Sharp lineaments outlining from advanced edge detectors of aeromagnetic data: Gabal Ineaji area, South Eastern Desert, Egypt

ABSTRACT

To interpret geological structures, edge detection is a crucial step. Thus, high-precision computing of the boundaries of possible sources is evolving a necessity to study the subsurface structures. In this study, the tilt-angle, the Tilt-Angle of the total-horizontal gradient, the Tilt-Angle of the Tilt-Angle gradient, and Improved Logistic filters were applied to aeromagnetic data from Gabal Ineji data, South-Eastern-Desert of Egypt. The results have been used to give more precisely accurate structural maps, particularly when compared to revealed geological structures. that gives reliable interpretations. The utilised methods showed that the NW-SE and N-S trends play an effective role in formulating the structural setting of the research area.

KEYWORDS:

• Aeromagnetic, lineaments and structures
• edge detection
• Eastern Desert, Egypt

1. Introduction

Determination of causative sources plays a huge step in the delineating potential-field anomalies (Bournas and Baker 2001; Ardestani and Motavalli 2007). Therefore, the efficiency of the boundary detector filters needs proper tracing of the horizontal locations of the causative bodies (Saada et al. 2021a, 2021b, 2022; Eldosouky et al. 2022a,b,c,d; Ekwok et al. 2022; Pham et al. 2022). The magnetic data have a connection with variations in magnetic-susceptibilities and the depths of their origins. As a result, these data are employed to identify the depths and extent of the magnetic sources that they have produced. The abundance of magnetic data that was used for reconnaissance investigations of petroleum and minerals has recently made this goal particularly essential.

To assess the properties of magnetic sources, numerous techniques have been devised, such as boundary locations and depths, based on the usage of magnetic derivatives (Salem et al. 2008). The Source-Parameter-Imaging (SPI) was employed by Salako (2014) to assess the depth of the basement surface. Different methods have been involved to recognise structures (subsurface) and the boundaries of anomalies and magnetic sources (Hinze et al. 2013; Pham et al. 2020,b). These techniques, which rely on magnetic field derivatives, are effective in that they can overcome imperfect data and involve little computational work (Pilkington and Tschirhart 2017). The analytic-signal (AS) amplitude (Nabighian 1972, 1974; Roest et al. 1992) and the total-horizontal gradient (Cordell and Grauch 1985) are two examples of standard techniques in this class. These filters have been operated to outline the causative origins in aeromagnetic data (Behrendt et al. 1996; Bastani and Pedersen 2001), besides being employed as elements to advance other filters (Wijns et al. 2005; Cooper 2009; Ferreira et al. 2013). To balance the low- and high-amplitudes due to deep- and shallow-sources, respectively, several methods have resorted to adjustment, the concentration is done on local-phase techniques such as Tilt-Angle (TA) (Miller and Singh 1994), Theta-Map (TM) (Wijns et al. 2005), and Horizontal Tilt-Angle (HTA) (Cooper and Cowan 2006). These methods have widespread use than higher-order derivatives (Verduzco et al. 2004; Ferreira et al. 2013). The Euler deconvolution was also provided by Thompson (1982) to ascertain the depth of the basement surface.

Several derivative strategies are discussed in this work as the Tilt-Angle (TA), the Tilt-Angle of the total-horizontal gradient (TAGH), the Tilt-Angle of the Tilt-Angle gradient (TTDR), and Improved Logistic filter (IL) have been applied to the aeromagnetic data from Gabal Ineaji area, Egypt for locating the probable boundaries of the magnetic sources taking into consideration the surface lineaments exhibited by the geologic map. Finally, depicting and constructing the whole structural architecture of the research area.

2. Methods

Various approaches are concerned with delineating the edges of potential-field (PF) anomalies caused by geologic structures. Newly, edge detectors comprise an actual stage in the PF data interpretation (Eldosouky et al. 2022a,b,c,d). To avoid noise effects while dealing with aeromagnetic data, the Upward-continuation (UC) technique is utilised to filter shallow local “noise” and highlight deep regional anomalies, as this technique can be employed as an effective smoothing strategy for removing noisy short wavelengths. The formula for calculating upward continuation in Geosoft INC (2015) is:

(1) $\mathrm{L}\left(\mathrm{r}\right)\mathit{\hspace{0.17em}}=\mathit{\hspace{0.17em}}{\mathit{e}}^{-\mathit{hr}}$(1)

where h = continuation level and r = is wavenumber (Dobrin and Savit 1988).

