

Wadi El-Nakheel is a prominent inland syncline located in the central Eastern Desert of Egypt. Here are some critical geological aspects of this intriguing area: Wadi El-Nakheel extends in a WNW to NW direction, covering approximately 54 km. Its width varies between 7 to 13 km, and its total area is around 348.8 square kilometers [1]. Wadi El-Nakheel is the region’s most prominent and most conspicuous syncline. It lies between latitudes 25°58′ and 26°16′ N and longitudes 34°20′ and 33°55′ E (approximately 12 km west of the Quseir area). The basin includes several sub-basins, such as Wadi Bayda, Wadi Kareem, and Wadi Abu Hammad. These sub-basins contribute to the overall geological complexity of the area [2]. The region of Wadi El-Nakheel is underlain by Neoproterozoic basement rocks from the Arabian–Nubian Shield. These rocks have a complex tectonic history since their formation. Representative samples collected from different rock units in the Wadi El-Dahal area revealed Carboniferous zircon fission-track cooling ages of 353 ± 9 Ma and 344 ± 11 Ma; the southeastern and northwestern parts of Wadi El-Nakheel are characterized by a thick sedimentary cover of 385 m and 1300 m, respectively, as stated by [3,4].
Geological lineaments are linear features on the Earth’s surface that indicate significant tectonic units within the crust. These features are associated with various geological processes, including the formation of minerals, active faults, groundwater flow, earthquakes, and geomorphology [5]. Let us delve into this topic further. Lineaments can take different forms, such as fracture zones, shear zones, and igneous intrusions (like dykes). They often appear as linear patterns on geological or topographic maps and can be evident in aerial or satellite photographs [6]; these linear features provide valuable clues about underlying geological structures and processes. Geological lineaments play a crucial role in identifying potential mineralized zones in different ways.
Lineaments often coincide with fault zones, fractures, and other structural features. These structures can act as pathways for mineral-rich fluids to migrate and accumulate. Lineaments intersect with areas of hydrothermal alteration, where hot fluids alter the composition of rocks. These altered zones may host valuable minerals. Lineaments can guide exploration efforts by highlighting areas with anomalous geochemical elements associated with mineralization. Lineaments may correlate with elevated radioactivity, indicating the presence of radioactive minerals. Lineaments help delineate different rock units, aiding in understanding their geological context.
In tectonic studies, lineaments on a regional scale remain controversial. Although published models explain their presence in most geodynamic environments as a result of enhanced erosion along strikes regular to the upper crustal regional extension, these models fail to account for lineament domains in regional strike-slip corridors that separate regional blocks, including transform faults [7].
The tomography method for the early identification of abnormal regions in complex rock-mass structures uses travel-time tomography, the damped least-squares method, and Gaussian filtering. Numerical and laboratory experiments show this method can detect abnormal regions, providing new insights into hazard detection in underground geotechnical engineering [8]. A different study also revealed that the activity of cracks during rock fracture increases, leading to the formation of initially damaged, progressively damaged, and fractured zones. This information can be used to predict the position of the main fracture in rocks [9].
Magnetic detection of lineaments is commonly used in geological and geophysical exploration, mineral exploration, groundwater exploration, and environmental studies. It can help identify subsurface structures that may influence the distribution of resources, geological hazards, or environmental factors. Lineament detection follows some criteria presented by [10].
The magnetic method is sensitive to some highly magnetized minerals; the presence of these minerals in different ratios in different types of sediments makes this method a potent tool for differentiating rock types. Mineral exploration using the magnetic method has been applied by many authors in similar geological settings [11,12,13,14,15,16,17].
The Minerals identified in this study, as shown in Figure 1 include sedimentary origin phosphate, located within the Dawi Formation; chromium mineral (Cr), located in a single location and related to the ophiolitic serpentinite formation; tantalum, niobium, and tin (TaNbSn); and talc Ore are located within the ophiolitic volcanic basin. In this study, the application of the geomagnetic method for mineral exploration was conducted by many authors [18,19,20].
In this study, we used available geological and magnetic data to assess the relationship between lineaments detected from the surface and subsurface of the area of Wadi El-Nakheel.

