Advanced Processing and Interpretation

Advanced Processing and Interpretation of Gravity and Magnetic Data

Prepared by G E T E C H

GETECH Kitson House Elmete Elmete Hall Leeds LS8 2LJ UK Phone +44 113 322 2200 Fax +44 113 273 5236 E-mail [email protected]

www.getech.com

Processing and Interpretation of G&M Data

This short document is intended to provide pro vide background theory and a nd methodology of the uses of gravity and magnetic data in exploration. Section 1 discusses the interpretation process itself, outlining the importance of qualitative

interpretation and the complementary roles that gravity and magnetic data offer. Section 2 provides examples of the various types of enhancements (or transforms) applied to

gravity and magnetic data to highlight particular characteristics or features to aid qualitative interpretation. Section 3 describes additional advanced methods of quantitative processing in support of

interpretation that can be applied to gravity and magnetic data, including 3D gravity inversion, depth to source estimation and 2D modelling.

advanced_processing_and_interpretation.doc

© GETECH Group plc 2007 -

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1.

The Interpretation Process

As with all geophysical interpretation, the analysis of gravity and magnetic data has two distinct aspects: qualitative and quantitative. The qualitative process is largely map-based and dominates the early stages of a study. The

resultant preliminary structural element map is the cornerstone of the interpretation. Qualitative interpretation involves recognition of: •

the nature of discrete anomalous bodies including intrusions, faults and lenticular intrasedimentary bodies - often aided by reference to characteristic magnetic response charts and perhaps performing simple test models

•

disruptive cross-cutting features such as strike-slip faults

•

effects of mutual interference

•

relative ages of intersecting faults

•

structural styles

•

unifying tectonic features/events that integrate seemingly unrelated interpreted features

The most important element in this preliminary qualitative stage surprisingly is not the interpretation of anomalous bodies themselves (that follows later) but rather the network of discontinuities e.g. lines of truncation and strike-slip faults that serve to compartmentalise and delimit discrete anomalies that at first sight may appear as a confused pattern of unravellable anomalies. Strike-slip faults/shear zones, small and large-scale, are commonplace particularly within intra-continental situations where crust is old, bearing witness to countless fault reactivations. They provide the principal means by which major structures are truncated and crustal stress is decoupled (fully or partially) from one crustal block to another. The quantitative process. Putting lines on maps during the qualitative process is the start of

quantitative phase. Refinement of these locations begins with the determination of z i.e. depth values. For example, depth estimates to tops of anomalous magnetic bodies are generated by a number of means including: slope measurement methods, analytic methods such as Euler and Werner. Gravity and magnetic modelling (ideally seismically controlled) including forward and inversion approaches contribute significantly to location in x, y and z. Accurate results of all these rely upon sensible qualitative recognition of body types. advanced_processing_and_interpretation.doc


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Processing and Interpretation of G&M Data Interplay of the qualitative and the quantitative soon develops, particularly as computer modelling proceeds. Not infrequently, the results of modelling alert the interpreter to unexpected geological scenarios that necessitate a qualitative re-appraisal of certain anomalies, perhaps for example even alluding to a change in the interpreted structural style for an entire study area. The likelihood of this happening depends on whether the study zone lies within an under-explored frontier area or is mature. The greater the seismic control within the modelling process, the less ambiguous the model will be. Once modelling is complete, the qualitative process reasserts itself on the basis of the mapped gravity and magnetic data alone, by the interpolation and extrapolation of modelled features into regions that do not benefit from modelling / seismic / well control. In this way, body geometries can be more accurately defined on a map-wide basis, more precise xyz location of bodies determined, and, interfering/overprinted bodies better recognised for what they are. Depth to basement contour maps can also be generated, conditioning the contours manually to the interpreted structural framework. 1.1

The supporting roles of gravity and magnetic data

Interpretation of magnetic data is theoretically more complex than the corresponding gravity data due to: •

the dipolar nature of the magnetic field, in contrast with the simpler monopolar gravity field

•

the latitude/longitude dependent nature of the induced magnetic response for a given body due to the variability of the geomagnetic field over the Earth’s surface

•

However, in practice it is often simpler than that of gravity due to the smaller number of contributory sources. Often, though not always, there is just one source - the magnetic crystalline basement. The gravity response is, by contrast, generated by the entire geologic section.