The following step, for interpretation purposes, is to use a variety of enhancement techniques that include different phase-based methods, which are used to show the boundaries of both residual and regional sources. The tilt-angle (TA) was the first phase-based approach proposed (Miller and Singh 1994). given by:

(2) $\mathbf{TA}=\mathit{\hspace{0.17em}}{tan}^{-1}\frac{\mathrm{dz}}{\sqrt{{(\mathrm{dx})}^2+{(\mathrm{dy})}^2}}$(2)

where dx, dy and dz = gradients of the potential field data in the x, y and z directions respectively.

It normalises the vertical derivative by using the amplitude of the entire horizontal derivative. Verduzco et al. (2004) revealed in their work that the TA filter also acts automatic gain-control of anomalies. Hence, the filter is effective in tracing out striking anomalies (Cooper and Cowan 2006).

Ferreira et al. (2013) suggested using the TAHG filter, which is given by:

(3) $\mathbf{TAGH}=\mathit{\hspace{0.17em}}\mathbf{atan}\mathit{\hspace{0.17em}}\frac{\left(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dz}}\right)}{\sqrt{{(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dx}})}^2+{\left(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dy}}\right)}^2}}$(3)

Where δ$\mathrm{THDR}$/δx and δ $\mathrm{THDR}$/δy and δ $\mathrm{THDR}$/δz = first-order horizontal derivatives in the x, y, and z directions of the horizontal-gradient derivative ($\mathrm{THDR}$).

Another edge detection method, related to the assignment of the tilt from the tilt derivative was likewise proposed by Cooper and Cowan (2006) to enhance the edges of the PF sources as follows:

(4) $\mathbf{TTDR}=\mathit{\hspace{0.17em}}\mathbf{atan}\mathit{\hspace{0.17em}}\frac{\left(\frac{\mathrm{\partial }\mathbf{Tilt}}{\mathbf{dz}}\right)}{\sqrt{{(\frac{\mathrm{\partial }\mathbf{Tilt}}{\mathbf{dx}})}^2+{\left(\frac{\mathrm{\partial }\mathbf{Tilt}}{\mathbf{dy}}\right)}^2}}$(4)

Where δ$\mathrm{Tilt}$/δx, δ$\mathrm{Tilt}$/δy, and δ$\mathrm{Tilt}$/δz = first-order horizontal derivatives of the TA in the x, y, and z directions.

The last utilised method (Pham et al. 2020) deals with the logistic-function of the AS (Pham et al. 2018) to equalise the signals. It is named as the improved logistic (IL) and given by:

(5) $\mathbf{IL}=\mathit{\hspace{0.17em}}\frac{1}{1\mathit{\hspace{0.17em}}+\mathit{exp}\left[\mathit{\hspace{0.17em}}\mathrm{\_}\mathit{p}\left({\mathit{R}}_{\mathit{THDR}}\mathit{\hspace{0.17em}}\mathrm{\_}\mathit{\hspace{0.17em}}1\right)\mathit{\hspace{0.17em}}+1\right]}$(5)

where,

(6) ${\mathit{R}}_{\mathit{THDR}}=\frac{\left(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dz}}\right)}{\sqrt{{(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dx}})}^2+{\left(\frac{\mathrm{\partial }\mathbf{THDR}}{\mathbf{dy}}\right)}^2}}$(6)

And p between 2 and 5.

2.1. The geology

Gabal Ineaji is located to the East side of Lake Nasser southeast of Aswan city by 180 km (Figure 1). It is framed by Latitudes 22° 02“& 23° 23” N and Longitudes 33° 47“& 34° 22” E. The Gabal Ineaji area is a part of the Precambrian belt of the South-Eastern-Desert (SED) that is covered mostly with foreland sediments ranging in age from Quaternary to Cretaceous, that unconformably overlie Precambrian basement rocks represented by younger granites (Conoco 1987). The Gabal Ineaji area is mountainous with moderate to high relief and the majority is covered by crystalline basement (Igneous and Metamorphic) rocks in its eastern parts.

Figure 1. Location of Gabal Ineaji area, SED, Egypt.

The Precambrian rocks overlay the southern and western portions of the research area, comprising metasediments and calc-alkaline granites (younger and older granites).

