GRADIOMETER

Field of the Invention

The present invention relates to a method of analysing data obtained using a gravity gradiometer, such as an airborne gravity gradiometer .

Background to the Invention

Airborne gravity gradiometers are used to provide gravity gradient data that can be analysed to obtain information concerning density variations in the ground, which may be caused by deposits such as iron ore deposits . Consequently, the use of gravity gradiometers is of interest for mining exploration . Airborne gravity gradiometers have highly sensitive detectors that are supported by complex mechanical support systems, which are used to attenuate external forces (for example caused by sudden movements of the aircraft) as much as possible . The analysis of data obtained with a gravity gradiometer is a challenging task. The shape or profile of the ground surface has a significant influence on the gravity gradient data due to the sharp density contrast between the air and the ground. Consequently, so called "terrain corrections" of the gravity gradient data are usually required in order to identify variations of the gravity gradient that are caused by deposits in the ground. Further, the gravity gradient strongly depends on the distance from the ground, but an aircraft does not always fly at exactly the same height. Consequently height corrections of the gravity gradient data may be required if the data is to be viewed as a grid image without "line effects" . Recently an alternative data processing method has been proposed. In this method a density distribution in the ground is modelled and corresponding gravity gradient data are then calculated. The calculated gravity gradient data and the measured gravity gradient data are compared and in an

iterative process the model is manipulated until the

calculated and measured data match. The modelled density distributions consequently is a representation of the density distribution in the ground and information concerning the presence of deposits can be derived without the need for separate terrain or height corrections.

US patent US 6615139 and PCT international application publication number WO 2004/003594 both disclose specific types of inversion modelling. PCT international application

publication number WO 2007/012895 discloses calculation of an equivalent source of the gravity gradient tensor data in the ground. The equivalent source is then used to calculate other components of the gravity gradient tensor. Further, prior publications Li,Y., "Processing gravity gradient data using an equivalent source technique", SEG Expanded Abstracts 20, 1466 (2001), doi : 10.1190/1.816382 and Dampney, C. "The Equivalent Source Technique", Geophysics, vol. 34, 1969, pg.30-53 also disclose related information.

The present invention provides further improvements. Summary of the Invention

The present invention provides in a first aspect a method of analysing gravity gradient data, the method comprising the steps of: providing the gravity gradient data for a survey area, the gravity gradient data being related to data obtained using the gravity gradiometer, the survey area having a ground surface that is profiled by features of the ground surface; providing a model of the survey area including the profiled surface; dividing at least a portion of the surface of the modelled survey area into a plurality of surface elements, each surface element defining a cell that extends to a depth below the surface and is positioned over a region to which a largely uniform density is assigned; and calculating ground densities for at least some of the cells and calculating corresponding gravity gradient data such that the calculated gravity gradient data are comparable with the provided gravity gradient data, whereby the calculated ground densities are indicative of a density distribution below the surface of the survey area.

The step of dividing at least a portion of the profiled surface of the survey area into a plurality of surface elements may be conducted such that the defined cells have identical depth from the surface and identical volume. The provided model of the survey area typically is a digital terrain elevation model.

The cells typically are located at the surface of the modelled survey area such that the surface elements form top surfaces of the cells. Alternatively, the cells may be located at a uniform depth below the surface elements and a layer to which a uniform density is assigned may be located over the cells.

Further, the step of dividing at least a portion of the profiled surface of the survey area into a plurality of surface elements may comprise assigning a uniform density distribution to at least some areas around the survey area.

Each cell typically has a flat top and bottom surfaces, but may alternatively also have a curved or sloped top and bottom surfaces so as to better approximate the profile of the profiled surface of the survey area.

The step of dividing at least a portion of the profiled surface of the survey area into a plurality of surface elements may comprise the use of a computer software routine to calculate a shape for the top and bottom surfaces of each cell such that the calculated shapes better approximate the profiled surface of the survey area rather than flat surface shapes .

The top and bottom surfaces of each cell typically are parallel to each other. The cells may have a substantially rectangular or sguare cross-sections shape in a plane along the profiled surface. Further, each cell may have a uniform density distribution.

The cells may have any suitable depth, but typically have a depth less than 500 meters, such as in the range of 10 meters to 200 meters, 15 meters to 60 meters or approximately 20 meters to 30 metres.

The step of providing the gravity gradient data for a survey area typically comprises collecting measured gravity gradient data and processing the collected gravity gradient data for example to improve the signal-to-noise ratio The step of calculating ground densities for at least some of the cells and calculating corresponding gravity gradient data typically is performed such that the calculated gravity gradient data are largely identical with the provided gravity gradient data. This step is typically performed such that the calculated gravity gradient data matches the provided gravity gradient data within a predetermined error margin.

