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Basement Depth Estimation of Cheshire Basin in Northwest England By Power
Spectrum Analysis of Gravity Data Nadiah Hanim Shafie
Postgraduate Student, School of Environmental and Natural Resources Sciences,
Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
e-mail: [email protected]
Umar Hamzah Professor, School of Environmental and Natural Resources Sciences,
Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia e-mail: [email protected]
Abdul Rahim Samsudin Professor, School of Environmental and Natural Resources Sciences, Faculty of
Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
Azmi Ibrahim Postgraduate Student, School of Environmental and Natural Resources Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600
Bangi, Selangor, Malaysia e-mail: [email protected]
ABSTRACT Analysis of gravity data by power spectrum technique has been widely used for automatic estimation of bedrock depth. A total of 3000 gravity data representing an area within 53°7’-53°35’ N and 1°51’-3°3’ W in Cheshire Basin NW England were processed and analysed by Oasis Montaj computer software to produce Bouguer anomaly map. The power spectrum technique was then applied to the calculated Bouguer anomalies for depth estimation of the bedrock in the study area. Bouguer anomalies along 5 selected lines in E-W direction were used in the power spectrum analysis. In general Bouguer gravity values measured in the study area are within -8.8 to 17.0 mGal with positive anomalies concentrated in the west and east while gravity lows are dominant in the middle part. An abrupt change in the anomaly observed along a NE–SW line from -2.6 to 8 mGal especially in the east and west is associated with major faults. The negative Bouguer anomaly zone in the middle of the study area bordered by positive Bouguer values was interpreted as representing thick sediment deposited in a big graben between 2 major faults. Power spectrum curve slopes of lines A to E show depths ranging from 4.12 to 4.68 km representing deeper Bouguer anomaly sources and values ranging from 0.71 to 0.87 km for the shallower one. Deeper source depth of 4.41 km represent an average of basement rock depth underlying the thickest sediment while the average of shallow source depth of about 0.81 km represents depth of shallow basement rock underlying the thinnest sediment layer mostly in the far east and west of the study area.
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KEYWORDS: Gravity interpretation, Bouguer anomaly, power spectrum analysis and bedrock depth.
INTRODUCTION Gravity measurements are used in determining the earth gravity field at any point on the
surface of the earth. This non-destructive technique measures the density difference of the subsurface rock materials for subsurface geological interpretation especially in delineating basement rock underlying the oil-bearing sedimentary deposits in any oil exploration. Not only in determining the basement rock, gravity surveys are also used in detecting fault structures which also related to locating the oil potential zones. Determination of depth to each gravity source remains as the main topic of discussion by many researchers in this discipline. Amongst the techniques used in depth determination are 3D Euler deconvolution as reported by Tedla et al. (2011), upward continuation by Salimi & Motlagh (2012) and power spectrum analysis by Chamoli & Dimri (2010). The power spectrum analysis technique applied on gravity data was also widely used in subsurface automatic depth determination such as bedrock (Rina Dwi Indriana 2008). The analysis was only carried out in areas with gravity anomaly for average depth determination of the anomaly. Basically, Fast Fourier Transform technique is used to calculate the power spectrum radial logarithmic of the gridded magnetic data in estimating the average anomaly wave number along X and Y directions (Spector & Grant 1970). Radial squares for 2D survey decreases with depth increase of the source r with exponential factor (-2tr) where r is the wave number. Therefore, if the depth factor determines the shape of the power spectrum, log of the power spectrum is directly proportional to -2tr and the source depth is measured from the average of radial power spectrum log. The curve produces 5 depth values for each power spectrum (Connard et al.1983) referring to existence of several layers in the earth crust.