2. Materials and Methods

2.1. Location and Geology

The area is located in the eastern part of Egypt’s Eastern Desert and is bounded by 26°00′ to 26°15′ to the north and bordered by 33°51′ and 34°15′ to the east (Figure 1). This area was highly deformed during the Red Sea Rift and the Pan-African orogeny; the lithology of the studied area varies from Precambrian metamorphic and basement rocks to Phanerozoic sedimentary cover; the geological map (Figure 1) was traced from the geological map of Egypt NG-36-NE Quseir datasheet after CONOCO [21]. The most significant lithological units can be described as follows.
Basement rocks include the ophiolitic mélange found in Egypt’s Central Eastern Desert (CED). They represent an intact ophiolitic sequence of oceanic crust, blocks, and fragments. These ophiolites occur both as a coherent sequence and as dismembered components. The ophiolite sequence primarily consists of metagabbro, sheeted dykes, and pillow lavas. It can be described as exotic fragments of the oceanic lithosphere tectonically incorporated into a volcaniclastic matrix, forming a fascinating tectonic ophiolitic mélange. The pillowed metabasalts are classified as high-Ti MORB-type, comparable to MORB or BABB (back-arc basin basalt) ophiolites. These likely originated from evolved magma within an intra-oceanic back-arc basin. It also represents remnants of oceanic crust that once formed the basin floor and were tectonically obducted during its closure [22,23]. In the tectonic context, the formation of the Ghadir ophiolitic mélange involved tectonic processes within a back-arc basin. Some dismembered ophiolitic rocks were also emplaced along structural contacts. Overall, MORB (mid-ocean ridge basalt) ophiolites in the Eastern Desert (ED) of Egypt are thought to have formed in a back-arc basin due to the collision of an island arc system with the African continent. Neoproterozoic ophiolites are widespread in the Arabian–Nubian Shield (ANS), ranging in age from 690 to 890 Ma. These ophiolites are crucial for understanding the evolution of the Pan-African orogeny. They can be classified into two main types: MORB (mid-ocean ridge basalt) ophiolites and SSZ (supra-subduction zone) ophiolites.
Older granite (grey granite) occurs in the studied area; it is calc-alkaline, usually foliated quartz-dioritic to granodioritic rocks (previously “Grey Granite” or “Older Granite”) in part, and deeply weathered. The younger granite, another plutonic rock within the area, is described as alkaline, generally undeformed granitic to alkali-feldspar granitic rocks (previously “Pink Granite” or “Younger Granite”) in part. Volcanic rock units include the Dokhan volcanic, composed of calc-alkaline andesitic to rhyolitic volcanic rocks, and post-Hammamat felsite. Hammamat classics consist of molasse-type conglomerate to siltstone sequence.
Phanerozoic sediments include the Thebes Group Formation, thinly bedded outer shelf chalk, and chalky limestone rich in chert bands and concretions. Near Quseir city, there are more biogenic and nodular limestone with uppermost middle Eocene beds [24]. The Umm Gheig Formation is a crystalline carbonate, algal, local reefal limestone. The Shagra Formation is composed of sandstone; its lower part is bioclastic, with some coarse-grained siliciclastic and a lower part of fine-grained siliciclastic, lacustrine limestone, and marl. The Umm Mahara Formation is composed mainly of bioclastic reefal and algal carbonate rock, underlain by the Ranga Formation and siliciclastic fanglomerates, and an interface of siltstone and sandstone. The Taref Formation belongs to the Nubian Group and is part of the Cretaceous succession. It predominantly consists of yellowish, pale red, pink, and white massive and cross-bedded sandstone. These layers exhibit a fining-upward cyclic pattern. Mineralogically, the Taref Sandstone contains quartz, feldspars, and rock fragments, with average proportions of 97.9%, 1.2%, and 0.9%, respectively. Based on its composition, the Taref Sandstone can be generally classified as a quartz arenite mineral after [25].
The Duwi Formation contains mostly phosphatic minerals and has phosphate beds alternating with black shale, marl, and oyster limestone. It is located within the study area. These sediments were primarily deposited in shallow epeiric seas, flanking the southern margin of the Tethyan trough. The Duwi Formation comprises a heterogeneous suite of shallow marine rocks, including phosphate, shale, mudstone, marlstone, glauconite, and dolomite [25]. Quaternary and wadi deposits are situated unconformably on some of the older formations and are composed mainly of raised beaches, alluvial fans, wadi deposits, sand, and gravel.