The step of providing the gravity gradient data for the survey area typically comprises obtaining gravity gradient from measurements taken with an airborne gravity gradiometer that is flown over the survey area. For example, the gravity gradiometer may be flown along substantially parallel flight path sections over the survey area and the measurements may be taken at intervals such that gravity gradient data is provided for a plurality of positions along the flight path sections.

The step of calculating ground densities for at least some of the cells of the survey area typically is conducted such that the calculated densities of the cells are largely eguivalent to variations of the gravity gradient data taken at positions of the plane.

The invention will be more fully understood from the following description of specific embodiments of the invention. The description is provided with reference to the accompanying drawings . Brief Description of the Drawings

Figure 1 is a flow chart illustrating a method in accordance with an embodiment of the present invention;

Figure 2 is a representation of a model of a survey area in accordance with an embodiment of the present invention;

Figure 3 is a further representation of the ground area represented in Figure 2 showing the flight lines and tie lines ;

Figure 4 is a cross-section representation of a model of a survey area in accordance with an embodiment of the present invention ;

Figure 5 is a representation of an eguivalent value density map related to the model represented in Figure 4;

Figure 6 is a cross-sectional representation of a model of a survey area and surrounding ground area in accordance with an embodiment of the present invention;

Figures 7 and 8 show a map of gravity gradient data taken for the survey that is schematically indicated in Figure 6; and

Figures 9 shows a calculated equivalent density distribution corresponding to the map of gravity gradient data shown in Figure 8.

Description of Specific Embodiments of the Invention

Referring initially to Figure 1, a method of analysing gravity gradient data according to a specific embodiment of the present invention is now described. The method 10 includes the initial step 12 of providing the gravity gradient data by flying a gravity gradiometer over a survey area and collecting the gravity gradient data for the survey area. The survey area has a ground surface that is profiled by features of the ground surface. The collected gravity gradient data typically are processed further to improve the signal-to-noise ratio.

Where a cross-component gravity gradiometer is utilised, such as the gravity gradiometer of van Kann et al detailed in the patent applications WO2007038822 and WO2008061284 to measure gravity gradient tensor data, the gravity gradient data provided by step 12 of the method 10 are the actual measured gravity gradient data (VKa or VKc) for the actual measurement location .

Step 13 provides a model, such as a digital elevation map (DEM) of the survey area, which typically involves obtaining topographical information using laser detection and ranging (LiDAR) and/or related techniques such as shuttle radar topography mission (SRTM) or data obtained using satellites.

Step 14 divides the modelled surface of the survey area into a plurality of surface elements that each defines a cell having a depth. In this embodiment all cells define the same depth from the modelled surface. In this embodiment all cells have a square cross-sectional shape, but the cells may alternatively have any other suitable shape . The aircraft typically flies the gravity gradiometer along parallel flight lines and the surface elements may measure 25 meters by 25 meters for flight lines spaced 100 meters apart. A uniform density is assigned to the ground volume below the cells . Step 16 calculates ground densities, which hereafter referred to as "equivalent ground density values" for each cell. The equivalent ground density values are calculated such that cells having the calculated ground densities would result (or are comparable with) gravity gradient data that correspond to the gravity gradient data provided by step 12. Consequently, variations of the calculated densities of the cells are largely equivalent to variations of the provided gravity gradient data obtained using the gravity gradiometer. The process changes these density values iteratively until the calculated gravity gradient matches the observed gravity gradient .

In an iterative inversion process, an equivalent density is calculated for each cell and corresponding gravity gradient data are calculated. The calculation of the gravity gradient data takes into account locations at which the gravity gradiometer generated the gravity gradient data (step 12) such that the calculated and measured data can be compared for these locations. The equivalent densities of the cells are then varied and in an iterative process the gravity gradient data is calculated until the calculated and measured gravity gradient data are basically identical. Consequently, the method 10 effectively condenses any density anomaly below a surface element into a cell having a pre-determined depth from the surface. As the surface of each cell approximates a corresponding surface area of the ground and the gravity gradient data are calculated for the position of airborne gravity gradiometer at which the data was taken, the method 10 is largely independent from terrain effects and height variations of the aircraft over the ground. In contrast to conventional gravity gradient data processing methods separate terrain and height corrections are typically not necessary.

Figure 2 shows a model of a survey area 15, which is divided into a series of cells 35 by grid lines 40. Figure 3 shows within the survey area 15 of Figure 2 (including cells 35 and grid lines 40) a series of flight lines of an aircraft (not shown) and consisting of survey lines 45 and tie lines. The flight lines are the flight paths over which the gravity gradiometer measure the gravity gradiometer tensor data for the survey area 15. The tie lines are lines perpendicular to the flight lines 45. Measurements of the gravity gradiometer tensor taken on the tie lines 45 are used to obtain the gravity gradiometer tensor data on the flight lines 45 for monitoring drift of the gravity gradiometer instrument during the survey.

