Example: Cloncurry region, Queensland
The Cloncurry region, located in western Queensland, Australia, hosts the Mt Isa lead-zinc, Cloncurry gold and Ernest Henry iron oxide copper-gold (IOCG) deposits, among others. The region has good-quality magnetic data. These data were processed by Fathom Geophysics.
Presented below are some of the results of this data-processing. Standard filtering results appear first, followed by some of the results of Fathom Geophysics' advanced data-analysis and imaging.
Standard filtering results presented include: reduction to the pole, first vertical derivative, tilt angle, horizontal gradient magnitude, analytic signal, first vertical derivative minus horizontal gradient magnitude, pseudogravity, residuals, and automatic gain control.
The advanced imaging results presented include various ternary diagrams, and intrusion detection.
Feel free to get in touch with us if you have any questions about this example. Please note that our in-house-developed data-processing tools are subject to continual improvements. We strive to keep our online examples up to date, but bear in mind that we may now be able to produce superior results compared to what you see here.
Reduction to pole
FIGURE 1: Results of reduction to the pole (RTP) performed on Cloncurry total magnetic intensity (TMI) data. A magnetic dataset shows the variation in the Earth's magnetic field caused by variations in the magnetic susceptibility of the survey area's underlying rocks. This filter produces a field as though the survey's observations were made at the Earth's magnetic pole. The benefits of this image, compared to looking at the TMI data, is that (1) magnetic anomalies now sit directly over their source, and (2) anomalies are symmetric rather than skewed. (Note, though, that this will not be so for locales in which the rocks have significant remanence.) It means that the observer is better able to accurately locate magnetic sources.
First vertical derivative
FIGURE 2: Results of first vertical derivative (1VD) processing performed on Cloncurry RTP data. The results show the rate of change of the magnetic field in the vertical direction. Because the filter used to obtain this image accentuates shorter-wavelength features (i.e., localized features) in the original RTP data at the expense of longer-wavelength features (i.e., regional-scale features), the end result is a reduction in the data's dynamic range. This helps the observer more readily notice the subtle textural variations in the data's fine features.
Tilt angle
FIGURE 3: Results of tilt angle processing performed on Cloncurry RTP data. The filter used to produce this image removes from the RTP data information about how strong induced magnetization is. Stronger peaks are dampened, while weaker peaks get a boost. The end effect is a map of equalized peaks that helps the observer to notice relatively subtle features and structures that might have been 'swamped' in other types of images.
Horizontal gradient magnitude
FIGURE 4: Results of horizontal gradient magnitude (HGM) processing performed on Cloncurry RTP data. The filter used to produce this image defines where steep gradients exist in the original RTP data. Peaks are situated at locations where the strongest magnetic susceptibility contrasts occur in the RTP data. (Note that edges highlighted in the HGM image are positioned in the down-dip direction of sources with non-vertical sides.) This is useful when trying to determine where the geological faults or lithological contacts are seated — their precise locations aren't always easy to discern in the RTP image itself.
Ternary RGB image: 1VD, tilt angle, HGM
FIGURE 5: Ternary RGB image co-displaying the 1VD, tilt angle, and HGM results from processing performed on Cloncurry RTP data. This image has its red channel set to the first vertical derivative, its green channel set to the tilt angle, and its blue channel set to the horizontal gradient magnitude. All of this information combines to help the observer intuitively understand where major structural features are situated, where breaks in the continuity of the magnetic 'fabric' occur, and how the textural character of the magnetic data changes from one locale to the next.
Ternary CMY image: 1VD, tilt angle, HGM
FIGURE 6: Ternary CMY image co-displaying the 1VD, tilt angle, and HGM results from processing performed on Cloncurry RTP data. This image has its cyan channel set to the first vertical derivative, its magenta channel set to the tilt angle, and its yellow channel set to the horizontal gradient magnitude. This image can be regarded as the 'negative' of its RGB complement (which is shown in the previous figure), in the same way that photographic negatives represent the inverse of the photographs they help to produce during development in a dark room. By toggling between the RGB and CMY images, a fuller understanding of the area of interest can be gained, because often the eye is drawn to certain features depending on how they're colored.
1VD minus HGM
FIGURE 7: Results of 1VD minus HGM processing performed on Cloncurry RTP data. By subtracting the HGM from the 1VD results, you obtain a 'skeletonized' image with boosted contrast. This helps the observer notice detailed features in the data that were created by shallow/localized causative bodies. For instance, textural variations and precise trend-directions of linear features become readily apparent.