Reduced gravity data were obtained from the British Geological Society (BGS). About 3000 gravity data measured in Cheshire Basin of Northwest England covering an area of about 4000 km2 were used in this study as shown in Figure 1. Data were processed and analyzed by Oasis
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Figure 1: Location of the study area
Monta0j computer software. Bouguer anomaly map produced indicate the differences in anomalies associated with difference rock densities in the study area. Power spectrum technique was applied to the data for estimating the sediment thickness above the basement rock. Figure 2 shows the geology of Cheshire Basin consisting of Triassic mudstone, Perm-Triassic sandstone and Carboniferous limestone overlying the lower Paleozoic crystalline basement at depth of about 6000 m. (Abdoh et al. 1990). A report from Department of Energy and Climate Change (DECC) in 2010 believed that the Cheshire basin was formed during the regional displacement in Perm-Triassic trending NW-SE with major faults trending NE-SW. Chadwick & Evans (1995) proved that this half-graben was formed between fault systems of Wem-Red rocks which penetrated into the basement at depth of about 3500 m. A study by DECC (2010) also indicated that this half-graben shaped Cheshire basin is deeper towards the east and controlled by Red Rock fault systems trending NE-SW.
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Figure 2: Geological map of Cheshire Basin
The stratigraphy of Carboniferous and Perm-Trias basin is shown in Figure 3. In general, Cheshire basin is covered at the top by Jurassic marl. Mudstone and halite were deposited during upper Triassic and minor sandstone layer and siltstone were deposited during lower Triassic. Marl and sandstone of Sherwood sandstone, Cumbrian Coast and Appleby were deposited in upper Permian. An unconformity known as Variscan separates the Stephanian and Westphalian of Carboniferous in age.
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Figure 3: Stratigraphic column of Cheshire Basin (DECC, 2010)
POWER SPECTRUM THEORY Depths of sedimentary layers with different densities can be calculated by applying spectral
factorization technique (Spector & Grant, 1970; Karner & Watts, 1983). Based on Rina Dwi Indriana (2008), spectral analysis of gravity data anomaly in 1D along a line profile could be derived in Fourier equation as given below;
(1)
where is the total number of data in direction, is the data interval in direction , are 0, 1, 2, 3, …., and are the coefficients of cos and sine, is partial interval value of data while
when , and when .
When equation (1) is replaced by least squares technique, it will become
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(2) and
(3) where is the maximum index of gravity data point in the direction of , is and are the data points index in direction .
Equations (2) and (3) are combined to produce log of power spectrum, as given below
(4)
Equation (4) can also be written without log function as given below
(5)
The frequency of gravity anomaly field with different in rock density along a profile is given in equation below;
(6)
Where is the frequency response of the gravity anomaly field, is the frequency response of different density, is the limited depth while is the resulting angle frequency.
If the density value is picked randomly and not proportionate with the gravity value, the value for response frequency, , hence
(7)
It is known that is the angle frequency, is a constant and is the wave number (cycle/meter). Equation (7) can be rewritten as
(8)
The subsurface depth can be calculated based on difference of power spectrum as in equation (8) which can be arranged as given in equation (9) with depth value of positive indicating average depth along the gravity data profile.
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(9)
whereby and are the power spectrum, and are the wave numbers. Equation (9) gives the depth, which are obtained from difference of the power spectrum curve slopes divided by
. Basically, the power spectrum curves are divided into three components associated with gravity anomalies originated from deepest, shallow and noise sources.
METHODOLOGY Gravity method is normally used in getting subsurface geological information. Bouguer
anomaly map and power spectrum curves were derived from the gravity data of 80 50 km square areas within the Cheshire Basin, Northwest England. Figure 4 shows the gravity stations where about 3000 gravity readings were measured and reduced by the BGS following the International Gravity Standardisation Net 1971 and National Gravity Reference Net 1973. The data geographical positions are referred to Geodetic Reference System 1967. Grid interval of 1.8 × 1.8 km was used for gravity data selection and minimum curvature technique was used to produce the Bouguer gravity anomaly map. The Bouguer gravity anomaly is the resultant of local and residual field anomalies associated with general geology of the study area. The Bouguer anomaly is calculated after gridding by an equation as shown below;
(10)
whereby is the field gravity data, is the theoretical gravity value, zg ∂∂ is the vertical gradient of gravity data (0.3086 mgal/m), is the gravity constant (6.672×10-6 m2kg-1mgal), is the density of crustal material (2675 kg/m3 ) and finally is the height above the datum.