2.2. Methodology

This study involved correlation between mineral location and the structure distribution within the area under study and a surface structure analysis to detect the major and minor structures made after tracing the fault system from a geological map of the area. In addition, lineament detection from geomagnetic data was undertaken using the RTP map, FVD. The technique proposed by [26] was used to trace magnetic structural lineaments where structures follow certain patents, like elongation of contour lines, alignment of small anomalies in a linear shape, etc. An analytic signal map detected major faults within the area. A 2D model using [27]’s software was conducted in areas where sedimentary cover exists; all structures generated were then correlated with discovered minerals in the studied areas.

2.2.1. Geomagnetic Data Processing

The Western Geophysical Company of America acquired the total magnetic data using a proton precision magnetometer with a sensor that had high sensitivity at a time of approximately 0.01 nT. The aeromagnetic survey was conducted in 1983 [28] with a sampling rate of 1 km, tie lines every 15 km, and terrain clearance of 120 m. The area’s International Geomagnetic Reference Field (IGRF) model was calculated and removed from these data. The magnetic field parameters, magnetic intensity (H) 42,425 Gamma, inclination 39.5°, and declination 2°, describe the main geomagnetic field related to the earth’s core, and removing these values gives the resulting magnetic anomalies related to the rocks. I is the magnetic inclination or dip angle, the angle between the Earth’s surface and the magnetic field line at a given location. It represents how steeply the magnetic field lines intersect the Earth’s surface. D is magnetic declination, or magnetic variation, which is the angle between true north (geographic north) and magnetic north (the direction in which a magnetic compass points) at a particular location.
The total magnetic intensity (TMI) anomaly map, shown in Figure 2, indicates that the magnitude ranges from 688 to 1213 nT. In the reduced-to-pole (RTP) map shown in Figure 3, the magnetic field ranges from 668 to 1380 nT, and most of the anomalies are oriented northwest–southwest, which is the direction of Wadi El-Nakheel. RTP is a mathematical transformation applied to total magnetic intensity (TMI) data. It aims to create a map that is more closely related to actual rock units’ locations, depending on their magnetization (and, therefore, geology) rather than the original TMI map, which is affected by the inclination and declination of the earth’s magnetic field.
To fulfill the goals of this study, the geological map was traced to extract surface geological lineaments, and Rose diagrams were constructed to show dominant trends. Magnetic data were treated to remove the main earth geomagnetic field (IGRF) and reduced to the magnetic pole map to reorient the location of magnetic anomalies. The analytic signal map was constructed and used using the absolute value of the analytical signal in the determination of magnetic source parameters without making assumptions regarding the direction of magnetization of the magnetic source body [29]. The following equation satisfies the basic requirement of the analytic signal [30,31]
A x , y = M x x + M y y + M z z
where, A x , y is the amplitude of the analytic signal, M x represents the magnetic derivatives on the x direction, etc.
The first vertical derivative map (1VD) enhanced the vertical location of magnetized bodies.
The three-dimensional Euler deconvolution is a geophysical technique used to calculate the position of discontinuities in physical properties without relying on prior local geological information [32,33]. The Euler deconvolution is employed to identify faults and other geological structures based on potential field data (such as magnetic or gravity data). It allows us to estimate the depth and location of these subsurface features. The Euler’s homogeneity equation, when taking into account a base level for the background field, can be written [34] as follows:
x , x 0 T x + y , y 0 T y + z , z 0 T z = N B T
where, “T” is the observed field, “x0, y0, z0” are source anomaly locations, “B” is the base level of the observed field, and “N” is the structural index, which is the main expression representing the dimensionality of the detected structures. We applied order (N = 0) to detect the boundary between lithological units and order (N = 1) to detect causative body location. Processing and filtering of magnetic data were carried out using software [35].
Lineaments criteria were applied to different magnetic maps to detect the deep-seated structure controlling the lithological boundaries and the structure related to the formation of Wadi El-Nakheel.
The first vertical derivative (1VD) quantifies the rate of change of a signal concerning survey height. It explains how the signal (such as a magnetic field, gravity, or other geophysical measurement) varies vertically. The amplitude ranges from −0.98 to 0.93 nanotesla/meter. The 1VD can enhance geological and geophysical maps. It helps identify geological structures, faults, and mineral deposits; the 1VD is shown in Figure 4.
The analytic signal map derived from magnetic data is a geophysical tool used to enhance and interpret magnetic anomalies, particularly in identifying subsurface geological structures such as faults, fractures, and mineralized zones. Here is a description of the meaning and significance of the analytic signal map. The analytic signal is a mathematical transformation applied to magnetic data that enhances the amplitude and sharpens the edges of magnetic anomalies. It is calculated using the horizontal and vertical gradients of magnetic field measurements. The analytic signal map highlights areas of rapid change or discontinuity in the magnetic field, making subtle anomalies more pronounced and more accessible to identify. This enhancement helps delineate the boundaries and edges of magnetic features, such as fault zones or mineral deposits, with greater clarity. The amplitude of data ranges from 0 to 1.09 nT/m. the analytic signal map is shown in Figure 5.