Automatic gain control
FIGURE 8: Results of automatic gain control (AGC) processing performed on Cloncurry RTP data. The filter used in this image re-scales the magnetic signal so that the data's range is reduced. Big booming highs are pulled down, while weaker highs are given a boost. This gives the observer the chance to take more notice of locales that may have been previously overlooked because they seemed unremarkable in the RTP image.
Analytic signal
FIGURE 9: Results of analytic signal (AS) processing performed on Cloncurry RTP data. The analytic signal is also known as the total gradient magnitude. The filter used to produce this image highlights locations in which the original RTP data possesses steep gradients. Peaks in the analytic signal correspond to places where either the vertical derivative (1VD) is large (regardless of whether a large positive number or a large negative number), or the horizontal gradient magnitude (HGM) is large. AS peaks are situated over the top of small sources. Peaks are also found along the interfaces where large-scale susceptibility contrasts occur.
Analytic signal of vertical integral
FIGURE 10: Results of AS of vertical integral (VIAS) processing performed on Cloncurry RTP data. The vertical integral of the RTP data (not shown among images presented in this example) yields the magnetic potential that would have been collected if the area of interest were situated at the Earth's magnetic pole — a procedure that accentuates relatively long-wavelength features in the data. Because the step of calculating the analytic signal re-introduces relatively short-wavelength features, this VIAS image has wavelengths and amplitudes that are similar to the original RTP image. The usefulness of this image is that it is less affected by remanence than its counterpart RTP image.
Ternary CMY image: RTP, AS, VIAS
FIGURE 11: Ternary CMY image co-displaying the RTP, analytic signal, and analytic signal of the vertical integral results from processing performed on Cloncurry RTP data. This image has its cyan channel set to the RTP, its magenta channel set to the analytic signal of the RTP (AS), and its yellow channel set to the analytic signal of the vertical integral (VIAS). All of this information combines to help the observer intuitively understand which locations in the area of interest are most likely to be affected by remanence. Locales that are likely remanence-affected are sites with magnetic lows in the RTP data but that also show up as magnetic highs in the AS and the VIAS. Such sites are represented in this ternary image as bright red-colored areas.
Pseudogravity
FIGURE 12: Results of pseudogravity (PG) processing performed on Cloncurry RTP data. This filter is applied to the vertical integral of the RTP data (image not shown in this example). The filter produces the equivalent magnetic field that would be expected if magnetism were a monopole phenomenon (similar to how gravity is a monopole field), rather than the dipole phenomenon that it is. The benefit of re-casting magnetic data in this way is that longer-wavelength features (i.e., deep/broad features) are accentuated.
Pseudogravity residual
FIGURE 13: Results of pseudogravity residual processing performed on Cloncurry RTP data. A residual is obtained by performing a differential upward continuation. The filter used to produce this image emphasizes magnetic anomalies in the pseudogravity grid that are attributable to relatively shallow/localized sources. The benefit of viewing the area of interest's magnetic data in this way is that it allows the observer to hone in on what is happening with the more detailed parts of the area's deep/broad magnetic features.
HGM of pseudogravity residual
FIGURE 14: Results of pseudogravity residual's horizontal gradient magnitude processing performed on Cloncurry RTP data. The filter used to produce this image defines where steep gradients exist in the pseudogravity residual data. Peaks are situated at locations where the strongest magnetic susceptibility contrasts occur in the pseudogravity residual data. This is useful when trying to determine where the geological faults or lithological contacts are seated — their precise locations aren't always easy to discern in the pseudogravity residual data image itself.
Ternary RGB image: PG, PG residual, HGM of PG residual
FIGURE 15: Ternary RGB image co-displaying the pseudogravity, pseudogravity residual, and pseudogravity residual's horizontal gradient magnitude results from processing performed on Cloncurry RTP data. This image has its red channel set to the pseudogravity, its green channel set to the pseudogravity residual, and its blue channel set to the horizontal gradient magnitude of the pseudogravity residual. All of this information combines to help the observer intuitively understand where major structural features are situated, where breaks in the continuity of the magnetic 'fabric' occur, and how the textural character of the magnetic data changes from one locale to the next. This benefit of this image is similar to the benefit of the ternary images involving 1VD, tilt angle, and HGM — the difference here is that the area of interest's deeper/broader features are being emphasized.
250m-1,000m residual
FIGURE 16: Results of 250m-1,000m residual processing performed on Cloncurry RTP data. A residual is obtained by performing a differential upward continuation. The filter used to produce this image emphasizes magnetic anomalies attributable to shallow/localized sources.