The sedimentary cover in the northeastern portion of the research area indicated the superiority of Upper-Cretaceous Nubian-Sandstone sequence which is placed from the most aged to the youngest as follows; Abu Aggag and Um Barmil formations, overlain by Quaternary deposits which take place as a wadi filling. Metamorphosed Leucocratic is found in the southern portion of the research region (Conoco Inc 1989). The exposed rock units could be arranged into four main groups from younger to older (Schandelmeier et al. 1983, 1987; Greiling et al. 1988):

1. Quaternary deposits.

2. Cordilleran-stage associations (diverse varieties of granites).

3. Island-arc assemblage and Pan-African-ophiolites.

4. Pre-Pan-African rocks.

According to (El-Shazly 1966), Gabal Ineaji area contains four major provincial fault trends (NE – SW, NW – SE, E – W & N – S).

Inspection of the associated geologic map (Figure 2) exhibits a lot of structural surface trends that are mapped over it. Analysis of these outlined trends reveals that they assume various trends with different frequencies. These trends can be arranged according to the degree of their importance as follows: NE-SW, ENE-WSW, NW-SE, N-S, and W NW-ESE.

Figure 2. Geologic map of Gabal Ineaji area.

2.2. Airborne geophysical magnetic data

The Airborne geophysical data were obtained from the survey of Aero-Service (1984). This airborne survey was conducted over most Egyptian Eastern Desert, following parallel flight lines that are 45 and 225 degrees from true north and spaced 1.5 km apart in a NE – SW trajectory. The tie lines were being passed in a NW-SE orientation, perpendicular to the principal flying line, at azimuths of 135 & 315 from north (Aero-Service 1984). The magnetic declination and inclination were 2° E and 39°.5 N, respectively. The analog sheet data of the survey was digitised and then gridded employing the minimum curvature process to construct the total magnetic-intensity (TMI) map of Gabal Ineaji area (Figure 3). Then, to remove the impact of the earth’s magnetic regional field, the International Geomagnetic-Reference Field (IGRF) was subtracted (Figure 3).

Figure 3. TMI map of Gabal Ineaji area.

The TMI data were reduced to the North-Magnetic-Pole (Figure 4), utilising the Gesoft packages (V. 8.4), to proccess the effects of declination and inclination of the magnetic field. The parameters operated for the transformation are Dec. of 2°E and Inc. of 39°.5N which indicated the mean value for the research area. The reduced-to-the-pole (RTP) map (Figure 4) shows that the area is affected by many of shallow high and low magnetic anomalies of varying wavelengths, amplitudes, and sizes, as well as magnitudes. The diversity in amplitudes of these magnetic anomalies may reflect changes like geologic rocks and their depths, respectively.

Figure 4. RTP map of Gabal Ineaji area.

The RTP map shows a maximum amplitude value of about 245.092 nT in the western, southeastern, and northeastern parts which are associated with Leucocratic metamorphic rocks, and older and younger granite. The shapes of these high magnetic anomaly features are elongated in the southeastern and northeastern parts with NE direction, while the southwestern part shows broad positive anomalies trending in SW and WNW directions.

On other hand, the low magnetic features are associated with metasediments and sedimentary rocks with a minimum amplitude value of about − 289.881 nT in the northeastern and southeastern regions of the area trending in NE and SW directions. The aeromagnetic RTP map (Figure 4) elucidates that almost all of the magnetic anomaly trends are in the NW, SE, NS, and EW directions which may be due to the effect the Gulf of Suez opening, Syrian Arc system, and Red Sea tectonic forces.

3. Results

To minimise the noise effects and help detecting of deep structures, the RTP (Figure 4) data is upward-continued to an altitude of 100 m (Figure 5) (Ferreira et al. 2013).

Figure 5. Upward continuation (UC) of RTP map of Gabal Ineaji area.

The edges assessed by the TA filter are shown in (Figure 6). The TA map provides the boundaries of Gabal Ineaji region, so that the edges can be traced along TA-zero contours.

Figure 6. TA map of Gabal Ineaji area.

The edges are calculated using the TAHG filter (Figure 7). It can reveal all the horizontal source boundaries and also equalise signals derived from both deep and shallow sources. The TAHG approach is exceptional because it allows for peak amplitudes over the borders of the sources, has an appropriate resolution, and is least dependent on the structure depths. Also, the TAHG method has the best resolution in locating the borders of deeper sources.

Figure 7. TAGH map of Gabal Ineaji area.

The boundaries determined by using the TTDR method (Figure 8) detect many geologic features. The obtained edges from TTDR are connected and hazy making the interpretation more dificult.