In the case of intrasedimentary bodies, the dipolar nature of the magnetic response is particularly diagnostic of the disposition (e.g. dip) of the source. It is for this reason that it is important for the interpreter to be familiar with a wide range of induced magnetic responses produced by simple geological bodies at the geomagnetic field inclination for the region. Seeking mutual consistency



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Processing and Interpretation of G&M Data of both gravity and magnetic interpretations ensures that ambiguities within the interpretation are minimized.

Characteristic geomagnetically induced magnetic responses for regions close to the geomagnetic equator.

Modelling of potential field data is an important aspect of the interpretation, and is often performed using a “bottom-up / outside-in / magnetics-first” approach. This ensures that deep magnetic basement sources, which impact regionally on the study area, are understood first, before attention is focused on the detail within the area of interest. The interpreter should always be aware of the potential confusion generated by overprinting of similar wavelength responses caused by: (i) deep crustal features, (ii) laterally distal crustal features, and, (iii) broad centrally located shallow crustal features. Resolving this confusion is invariably achieved by seeking consistency between the modelled gravity and magnetic data, while adhering to sensible geological principles and experience. The following expands on this process. A “magnetics first” approach recognises that the sedimentary section often possesses little significant magnetic susceptibility. The major proportion of magnetic signal is generated at crystalline (igneous or metamorphic) basement level. This is useful, because unlike gravity where the entire section contributes to the observed field, all but the shortest wavelength magnetic responses can be ascribed to the underlying basement. If shallow intra-sedimentary magnetic sources do exist, these are usually of short wavelength and sufficiently discrete to be recognised for what they are. The modelling of the magnetic data is particularly important for extending interpretation below the effective level of seismic penetration. Once the magnetic data have advanced_processing_and_interpretation.doc


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Processing and Interpretation of G&M Data been interpreted in this way, consistency is then sought with the longer wavelength gravity features. Any remaining long wavelength gravity anomalies may be more properly ascribed to broad shallow sources, rather than to deep sources. 1.2

Magnetic response of N-S orientated features located at the Equator

Interpretation of magnetic anomalies close to the magnetic equator is complicated for several reasons: •

Ambient field is horizontal

•

Ambient field is weak (~35,000 nT compared to up to 70,000 nT in higher latitudes)

•

Structures striking N-S are difficult to identify

Magnetic anomalies are generated when the flux density cuts the boundary of a structure. If the structure strikes parallel with the field then in Equatorial areas the flux stays within the structure and no anomaly is generated.

Induced magnetic response of a 2D rifted basin striking W-E and N-S at or near the geomagnetic equator. The sediments are assumed to have low susceptibility and the basement high susceptibility. Small arrows show the induced magnetisation vector directions.



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Processing and Interpretation of G&M Data A similar effect is seen when a magnetic field is reduced to the equator (RTE) instead of to the pole (RTP), where N-S structures are difficult or impossible to identify in RTE maps. This is shown below. In this example the TMI has Inclination = –62 and Declination = –12, thereby allowing both stable RTP and RTE anomalies to be derived. In magnetic equatorial regions where Inclination is less than say 15 then RTP is generally unstable and can not be derived.

Since faults and many structures have irregular shapes, albeit in regional form they may be 2D, then parts of the structure will be magnetically imaged where the flux cuts the structural interface generating dipole shape anomalies. Thus N-S striking structures may be identified by a ‘string of pearls’ i.e. line of magnetic dipole anomalies. The Analytic Signal is the best derivative to recover the N-S contacts in equatorial regions as is shown by the diagram below.



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2.

Enhancements and Transformations of Potential Field Data

The area used in this series of images is a region of Poland traversed (NW-SE) by the Teisseyre Tornquist Zone which divides the shallower crystalline basement of the East European platform to the NE, from the deeper West European platform to the SW. The thick Palaeozoic and Mesozoic sedimentary cover of central Poland has undergone significant deformation (folding and faulting) during the Caledonian, Variscan and Alpine orogenic phases. This has generated a set of clear magnetic and gravity responses from basement and the sedimentary section that allow similarities and differences to be clearly observed in the images generated. The gravity images are on the left hand side of the page and the magnetic images are on the right. All the techniques described in this section were generated using GETECH’s own ‘GETgrid’ software package. The software utilises FFT and spatial domain operators and has a host of additional features (e.g. boolean logic, vector overlays, grid arithmetic).



