“…Since the target depth is the basement which is approximately undulating 5 km–6 km, the data is upward continued at 12 km to remove the short wavelength anomalies. Jacobsen (1987) demonstrated that if a potential field is upward continued to a certain height , then it is possible to focus on sources situated at a depth greater than (see also Lyngsie et al., 2006 ; Mammo 2010 ).…”
Section: Separation Of Regional and Residual Fieldmentioning
The study area is situated in the Southern Main Ethiopian Rift being bounded within the limit of 37
o
00″0′-38
o
50′00″E and 5
o
50′00″-7
o
00′00″N. It is well known that the complex geological structure of the Main Ethiopian Rift has attracted intense attention so far and numerous geophysical investigations have been performed using potential field data-sets in Central and Northern Main Ethiopian Rift with the exception of the Southern Main Ethiopian Rift which is poorly constrained. Analysis of Full Tensor Gravity anomalies helps in understanding of the nature of shallow subsurface structural features and has a paramount importance in building general understanding of subtle details about subsurface geology of the area.
Separation of regional and residual gravity field is performed using upward continuation filtering technique. The residual gravity anomaly caused by local structures and anomalous body delineated four sub-basins with low amplitude response which is in agreement with the vertical gravity gradient anomaly (G
zz
) and tilt derivative horizontal (TDX) that clearly outlined and characterize edges of the sub-basins. The sub-basins delineated are the northern and southern Abaya, Chamo and Gelana basins. The tilt angle method which is used to delineate major subsurface structures and determine the source depth results showed that the area was affected by different lineament trending NE-SW, N–S, NNE-SSW, NW-SE and E-W, directional analysis performed indicates that the dominant trend is in agreement with the regional fault orientations. The estimated depth to the top of the lineaments on average varies from 0.9 km to 3.1 km and it is relatively deeper in the basins compared to the surrounding areas giving clues to the amount of sediment infill.
“…Since the target depth is the basement which is approximately undulating 5 km–6 km, the data is upward continued at 12 km to remove the short wavelength anomalies. Jacobsen (1987) demonstrated that if a potential field is upward continued to a certain height , then it is possible to focus on sources situated at a depth greater than (see also Lyngsie et al., 2006 ; Mammo 2010 ).…”
Section: Separation Of Regional and Residual Fieldmentioning
The study area is situated in the Southern Main Ethiopian Rift being bounded within the limit of 37
o
00″0′-38
o
50′00″E and 5
o
50′00″-7
o
00′00″N. It is well known that the complex geological structure of the Main Ethiopian Rift has attracted intense attention so far and numerous geophysical investigations have been performed using potential field data-sets in Central and Northern Main Ethiopian Rift with the exception of the Southern Main Ethiopian Rift which is poorly constrained. Analysis of Full Tensor Gravity anomalies helps in understanding of the nature of shallow subsurface structural features and has a paramount importance in building general understanding of subtle details about subsurface geology of the area.
Separation of regional and residual gravity field is performed using upward continuation filtering technique. The residual gravity anomaly caused by local structures and anomalous body delineated four sub-basins with low amplitude response which is in agreement with the vertical gravity gradient anomaly (G
zz
) and tilt derivative horizontal (TDX) that clearly outlined and characterize edges of the sub-basins. The sub-basins delineated are the northern and southern Abaya, Chamo and Gelana basins. The tilt angle method which is used to delineate major subsurface structures and determine the source depth results showed that the area was affected by different lineament trending NE-SW, N–S, NNE-SSW, NW-SE and E-W, directional analysis performed indicates that the dominant trend is in agreement with the regional fault orientations. The estimated depth to the top of the lineaments on average varies from 0.9 km to 3.1 km and it is relatively deeper in the basins compared to the surrounding areas giving clues to the amount of sediment infill.