Figure 4 shows a cross-sectional view of the survey area 15. A valley floor 55 is shown on the left, an escarpment 60 in the middle and a plateau 65 on the right.

The survey area 15 is an identified area for the purpose of illustration of the current embodiment and consists of ground of uniform density except for anomaly 70. A series of vertical lines extend downwardly from the surface of the ground 20. These lines represent the vertical edges of the cells 35.

The depth from the surface of the ground 20 over which the equivalent density of the cell 35 is calculated is shown as depth 'd' and is uniform for all of the cells. Line 25 defines bottom surfaces of the cells 35 which are parallel to the surface of the ground 20 but displaced below the surface of the ground 20 by the depth 'd' . An average density for the survey area 15 is assigned the region below the cells 35. This average density can be estimated by performing a "homogeneous property" inversion on the entire survey, whereby all cells are constrained to have the same density. The value which gives a best fit to the observed data is designated the average density. The

equivalent density of the cells 35 consequently is the density that is required to produce the same gravity gradient tensor data as was measured by the gravity gradiometer during the aerial survey of survey area 15.

Figure 4 also shows a spherical geological anomaly 70 situated at 200 meters below the surface 20. Figure 5 shows the results of the method 10 detailed above. Most equivalent density surfaces 75 of the equivalent density map are at the same height as in the idealised survey of Figure 4. Most of the survey area has uniform density near equal to the average density of the survey area 15. The anomaly is apparent within the equivalent density surface 75 by an increase in equivalent density for cell 80. Cells around the cell 80 may also show an increase (not shown in Fig. 5)

Referring now to Figure 6, the method 10 is illustrated with reference to a further example. Figure 6 is a cross- sectional representation of a model of a ground 60 including a model of survey area 70. Independent measurements are used to obtain information concerning the profile of the ground surface in the survey area 70 such that the survey area 70 can be modeled. The model of the survey area 70 is divided into a plurality of equally sized surface elements 72, which in this example are square . Each surface element 72 defines a cell 74 that has a bottom surface 7 6 that is parallel to the surface element 72 . In this example the surface elements 72 and respective bottom surfaces 76 of each cell 74 are curved or have smoothed edges so as to better approximate the profile of the survey area 70 . The modeling of the ground 6 0 is performed using a computer software routine that is also arranged to modify the shape of the surface elements 72 and respective bottom surfaces 76 so as to better approximate the profile of the survey area 70 . It is to be appreciated that in alternative embodiments the cells 74 may have flat surface elements 72 and respective bottom surfaces 76 and may also be of any other suitable shape.

A homogenous density is assigned to an area below and around the surface area. The ground surface of an area in the proximity of the survey (such as within a few thousand metres) is also modeled, but a relatively coarse digital elevation map (DEM, also obtained using LiDAR measurements and/or other measurements such as STRM measurements, is used in contrast to the survey area 70 for which a higher resolution DEM is used. The surface of the ground further away from the survey area 70 is approximated by a flat surface.

Figure 7 shows a map of gravity gradient data (converted to Gzz) for the survey area 70 that is schematically indicated in Figure 6 . The shown raw data are subject to further

processing such as removal of artifacts and terrain

correction. Figure 8 shows the processed property gradient data .

The equivalent densities for the cells 74 were then

calculated. The result of the calculation is shown in Figure 9, which shows the equivalent density distributions of the cells 74 for the survey area 70. Density variations that give rise to the observed variation in gravity gradient signal are clearly visible in Figure 9 and can be used to identify the deposits in the ground. The distribution shown in Figure 9, which is a map of "apparent density" has many similarities with that of Figure 8 and can be regarded as alternative presentations of the survey results that could be interpreted in the same way.

Iterative inversion methods for calculating a density

distribution that corresponds to observed potential field data are known in the art and inversion methods of the same concept may also be employed for performing some steps of analysing gravity gradient data in accordance with

embodiments of the present invention. For further details regarding inversion methods reference is made to "The

Resolving Power of Gross Earth Data" George Backus, Freeman Gilbert DOI : 10.1111/ j .1365-246X .1968. tb00216. x Geophysical Journal of the Royal Astronomical Society, Volume 16, Issue 2, pages 169-205, October 196. It is to be appreciated that the present invention may take many different forms. For example, the gravity gradient data may be analysed with the purpose of identifying deposits other than ore deposits. Further, the cells may not be separated from each other by straight walls. The density calculated distribution within each cell may also not necessarily be uniform, but may for example include a transitional region in which the density changes gradually. In addition, the cells may not necessarily be located at the surface of the modelled survey area, but may instead be positioned below a layer having a uniform thickness. Reference that is being made to prior publications does not constitute an admission that these publications are part of the common general knowledge of a skilled person in Australia or any other country.