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Reduction to the Pole (RTP)

This technique transforms induced magnetic responses to those that would arise were the sources placed at the magnetic pole (vertical field). This simplifies the interpretation because for sub-vertical prisms or sub-vertical contacts (including faults), it transforms their asymmetric responses to simpler symmetric and anti-symmetric forms. The symmetric ‘highs’ are directly centred on the body, while the maximum gradient of the anti-symmetric dipolar anomalies coincides exactly with the body edge. Pole reduction is difficult at low magnetic latitudes, since N-S bodies have no detectable induced magnetic anomaly at zero geomagnetic inclination. Pole reduction is not a valid technique where there are appreciable remanence effects. Pseudo-Gravity and Pseudo-Magnetic Fields

A magnetic grid may be transformed into a grid of pseudo-gravity. The process requires pole reduction, but adds a further procedure which converts the essentially dipolar nature of a magnetic field to its equivalent monopolar form. The result, with suitable scaling, is comparable with the gravity map. It shows the gravity map that would have been observed if density were proportional to magnetisation (or susceptibility). Comparison of gravity and pseudo-gravity maps can reveal a good deal about the local geology. Where anomalies coincide, the source of the gravity and magnetic disturbances is likely to be the same geological structure. (see Automatic Lineament Tracing). Similarly, a gravity grid can be transformed into a pseudo-magnetic grid, although this is a less common practice.



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Processing and Interpretation of G&M Data Traditional Filtering

Filtering is a way of separating signals of different wavelength to isolate and hence enhance anomalous features with a certain wavelength. A rule of thumb is that the wavelength of an anomaly divided by three or four is approximately equal to the depth at which the body producing the anomaly is buried. Thus filtering can be used to enhance anomalies produced by features in a given depth range.

Traditional filtering can be either low pass (Regional) or high pass (Residual). Thus the technique is sometimes referred to as Regional-Residual Separation. Bandpass filtering isolates wavelengths between user-defined upper and lower cut-off limits.



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Pseudo-depth Slicing

A potential field grid may be considered to represent a series of components of different wavelength and direction. The logarithm of the power of the signal at each wavelength can be plotted against wavelength, regardless of direction, to produce a power spectrum. The power spectrum is often observed to be broken up into a series of straight line segments. Each line segment represents the cumulative response of a discrete ensemble of sources at a given depth. The depth is directly proportional to the slope of the line segment. Filtering such that the power spectrum is a single straight line can thus enhance the effects from sources at any chosen depth at the expense of effects from deeper or shallower sources. It is a data-adaptive process involving spectral shaping. As such, it performs significantly better than arbitrary traditional filtering techniques described above. When gravity and magnetic depth slices coincide it is a good indication that the causative bodies are one and the same.



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Processing and Interpretation of G&M Data First Vertical Derivative

VDR = −

∂Α ∂ z

This enhancement sharpens up anomalies over bodies and tends to reduce anomaly complexity, allowing a clearer imaging of the causative structures. The transformation can be noisy since it will amplify short wavelength noise. In our example it clearly delineates areas of different data resolution in the magnetic grid.



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Processing and Interpretation of G&M Data 2

Total Horizontal Derivative

⎛ ∂Α ⎞ ⎛ ∂Α ⎞ HDR = ⎜ ⎟⎟ ⎟ + ⎜⎜ ∂ x ∂ y ⎝ ⎠ ⎝ ⎠

2

This enhancement is also designed to look at fault and contact features. Maxima in the mapped enhancement indicate source edges. It is complementary to the filtered and first vertical derivative enhancements above. It usually produces a more exact location for faults than the first vertical derivative, but for magnetic data it must be used in conjunction with the other transformations e.g. reduction to pole (RTP) or pseudo-gravity. Specific directional horizontal derivatives can also be generated to highlight features with known strikes. This technique can be applied to pseudo-depth slices to image structure at different depths.