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Figure 4: Location of gravity data in study area
Power spectrum technique was applied to five east-west profiles. A total of 100 data points were selected in the process (Figure 5). Fast Fourier Transform (FFT) was applied for calculating the average gravity wave number along X and Y directions. The calculated power spectrum curves will be represented by Log (power) versus the wave number (1/K). The slopes of power spectrum curves normally determine types of gravity sources. Depth of basement rock will be estimated by calculating the slope gradient of the power spectrum curve and equation 9. Results obtained from power spectrum were then compared to seismic section, NW-SE2 located among the power spectrum profiles.
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Figure 5: The east-west line of power spectrum analysis and seismic section, NW-SE2 in
the Bouguer anomaly gravity map
RESULT AND DISCUSSION The difference in Bouguer anomaly values ranging from -8.8 to 17 mgal as shown in the map
is interpreted as due to difference in rock densities in the study area (Figure 6). The higher and positive anomalies are located in the eastern and western part of the study area while the gravity lows or negative are dominant in the central part. The negative gravity values are interpreted to represent the positions of thickest sediment while the positive anomalies indicate the thinning of the same sedimentary layers towards the east and west. Based on well data, the negative anomalies observed in the middle of the study area coincide with the low density sediment of Triassic Mercia mudstone and Sherwood sandstone groups overlying the sandstone and marl of Permian in age. The whole sediment layers overlain the granitic bedrock. The abrupt change in anomaly from -2.6 mGal to 8 mGal along a line trending NE-SW beginning in the middle towards the SE of the study area is associated with the presence of a major fault zone. Similar changes in gravity anomalies in the west are believed to be due to the presence of other faults. With the faults finding, the thick sediments are interpreted as deposited in the graben bordered by these big faults in the eastern and western part of the study area.
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Figure 6: Bouguer anomaly gravity map
Figure 7 shows the interpreted power spectrum curves of A until E along the E-W lines. Depths to the gravity sources are calculated from the curve slopes. Table 1 shows the estimated depths of deep and shallow sources. Average depth which produces gravity anomaly values of deep sources is 4.4 km while for shallow is about 0.8 km. The average of shallow depth referred to bedrock underlying the thin sediment in the eastern and western flanks while the average of deep source is related to deep seated bedrock underlying the thick thick sediment in the middle area. The result obtained is in agreement to what has been reported by Jackson and Mulholland (1993) where they estimated the maximum thickness of Permo-Triassic sediments in the region is about 4.38 km.
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Figure 7: Power spectrum analysis graph of profile (A), (B), (C), (D) and (E)
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Table 1: Depth estimation for thick and shallow unconformity bedrock
Profile Thick Unconformity Depth (km) Shallow Unconformity Depth (km) (A) 4.12 0.83 (B) 4.44 0.71 (C) 4.67 0.86 (D) 4.13 0.87 (E) 4.68 0.76
Average 4.41 0.81
Depths obtained from the power spectrum technique are compared with depths interpreted from seismic lines in the study area. The position of northwest-southeast seismic line NW-SE2 along 77.95 km used for the comparison is shown in Figure 8. Geological cross section traced from the seismic line indicates that maximum depth of the pre-Permian basement rock is about 3.9 km. Geological interpretation of profiles D and E show increasing depth of basement towards the south of the study area. The boundary of Mercia mudstone and Sherwood sandstone sitting on top of the Permian bedrock as well as the major faults positions are clearly visible in these seismic sections. The fault planes approximately dip towards NW-SE and NE-SW.
Figure 8: NW-SE seismic profile in Cheshire Basin
CONCLUSION In general, the power spectrum technique can be applied to gravity data for basement rock
depth estimation. Based on the study, the difference in gravity anomalies relates to difference in rock densities where gravity lows in the middle of the study area are associated with the thickest part of the sedimentary basin lying on top of basement rock. This basin is deposited in a graben bordered by major faults in the east and west of the study area. Power spectrum analysis shows that the average depth of deepest basement is approximately 4.41 km while the shallowest basement rock is towards the east and west with an average depth of about 0.81 km. These depths estimate are validated when compared with seismic sections of the same area.
REFERENCES 1. Abdoh, A., Cowan, D. and Pilkington M. (1990) “3D gravity inversion of the
Cheshire Basin,” Geophysical Prospecting, 38, 999-1011.