2.2.2. Magnetic Modeling

Two-dimensional magnetic modeling using Talwani’s theory is a geophysical technique employed to interpret magnetic anomalies and infer subsurface geological structures. This method, developed by [27], is particularly useful in the context of geological exploration and understanding subsurface features such as faults, dykes, and ore bodies. Talwani’s theory provides a mathematical framework for modeling the magnetic effect of two-dimensional bodies with complex geometries. The theory assumes that geological bodies can be approximated by a series of polygons, and the magnetic effect at the surface can be calculated from these polygons. In polygonal approximation, the subsurface geological structure is represented as a series of adjacent, vertically infinite polygonal prisms. Each prism has a constant magnetization vector.
To calculate the model, consider a polygon with vertices coordinates x i , z i ,   i = 1 , , n i = 1 , , n . The vertical component of the magnetic anomaly at a point x , z due to a single polygon edge can be expressed as:
Z i = M . z i + 1 z i x i 1 x i 2 + z i 1 z i 2 ln x x i 2 + x x i 2 x x i + 1 2 + z z i + 1 2
M is the magnetization of a body, determined by its susceptibility χ   and the ambient magnetic field H, as follows
M = χ H
Then, the vertical component of the magnetic field anomaly due to a single polygonal prism Z i can be calculated.