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Processing and Interpretation of G&M Data ∂2Α 2VD = ∂Ζ 2

Second Vertical Derivative

The second vertical derivative serves much the same purpose as ‘residual’ filtering in gravity and magnetic maps, in that it emphasises the expressions of local features, and removes the effects of large anomalies or regional influences. The principal usefulness of this enhancement is that the zero value for gravity data in particular closely follows sub-vertical edges of intrabasement blocks, or the edges of suprabasement disturbances or faults. As with other derivative displays, it is particularly helpful in the processing stage where it can be used to highlight line noise or mislevelling.

2

Analytic Signal (Total Gradient)

2

⎛ ∂Α ⎞ ⎛ ∂Α ⎞ ⎛ ∂Α ⎞ AS = ⎜ ⎟⎟ + ⎜ ⎟ + ⎜⎜ ⎟ x y ∂ ∂ ⎝ ⎠ ⎝ ⎠ ⎝ ∂ z ⎠

2

The analytic signal, although often more discontinuous than the simple horizontal gradient, has the property that it generates a maximum directly over discrete bodies as well as their edges. The width of a maximum, or ridge, is an indicator of depth of the contact, as long as the signal arising from a single contact can be resolved. This transformation is often useful at low magnetic latitudes because of the inherent problems with RTP, (at such low latitudes).



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Automatic Lineament Tracing

The automatic lineament detection algorithm requires the data to have been processed (or transformed) such that the edge of a causative body is located beneath a maximum in the grid. Several transforms satisfy this requirement e.g. horizontal derivative of gravity (or of pseudogravity, for magnetic data) and also analytic signal. The results help to quantify the different gravity and magnetic responses of structures located in the shallow and deep sedimentary sections and in the basement.

A significance factor N, ranging in value from 0 to 4, is assigned to each grid cell depending on the relation to its neighbours. N=1 might represent a point on a spur, N=2 and N=3 a point on a ridge and N=4 a point on a peak. The values of N are colour coded and displayed as a grid. These lineament grids can then be displayed on top of any other grid.



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Grid Display

Aside from the data transformations applied to grids it is often beneficial to display grids themselves in a variety of ways. This ensures that the maximum amount of information contained in the transforms can be utilised in the interpretation phase. The following three grids of gravity data show the same data displayed in grey-scale shaded relief, colour shaded relief and in a dipazimuth display. Vector data (station locations, flight lines, coastlines etc.) can be added as an overlay. The dip-azimuth display highlights slope changes in all directions and is therefore useful for picking out multiple trends in the data simultaneously.



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Processing and Interpretation of G&M Data Tilt Derivative

−1 ⎡ VDR ⎤ TDR = tan ⎢ ⎣ THDR ⎥⎦

The Tilt derivative (TDR) is similar to the local phase, but uses the absolute value of the horizontal derivative in the denominator Due to the nature of the arctan trigonometric function, all amplitudes are restricted to values between + π /2 and - π /2 (+90and -90) regardless of the amplitudes of VDR or THDR. This fact makes this relationship function like an Automatic Gain Control (AGC) filter and tends to equalise the amplitude output of TMI anomalies across a grid or along a profile. The Tilt derivatives vary markedly with inclination but for inclinations of 0and 90, its zero crossing is located close to the edges of the model structures. The Total Horizontal derivative of the TDR is independent of inclination, similar to the Analytic Signal, but is sharper, generating better defined maxima centred over the body edges, which persist to narrower features before coalescing into a single peak.



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3.

Quantitative Interpretation Techniques

The enhancement techniques described in Section 2 generally help to estimate the 2D spatial location of structures and their edges but do not generally provide estimates of the depth. The exceptions are the pseudo-depth slicing and the analytic signal. This section describes semiautomated methods of depth estimation (3D Euler, Werner and SPI) and forward modelling of 2D and 3D data. These are routinely used to model sub-surface structures constrained by seismic and well data. Euler deconvolution

GETECH has developed several in-house 3D anomaly interpretation packages for application to total magnetic intensity (TMI) data, which employ Euler's homogeneity equation to identify location, depth and nature of any sources present (Reid et al., 1990):

(x − x 0 )

∂T ∂T ∂T + (y − y 0 ) + (z − z 0 ) = N(B − T ) ∂x ∂y ∂z

where: (x0, y0, z0): the position of a source whose total field T is detected at any point (x,y,z) B: the background value of the total field N: the degree of homogeneity, interpreted physically as the attenuation rate with distance, and geophysically as a structural index (SI): Geological Model Number of Infinite dimensions Magnetic SI Gravity SI