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2. Chadwick, R. A. and Evans, D. J. (1995) “The timing and direction of Permo-Triassic rifting in southern Britain,” In: Boldy, S. R. (ed) Permo-Triassic Rifting in the UK. Geological Society, London. Special Publications, 91, 161-192.
3. Chamoli, A. and Dimri, V. P. (2010) “Spectral analysis of gravity data of NW Himalaya,” EGM International Workshop. Italy.
4. Connard, G., Couch, R. and Gemperle, M. (1983) “Analysis of aeromagnetic measurements from the Cascade Range in central Oregon. Geophysics,” 24, 429-436.
5. David, E., Andy, C. and Nigel, S. (2014) “The Cheshire Basin: Hidden mineral resources,” Earthwise Issue of 07. Earthwise magazine. British Geological Survey.
6. DECC. (2010) “The Hydrocarbon Prospective of Britain’s Onshore Basins,” United Kingdom: UK Onshore, Department of Energy and Climate Change, British Geological Survey.
7. Jackson, D.I. and Mulholland, P. (1993) “Tectonic and stratigraphic aspects of the East Irish Sea Basin and adjacent areas: contrasts in their post-Carboniferous structural styles,” In Parker, J.R. (Ed.) Petroleum geology of northwest Europe: proceedings of the 4th Conference, 791-808.
8. Karner G. D. and Watts A. B. (1983) “Gravity Anomalies and Flexure of the Lithospere at Mountain Ranges,” J. geophys. Res, 88, 10449-10477.
9. Rina Dwi Indriana (2008) “Estimasi ketebalan sedimen dan kedalaman diskontinuitas Mohorovicic daerah Jawa Timur dengan analisis power sectrum dan data anomlai gravitasi,” Berkala Fisika, 11(2), 67-74.
10. Salimi, P. and Motlagh, A. T. (2012) “Mapping of the bedrock topography using gravity data: A case study in the South of Hormozgan Province, Iran,” Journal Geophysic & Remote Sensing, 2(1), 1-6.
11. Spector A. and Grant F.S. (1970) “Statistical models for interpreting aeromagnetic data,” Geophysics, 35, 293-302.
12. Tedla, G. E., van der Meijde, M., Nyblade, A. A. and van der Meer, F. D. (2011) “A crustal thickness map of Africa derived from global gravity field model using Euler deconvolution,” Geophysical Journal International, 187, 1-9.
13. Noer El Hidayah Ismail, Dr. Rosli Saad, Dr. Mokhtar Saidin, M.M. Nordiana, and A.H.A Teh Saufia: “The Gravity Data Response Towards Granitic and Sedimentary Bedrock- Bukit Bunuh Study for Meteorite Impact” Electronic Journal of Geotechnical Engineering, 2013 (18.G2) pp 1757-1765. Available at ejge.com.
14. Nadiah Hanim Shafie, Umar Hamzah, and Abdul Rahim Samsudin: “2D Gravity Inversion Technique in The Study of Cheshire Basin” Electronic Journal of Geotechnical Engineering, 2014 (19.S) pp 4381-4394. Available at ejge.com
15. Abd Rahim bin Harun and Abdul Rahim bin Samsudin: “Application of Gravity Survey for Geological Mapping and Cavity Detection: Malaysian Case Studies” Electronic Journal of Geotechnical Engineering, 2014 (19.S) pp 8247-8259. Available at ejge.com
16. Nabila Sulaiman, Dr. M.M. Nordiana, Dr. Rosli Saad, Dr. Muhammad Syukri, Hazrul Hisham, Umi Maslinda, and S.R. Ihsan: “Gravity Method Used in Identifying the
Vol. 21 [2016], Bund. 01 408
Northern Part of Seulimeum Fault, Krueng Raya, Aceh Besar, Indonesia” Electronic Journal of Geotechnical Engineering, 2015 (20.11) pp 4631-4637. Available at ejge.com
17. Rosli Saad, Mokhtar Saidin, Y .C. Kiu, Noer El Hidayah Ismail: “Bukit Bunuh Subsurface Study Using Gravity Method for Meteorite Impact Indicators” Electronic Journal of Geotechnical Engineering, 2012 (17.X) pp 3585-3589. Available at ejge.com
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