1,000m-2,500m residual
FIGURE 17: Results of 1,000m-2,500m residual processing performed on Cloncurry RTP data. A residual is obtained by performing a differential upward continuation. The filter used to produce this image emphasizes magnetic anomalies attributable to moderate-depth/breadth sources.
2,500m-5,000m residual
FIGURE 18: Results of 2,500m-5,000m residual processing performed on Cloncurry RTP data. A residual is obtained by performing a differential upward continuation. The filter used to produce this image emphasizes magnetic anomalies attributable to deep/broad sources.
Ternary RGB image: small-scale, medium-scale, large-scale residuals
FIGURE 19: Ternary RGB image co-displaying the 250m-1000m residual, 1000m-2500m residual, and 2500m-5000m residual results from processing performed on Cloncurry RTP data. This image has its red channel set to the 250m-1000m residual, its green channel set to the 1000m-2500m residual, and its blue channel set to the 2500m-5000m residual. All of this information combines to help the observer intuitively understand where major structural features are situated, where breaks in the continuity of the magnetic 'fabric' occur, and how the textural character of the magnetic data changes from one locale to the next. Another benefit of this type of image is that it essentially permits the observer to look at its 3 component images simultaneously. Features showing up as white are present as magnetic highs in all 3 residual maps, while yellow-colored features are present as highs in both the 250m-1000m residual map and the 1000m-2500m residual map. Cyan-colored features are present as highs in both the 1000m-2500m residual map and the 2500m-5000m residual map. Red-colored features represent highs in only the 250m-1000m residual map. Primary blue-colored features represent highs in only the 2500m-5000m residual map. Black designates locales where all three residual maps are displaying magnetic lows.
Ternary CMY image: small-scale, medium-scale, large-scale residuals
FIGURE 20: Ternary CMY image co-displaying the 250m-1000m residual, 1000m-2500m residual, and 2500m-5000m residual results from processing performed on Cloncurry RTP data. This image has its cyan channel set to the 250m-1000m residual, its magenta channel set to the 1000m-2500m residual, and its yellow channel set to the 2500m-5000m residual. This image can be regarded as the 'negative' of its RGB complement (which is shown in the previous figure), in the same way that photographic negatives represent the inverse of the photographs they help to produce during development in a dark room. By toggling between the RGB and CMY images, a fuller understanding of the area of interest can be gained, because often the eye is drawn to certain features depending on how they're colored. For instance, sometimes features showing up as black in a CMY ternary image attract the eye more and their precise extent is easier to judge than the same features showing up as white in the RBG ternary image. In some cases, though, this situation is reversed, depending on the nature of the geology being surveyed.
Ternary RGB image: X-gradient, Y-gradient, Z-gradient
FIGURE 21: Ternary RGB image co-displaying the X-gradient, Y-gradient, and Z-gradient (1VD) results from processing performed on Cloncurry RTP data. This image encapsulates information about how steeply the gradient changes in 3 orthogonal directions, namely the X and Y directions (within the plane of the image), and the Z direction (perpendicular to the plane of the image). All of this gradient information combines to help the observer intuitively identify the various major geological domains residing throughout the area of interest, and how these domains relate to each other.
Intrusion detection data-analysis
FIGURE 22: Results of intrusion detection data-analysis performed on Cloncurry RTP data. The filter used to produce this image highlights features in the data that are round — features that have a relatively high likelihood of being intrusive bodies or discrete alteration zones. The filter was used in a magnitude-independent way, so that round features were sought regardless of how prominent or quiet their magnetic signature is. (The filter could be used in magnitude-dependent mode if the exploration targets being sought are round magnetic features that are expected to be high-magnitude anomalies.) In this image, the filter was used to highlight round magnetically-high features possessing a radius between 1 kilometer and 2 kilometers. But note that the filter's settings can be adjusted if round features of a smaller or larger size were explorationally relevant.
Intrusion detection fused with RTP
FIGURE 23: Results of intrusion detection data-analysis superimposed on the Cloncurry area's grayscale RTP image. This image helps the observer understand how specific features in the intrusion detection results are associated with sites in the area of interest's magnetic data. Images of this type allow an expert observer (who has background knowledge about the geology of the area) to start formulating a testable theory as to why a given intrusion-detection feature has shown up. For instance, does a given peak in the results seem to be associated with likely magmatic intrusions, or does it seem associated with a site that might be hosting marked hydrothermal alteration because the site is where two or more geological structures (i.e., possible fluid pathways) intersect?