Sphere

0

3

2

Pipe

1 (Z)

2

1

Horizontal cylinder 1 (X or Y)

2

1

Dyke

2 (Z and X or Y)

1

0

Sill

2 (X and Y)

1

0

Contact

3 (X, Y and Z)

0

NA



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Processing and Interpretation of G&M Data Specification of the structural index N permits the equation to be solved for source position for a specific source geometry within a given data window. This window is progressively "moved" across the magnetic data grid, and solutions are generated within each. The process is repeated for various window sizes and structural indices, and the optimum parameters for the data are determined by clustering of output depth solutions and comparison with other available information. Solutions are generated for every window location, but for display purposes it is sensible to apply any of several "solution selector" methods, which eliminate poorly defined solutions. Numerous authors have proposed such methods. A simple criteria is the value of standard deviation of the calculated depth for each solution, expressed as a percentage of the depth value - solutions with a standard deviation above a given threshold are rejected. More sophisticated techniques include calculating multiple solutions in each window using both the observed field and it’s Hilbert transforms (Nabighian and Hansen, 2001), or analysing the eigenvalues and eigenvectors of the Euler equations (Mushayandebvu et al, 2004). Refined solution sets for different window sizes and SI values can be more easily interpreted in terms of subsurface structure.

a

b

c

(a) Model topography, (b) forward modelled TMI field and (c) Euler solutions



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Processing and Interpretation of G&M Data The Euler deconvolution results for a given study area typically comprise several hundred thousand solutions with a large spread of depths. Williams (2004) showed that for any given source structure, the individual depth estimates derived from methods such as Euler deconvolution often exhibit considerable scatter, but that the mean depths for a cluster of solutions provide a much more reliable estimate of the source depth. Tests performed on a realistic 3D model show that if the mean values of coherent clusters of Euler solutions are 1

calculated, these show a similar relationship to the “real” depths as the total Euler solutions but with a tighter spread and closer to a 1:1 correlation (see figures below). This process greatly reduces the number of solutions enabling them to be more easily used in constructing a final depth to basement map.

1

the model was created by taking a real topography dataset for an area with numerous exposed fault scarps of

varying size and orientation and then scaling these data to provide a “buried topography” analogue for the faulted basement surface of a sedimentary basin.



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Buried topography test. Plot of 2D constrained Euler solution depth versus model depth at the same x,y location for homogeneous susceptibility basement model (from Williams, 2004).

Buried topography test. (a) Manually defined polygons (shown in grey) to isolate clusters of 2D constrained Euler solutions (blue dots) for analysis of averaged source parameters. (b) Plot of mean solution depths, plotted at the mean solution x,y location, of the solution clusters defined in (a), with contours showing the basement depth in the same colour scale (contour interval 200 m). (c) Mean 2D constrained Euler solution depth versus model depth (from Williams, 2004)



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Processing and Interpretation of G&M Data Spectral Depth Method

The spectral depth method is based on the principle that a magnetic field measured at the surface can therefore be considered the integral of magnetic signatures from all depths. The power spectrum of the surface field can be used to identify average depths of source ensembles (Spector and Grant, 1970). This same technique can be used to attempt identification of the characteristic depth of the magnetic basement, on a moving data window basis, merely by selecting the steepest and therefore deepest straight-line segment of the power spectrum, assuming that this part of the spectrum is sourced consistently by basement surface magnetic contrasts. A depth solution is calculated for the power spectrum derived from each grid sub-set, and is located at the centre of the window. Overlapping the windows creates a regular, comprehensive set of depth estimates. This approach can be automated, with the limitation however that the least squares best-fit straight line segment is always calculated over the same points of the power spectrum, which if performed manually would not necessarily be the case. It should be noted that not all analytical depth methods will produce useful results for every study due to the inapplicability of theoretical assumptions associated with the method and certain configurations of magnetic sources (often related to source width/depth ratios and disparate source geometries in close proximity). For small windows of data the limited number of grid nodes often leads to power spectra becoming jagged at the start or end. This is the reason for omitting the first point in the automated determination of the deepest straight-line segment of the power spectra. To define a straight line on the basis of a set of points (in a least squares statistical manner) a minimum of 2 points is required, but more are preferable. Increasing the number of points used to define the straight line segment may conflict with obtaining the deepest characteristic source depths, as the slope of the power spectrum reduces for increasing wavenumber / decreasing wavelength. Depth results are generated for the entire dataset using different wavenumber ranges and window sizes.