Figure 8. TTDR map of Gabal Ineaji area.

On the other hand, as shown in (Figure 9) the IL filter can prevent any ambiguous result. the IL technique of the Upward-continuation (UC) can map the boundaries of deep features and deepest ones shaply than the other techniques.

Figure 9. Improved logistic (IL) map of Gabal Ineaji area.

4. Discussion

Reviewing the results obtained from the enhanced maps showed a variety of structure trends that are more declared and pronounced from the IL technique. These trends were consistent with those illustrated by the surface geological map as depicted in Figures 10 and 11. Meanwhile, plenty of other trends that prevailed in the subsurface were exhibited. This geophysical subsurface interpretation coincides with that of geological results previously obtained by El-Shazly (1966).

Figure 10. The lineaments (after Conoco 1987) extracted from the geologic map in Figure 2.

Figure 11. Rose diagram of the lineaments in Figure 10.

It deserves mention that using the applied edge filters reveal how well they performs in dealing with extremely distorted regions. Hence, these filters can be utilised to produce structural maps that are extremely accurate (Eldosouky et al. 2022). The filters also sharply delineate the boundaries of both the residual and regional sources. A new image for the structures of Gabal Ineaji area, SED of Egypt is produced using this technique, and the edges are declared in (Figure 15).

Accordingly, based on the results obtained from different utilised filters (TDR, TAGH, TTDR, and IL) (Figures 12–15), rose diagrams (Figure 16) have been created statistically to represent the various trends of the mapped lineaments. The examination of the extracted faults reveals the predominance of N-S, ENE, WNW, NE, NW, and E-W trends.

Figure 12. Lineaments trend of TDR.

Figure 13. Lineaments trend of TAGH.

Figure 14. Lineaments trend of TTDR.

Figure 15. Lineaments trend of improved logistics (IL).

Figure 16. Rose diagram of (a) TDR; (b) TAGH; (c) TTDR; and (d) IL.

It deserves mention that these trends were registered, in different parts of the southeastern desert of Egypt, as associated with mineral deposits (Ammar et al. 1983; El Rakaiby and Kamel 1988; Hussein et al. 1988; Garson and Krs 1976 and many others).

These trends assume that the N-S, NW, E-W, and NE follow the Precambrian tectonism. They agree well with the conclusions of Abdel Gawad (1967), Eldosouky et al. (2022a) and Hamimi et al. (2023), meanwhile, they disagree with Hunting Geology and Geophysics Ltd (1967) and also Krs et al. (1973).

The N-S and NW directions play an effective part in the structural setting of Gabal Ineaji area (Youssef and Elkhodary 2013). Relative examination of both flanks of the Red Sea (Meshref et al. 1980) reveals that the NW (Red Sea) trend is considerably stronger through the Arabian Coast than the other directions along the Nubian part, with some minor trends such as E- W and NE directions. In brief, these tectonic trends suggest that a tectonic force oriented in the E- W direction in the Precambrian time was responsible for the development of the major N-S trend accompanied by related sets oriented in ENE, WNW, NE, NW, and E-W directions. By the Phanerozoic time, a stress orientation to the nearly along the NNW direction had led to the conjugate NW and NE trends, in addition to the rejuvenation of most of the older trends, that are closely related to the Red sea evolution.

According to the results discussed above, the applied filters can be a potent structural imaging technique when used in conjunction with surface structural mapping.

5. Conclusion

A critical step in using magnetic data to structurally analyse the subsurface is determining the boundaries of magnetic abnormalities. Edge detection approaches are becoming more widespread in geophysical exploration due to improvements in accuracy and noise reduction. So, different derivative techniques the tilt-angle, the TA of the total horizontal-gradient (TAGH), the TA of the TA gradient (TTDR), and Improved Logistic filter (IL) have been applied to the Gabal Ineaji aeromagnetic data to determine the boundaries of potential field sources. When the aeromagnetic data is interpreted, this can be utilised to produce highly accurate structural maps, especially when streaked by exposed geological structures. In light of this study, it appears clear that the tectonic trends in the research area follow the Precambrian tectonism including the N-S, NW, E-W, and NE trends. The N-S and NW directions play powerful role in the structural setting of the research area. Finally, it can be stated that the applied methods perform more accurate and precise application to aeromagnetic data and proves its suitability for the thorough disclosure of geologic structures.

Disclosure statement

No potential conflict of interest was reported by the authors.