3. Results and Discussion

Surface structures traced from the geological map of Egypt NG-36-NE Quseir datasheet after [21] (Figure 6a–c) show the major and minor lineaments traced from the geological data sheet. The major trends dominating the area are northwest–southeast, as shown in the major lineaments analysis (Figure 6b). This trend is related to the Red Sea Rift orogeny. Another minor trend is the northeast–southwest direction, and it may be associated with the Gulf of Aqaba. The main Wadi El-Nakheel orientation is related to the northeast–southwest direction, while the smaller valleys trisecting Wadi El-Nakheel are related to the northeast–southwest trend. Figure 6c shows the minor trends. The same dominant geological trends are reported in addition to minor geological trends (north–south, east–northwest, and west–northeast).
The magnetic method is a sensitive geophysical technique. Regarding variation in the degree of magnetization of minerals, which varies in different types of rocks, the RTP lineaments (Figure 7a,b) clearly show that of the major dominant trends appearing in the surface geological analysis, the northeast–southwest is the most dominant. The northeast–southeast occurred with a smaller magnitude in addition to the minor lineaments direction in the background. The first vertical derivative structure trend (Figure 8a,b) shows a clearer view of the deep-seated structure trends because the 1VD map enhances the vertical distribution of the magnetic properties of the rocks, and consequently the boundary between rock units. The major lineaments dictated from this analysis were the northwest–southeast trend and the northeast–southwest trend. The analytic signal lineaments (Figure 9a,b) show similar geophysical behavior, as the analytic signal shows the same anomaly distribution as the RTP map; there is a high resemblance between the two maps, and the detected lineaments and geological trends shown in this map are the significant lineaments dictated from this analysis, the northwest–southeast trend and the northeast–southwest trend.
Results were obtained from the three-dimensional Euler deconvolution applying structural index 0 to detect boundaries between geological units based on their magnetization properties; the depth to magnetic sources started from 0 to a maximum depth of 1500 m. Deeper boundaries were located around the boundaries of the valley of Wadi El-Nakheel and to the west, where the boundary was between basement rocks and sedimentary succession, as shown in Figure 10.
The Euler deconvolution applying SI = 1 is presented in Figure 11, showing the alignment of the detected highly magnetized rocks. Regarding the deep-seated structures that control the wadi boundaries, we detected that the depth to the valley basement is about 1500 m. Wadi El-Nakheel is composed of sedimentary rocks surrounded by igneous and metamorphic rocks. The depth of the structure describes the extent of the fault system controlling the valley’s geomorphology.
Results obtained from the 2D magnetic modelling show the surface of the basement rocks, which is characterized by a rough surface and subjected to many faults. The profile location is shown in Figure 12a, where all profiles are traced on areas covered with sediments.
Two layers were assumed for smooth inversion. The first layer was sedimentary over, which varies in thickness from a few to hundreds of meters. The sediment layer’s magnetic susceptibility ranged from 0.000007 to 0.000371 CGS units, whereas the magnetic susceptibility of basement rocks ranged from 0.00143 to 0.003 CGS units; models generated by GM-SYS software (V 4.6) are shown in Figure 12b, e.
The results obtained from the geological and geomagnetic data analysis are plotted in a single map in Figure 13, Beside the location of mines with different kinds of minerals, and major subsurface lineaments

4. Conclusions

This paper aimed to analyze structural trends based on available geological and geophysical data and their relation to mineral resources presented in the studied area. It also aimed to detect the main geological trends related to the morphology of Wadi El-Nakheel. We determined the structural origins of Wadi El-Nakheel and the main part of the valley through a thorough structural analysis of the geological map and the sub-surface structural trend estimated from magnetic data. The RTP map, the 1DV map, and the analytic signal map show the valley orientation is connected to the primary geologic trend of the study area, which is the northwest–southeast trend. The sub-streams dissecting the valley are oriented with the secondary geologic trend, the northeast–southwest trend. Within the valley, magnetized sources reach a depth of up to 1500 m. Regarding structures affecting mineralization allocation, we detected that sedimentary mineral phosphate is aligned with outcrops of the Dawi Formation, with the primary structural trend in the area being northwest–southeast. All types of metallic ores are related to major and minor geological trends, as shown in Figure 12, and most ores situated along the lineaments derived from the magnetic field. Finally, the magnetic method can add important information about mineral allocation through structural analysis.

Author Contributions

Conceptualization, M.A.D., A.S.I. and A.S.; methodology, M.A.D., A.S.I. and A.S.; software M.A.D., A.S.I. and A.S.; validation, M.A.D., A.S.I. and A.S.; formal analysis, M.A.D., A.S.I. and A.S.; investigation, M.A.D., A.S.I. and A.S.; resources, A.S.; data curation, M.A.D., A.S.I. and A.S.; writing—original draft preparation, M.A.D., A.S.I. and A.S.; writing—review and editing M.A.D., A.S.I. and A.S.; supervision, M.A.D., A.S.I. and A.S.; project administration, A.S.; funding acquisition, A.S. All authors have read and agreed to the published version of this manuscript.