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a

b

Radially averaged power spectrum for a subset of the magnetic grid. Colour coded basement depth estimates derived from slope of linear sections in power spectrum for each subset.

The Tilt Depth method

The zero contour of the Tilt angle locates source edges (for vertical contacts). Salem et al . (in press) show that the half-distance between the +/-45 degree contours provides an estimate to source depth. The tilt angle is normalized to within +/-90 degrees, so can be advantageous in highlighting low amplitude features, although the method is of inherently lower resolution than the local wavenumber, for example, since it relies on plotting zones derived from a first order derivative. The depths are most reliable where the +/-45 degree contour corridor is linear with consistent width. Depths are less reliable where the corridor is irregular, suggesting complex sources interference between neighbouring anomalies.



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Processing and Interpretation of G&M Data Local Wavenumber or Source Parameter Imaging (SPI ).

Source Parameter Imaging or SPI™ (Thurston and Smith, 1997, Fairhead et al, 2004) is a profile or grid-based method for estimating magnetic source depths, and for some source geometries the dip and susceptibility contrast. The method utilises the relationship between source depth and the local wavenumber (k ) of the observed field, which can be calculated for any point within a grid of data via horizontal and vertical gradients. At peaks in the local wavenumber grid, the source depth is equal to n/ k , where n depends on the assumed source geometry (analogous to the structural index in Euler deconvolution) - for example n=1 for a contact, n=2 for a dyke. Peaks in the wavenumber grid are identified using a peak tracking algorithm (for example Blakely and Simpson, 1986) and valid depth estimates isolated. Advantages of the SPI method over Euler deconvolution or spectral depths are that no moving data window is involved and the computation time is relatively short. On the other hand, there is no way to assess the reliability of each depth estimate, and the need to calculate second order derivatives of the observed data means noise can be a problem. Errors due to noise can be reduced by careful filtering of the data before depths are calculated. Phillips et al (2006) proposed a method of analysing the local wavenumber to derive estimates of source depth and structural index. This method looks at the peaks of the in terms of both the amplitude and curvature, and a depth estimate is generated that is independent of structural index. The structural index can in fact be estimated from the data, and the estimate of structural index can provide a means of discriminating between reliable and spurious depth estimates.

a

b

(a) synthetic TMI field and (b) Local wavenumber depth estimates



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Processing and Interpretation of G&M Data 3D Gravity Stripping and Inversion

A grid of gravity can be inverted to yield a grid of the depth variation of a significant density boundary, commonly the base of a sedimentary basin. The technique involves stripping off the gravity effects of known layers, seismically determined, within the sub-surface before inverting for the structure of a deep density boundary. For example, the structure and densities of shallow sedimentary horizons in a basin may be well known from seismic and well data, but the basement may not be adequately imaged from the seismic data due to the presence of salt or volcanics. The gravity effect of each of the known sedimentary layers is calculated from forward modelling and subtracted from the observed gravity anomaly. The residual anomaly is then inverted to provide the depth to the top of the basement.

2D Profile Modelling

GETECH uses the GM-SYS modelling software from Northwest Geophysical Associates, Inc. (NGA). It is an interactive forward modelling program which calculates the gravity and magnetic response from a user defined hypothetical geologic model. Any differences between the model response and the observed gravity and/or magnetic field are reduced by refining the model structure or properties (e.g. density or susceptibility of model components).

It should be noted that gravity and magnetic models are non unique, i.e. many earth models can produce the same gravity and/or magnetic response, and similarly, several geological lithologies may be interpreted from a given model block’s density and susceptibility properties. It is therefore important to use as many independent sources of information as possible to help constrain the model, e.g. seismic structural horizons and density logs from wells located near the profile. Such control may be included in the GM-SYS model as image backgrounds (e.g. depth converted seismic lines) or as symbols (e.g. wells with lithology tops annotated with depth). advanced_processing_and_interpretation.doc


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Processing and Interpretation of G&M Data 2D modelling assumes two dimensionality of every model component block, i.e. the model may change with depth (Z direction) and along the profile (X direction, perpendicular to strike), as defined by the program user, but does not change along strike (Y direction). A 2D model may be visualised as a number of tabular prisms with their axes perpendicular to the profile with blocks and surfaces assumed to extend to infinity in the strike direction. These restrictions inherently assume that the modelled profiles do not change direction along the model extent. The models created by GM-SYS extend to depths of 50 km by default, and therefore the whole crustal structure can be modelled.