“…Validity of the estimated top of density contrasts ( Table 2 , column 4) could be guaranteed by comparing the gravity source depth results against the geologic stratigraphy ( Table 1 , Figure 6 ) produced based on well-log data ( Cherkose and Mizunaga, 2018 ). This source depth estimation method was used to estimate density horizons in northern part of Ethiopia ( Mammo, 2010 ), which lies close to our study area.…”
Section: Resultsmentioning
confidence: 99%
“… Layer Layer Geology Depth to top of the layer (m) Density Susceptibility References (Source for the parameters) 1 Pyroclastic and Lava flows (Silicic products) 0 2.477 0.00113425 Well-log data, Seismic study, Spectral analysis, Werner De-convolution 2 Lacustrine sediments 1000 2.34 0.000505 Well-log data, Seismic study and Blaikie et al. (2014) 3 Bofa Basalt, tuff and breccias 1500 2.81 0.0019558 Well-log data, Seismic study, Spectral analysis, Werner De-convolution ( Alemu, 1992 ) 4 Tertiary Ignimbrite 2500 2.58 0.0001825 Well-log data, Seismic study, Spectral analysis, Werner De-convolution ( Alemu, 1992 ) 5 Mesozoic sediment 2900 2.5 0.016 ( Mammo, 2010 ), Multi-Layer 3D gravity forward modeling 6 Crystalline basement 3000 2.74 0.0033 Gravity analysis result (depth), seismic velocity-density conversion ( Maguire et al., 2006 ) Figure 6 Conceptual model of six geological horizons identified from the well-log data, previous geological and geophysical studies and current geophysical data analysis. The color of layers representing stacked horizons where density contrasts occurs.…”
Section: Datasets and Methodologymentioning
confidence: 99%
“…These structures could be mapped using gravity and magnetic anomalies through the application of different mathematical filtering techniques. The subsurface relief for example could be mapped by defining density/susceptibility interfaces (source-depths) using filters like upward continuation ( Kebede et al, 2020 ), tilt depth ( Chen et al, 2016 ; Salem et al, 2007 ), 3D Euler Deconvolution ( Mammo, 2010 ; Keating and Pilkington, 2004 ), power spectral analysis ( Mammo, 2012 ), 2D Werner Deconvolution ( Mammo, 2012 ), 2D forward modeling ( Mickus et al, 2007 ), 3D structural inversion ( Tiberi et al, 2005 ), genetic algorithm ( Montesinos et al, 2016 ) and artificial neural network approach ( Alimoradi et al, 2011 ). The above mentioned source depth estimations methods are some of the various methods and are chosen differently by different researchers implying that there is no single approach.…”
Quantitative analysis of potential field data are made in the Ziway-Shala lakes basin over an area bounded by 38
°
00′ E - 39
°
30′ E and 7
°
00′ N - 8
°
30’ N. Most previous geophysical studies in the region under consideration focus on mapping the deep crustal structures and undulation of the Moho depth. Only few studies are targeted at mapping the shallow subsurface structures. The main focus of this paper is mapping geometries of the major lithological and structural units of the shallow subsurface using gravity and magnetic data. The ultimate objective of the research is to understand the hydrogeological dynamics of the region through mapping interfaces geometries. Automatic inversions, 2D joint forward modeling and 3D inversion are the major techniques employed. The 2D Werner de-convolution based on both gravity and magnetic data along the rift axis showed source depths tending to deepen northwards. Source depths estimates determined by Source Parameter Imaging also showed similar tendency. This is further strengthened by the joint 2D forward modeling of gravity and magnetic data which showed the top of the basement is sloping northwards. The result of the 3D gravity interface inversion agrees with results of the above mentioned depth estimation techniques. Finally, the gravity power spectral analysis resulted in two depth estimates, 1.53 km and 2.87 km which approximate the positions of two density interfaces. The shallow depth interface is thought to presumably delineate the low density Fluvio-lacustrine sediments including the rift floor volcanic units and crystalline basement. Our investigation results agree with the results of previous seismic studies which identified low velocity (“sediment-volcanic”) horizon in the rift floor with low resolution. The information obtained with regard to water balance of the basin, salinity level of the lakes and the conceptual hydrological flow model appears to reveal that the groundwater flow in the study region is controlled by subsurface structures, particularly, the mapped interface topographies.
“…This filter allows the magnetic data to be transformed as if it were acquired from a higher survey height. The depth of investigation is related to the upward continuation height by this equation (Mammo, 2010):…”
Ground magnetic surveys conducted in Suyoc, Mankayan, Benguet led to the delineation of features related to epithermal and porphyry copper targets in the area. High reduced to equator (RTE) anomalies are observed in areas with epithermal mineralization. The high RTE anomalies are attributed to hydrothermally altered rock with quartz veins. The previously recognized porphyry copper prospect in Palasaan (Mohong Hill) is characterized by low RTE anomaly surrounded by a high RTE anomaly. One explanation for this signature is the possible presence of a magnetic core and the destruction or absence of magnetite in the alteration haloes at the periphery of a porphyry prospect. Areas such as Mangga and Liten exhibit the same magnetic signatures. This distinct magnetic pattern coupled with observed alteration and mineralization signatures led to the interpretation of prospective blind porphyry deposits in these localities. Results of the study reveal the applicability of ground magnetic data in characterizing and extracting a potential area of mineralized zones at a regional scale.
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