Funding

This study is part of the work supported by the Science, Technology and Innovation Funding Authority (STDF), Egypt, under grant number 37233.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to it needing permission from the STDF administration.

Acknowledgments

This study is part of the work supported by the Science, Technology and Innovation Funding Authority (STDF), Egypt.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish results.

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Figure 1. The right panel shows a simple location map of the studied area, and the left panel shows the lithology and minerals found in the studied area (modified from [19]).
Figure 1. The right panel shows a simple location map of the studied area, and the left panel shows the lithology and minerals found in the studied area (modified from [19]).
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Figure 2. The total magnetic map.
Figure 2. The total magnetic map.
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Figure 3. The reduced-to-pole map.
Figure 3. The reduced-to-pole map.
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Figure 4. The first vertical derivative map.
Figure 4. The first vertical derivative map.
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Figure 5. The analytic signal is calculated from magnetic data.
Figure 5. The analytic signal is calculated from magnetic data.
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Figure 6. (a) Surface geological structures traced from CONOCO (1987), (b) the Rose diagram of the major lineaments, and (c) the Rose diagram of the minor lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
Figure 6. (a) Surface geological structures traced from CONOCO (1987), (b) the Rose diagram of the major lineaments, and (c) the Rose diagram of the minor lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
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Figure 7. (a) The structure traced from the reduced-to-pole map and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
Figure 7. (a) The structure traced from the reduced-to-pole map and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
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Figure 8. (a) The structure traced from the first vertical derivative and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
Figure 8. (a) The structure traced from the first vertical derivative and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
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Figure 9. (a) The structure traced from the analytic signal and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
Figure 9. (a) The structure traced from the analytic signal and (b) the Rose diagram of detected lineaments. The highest, moderate, and least repeated structural trend in the area is associated with the red, blue, and grey color of the rose diagram petals.
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Figure 10. The Euler deconvolution was detected using SI equal to 0.
Figure 10. The Euler deconvolution was detected using SI equal to 0.
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Figure 11. The Euler deconvolution detected using SI equal to 1.
Figure 11. The Euler deconvolution detected using SI equal to 1.
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Figure 12. Two-dimensional geomagnetic modelling. (a) Location map of the modeled geomagnetic profile with RTP map in the background and areas with basement rocks outcrops colored grey. (be) Inverted geomagnetic profiles from p1 to p4.
Figure 12. Two-dimensional geomagnetic modelling. (a) Location map of the modeled geomagnetic profile with RTP map in the background and areas with basement rocks outcrops colored grey. (be) Inverted geomagnetic profiles from p1 to p4.
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Figure 13. Minerals’ locations in relationship to detected lineaments, with the analytic signal in the background to highlight the geological boundary.
Figure 13. Minerals’ locations in relationship to detected lineaments, with the analytic signal in the background to highlight the geological boundary.
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Al Deep, M.; Ibrahim, A.S.; Saleh, A. Geophysical Assessment of Structurally Controlled Mineral Resources at Wadi El-Nakheel, Eastern Desert, Egypt. Resources 2024, 13, 83. https://doi.org/10.3390/resources13060083

AMA Style

Al Deep M, Ibrahim AS, Saleh A. Geophysical Assessment of Structurally Controlled Mineral Resources at Wadi El-Nakheel, Eastern Desert, Egypt. Resources. 2024; 13(6):83. https://doi.org/10.3390/resources13060083

Chicago/Turabian Style

Al Deep, Mohamed, Arwa Sameer Ibrahim, and Ahmed Saleh. 2024. "Geophysical Assessment of Structurally Controlled Mineral Resources at Wadi El-Nakheel, Eastern Desert, Egypt" Resources 13, no. 6: 83. https://doi.org/10.3390/resources13060083

APA Style

Al Deep, M., Ibrahim, A. S., & Saleh, A. (2024). Geophysical Assessment of Structurally Controlled Mineral Resources at Wadi El-Nakheel, Eastern Desert, Egypt. Resources, 13(6), 83. https://doi.org/10.3390/resources13060083

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