This is advantageous as the observed gravity field is

contributed to by the entire geologic section. To accurately model the upper crustal, residual components requires accurate definition of the regional, lower crustal density variations, such as Moho relief. In some cases, the positive regional gravity response from extended crust, giving rise to an elevated Moho, can be relatively well constrained from the gravity profile itself. An example is provided overleaf where the gravity profile shows negative perturbations (due to the basin sediments) from a regional, long wavelength gravity high. Alternatively, two shorter wavelength highs may be observed on either side of the basinal gravity low from which the regional may also be interpolated:



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The difficulty arises when the residual gravity lows due to the sedimentary fill almost cancel the gravity high due to crustal thinning and an elevated Moho (i.e. the basin is isostatically compensated), or if “ramp flat detachment” geometry prevails and the regional gravity high is not laterally coincident with the basinal gravity low. In these cases as much additional information as possible is used to constrain the model, such as well data or simultaneous magnetic modelling.

Werner Deconvolution

Werner deconvolution is a profile-based interactive technique used to analyse the depth to and horizontal position of magnetic source bodies, and the related parameters of dip and susceptibility. It is a rigorous, iterative, two-dimensional inversion technique that takes into account interference from adjoining anomalies. Analysis of the total magnetic intensity data yields these parameters for thin, sheet-like bodies such as dikes, sills, intruded fault zones, and basement plates of minor relief compared to the source-sensor separation distance. Applied to the horizontal gradient data Werner Deconvolution yields similar parameters for geologic interface features such as dipping contacts, edges of prismatic bodies, major faults, and slope changes of the basement surface.



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References BLAKELEY, R.J. AND SIMPSON, R.W, 1986. Approximating edges of source bodies from magnetic or gravity anomalies. Geophysics, v51, No 7, pp 1494–1498. FAIRHEAD, J.D., WILLIAMS, S.E. AND FLANAGAN, G., 2004. Testing Magnetic Local Wavenumber Depth Estimation Methods using a Complex 3D Test Model. SEG Annual Meeting, Denver, Extended Abstract. MUSHAYANDEBVU, M.F., LESUR, V., REID, A.B. AND FAIRHEAD, J.D., 2004. Grid Euler deconvolution with constraints for 2D structures. Geophysics, v69, pp 489-496 NABIGHIAN, M.N. AND HANSEN, R.O., 2001. Unification of Euler and Werner deconvolution in three dimensions via the generalized Hilbert transform. Geophysics, v66, No 6, pp 1805-1810. PHILLIPS, J.D., HANSEN, R.O., AND BLAKELY, R.J., 2006. The Use of Curvature in Potential-Field Interpretation. ASEG2006, expanded abstracts. REID, A.B., ALLSOP, J.M., GRANSER, H., MILLET, A.J., AND SOMERTON, I.W., 1990. Magnetic interpretation in three dimensions using Euler deconvolution. Geophysics v55 pp 80-91. SALEM, A., WILLIAMS, S., FAIRHEAD, J.D., RAVAT, D., AND SMITH, R., in press. Tilt-Depth method: A simple depth estimation method using first order magnetic derivatives. Submitted to The Leading Edge. SPECTOR, A. AND GRANT, F.S., 1970. Statistical Models for Interpreting Aeromagnetic data. Geophysics, v35, No 2, pp 293-302. THURSTON, J.B., AND SMITH, R.S., 1997. Automatic conversion of magnetic data to depth, dip, and susceptibility contrast using the SPI (TM) method. Geophysics, v62, No 3, pp 807 -813. WILLIAMS, S.E., 2004. Extended Euler deconvolution and interpretation of potential field data from BoHai Bay, China. PhD Thesis (unpublished), University of Leeds.



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Advanced Processing and Interpretation

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