Geophysical Exploration

Geophysical exploration uses measurements of physical fields or responses to investigate geological materials and structures. It is useful where exposure is limited or where a target has a detectable contrast with its surroundings. Method selection depends on the investigation objective, expected physical properties and site conditions; it is not simply a choice of the most detailed instrument available.^[1]

The result is evidence about a physical response and its possible sources. Mineral identification, commodity concentration and economic significance require additional geological and analytical evidence. A strong anomaly can be geologically useful without being a mineral deposit.

From Geological Hypothesis to Physical Contrast

A survey begins with a predicted link between the target and a measurable property. The target may be mineralisation, alteration, a host-rock boundary or a structure. Detectability depends on contrast, geometry, depth and measurement conditions. Conversely, no resolved anomaly does not prove absence: the target may lack sufficient contrast or lie outside the survey's effective sensitivity and coverage.^[1]

Magnetic measurements respond to the magnetisation of materials. Magnetic properties, source geometry and the direction of magnetisation affect the observed response. Consequently, the form and position of a magnetic anomaly cannot be read as a direct outline of an orebody. Temporal field variations and interference also need consideration during acquisition and processing.^[2]

Gravity investigates variations related to density distribution. A measured anomaly can be explained by different combinations of density contrast, depth and geometry. Position and elevation information and corrections for terrain effects therefore matter to interpretation, not only to survey administration.^[3]

For both methods, a practical question is whether plausible non-target geology could produce a similar response. Testing that possibility can be more informative than assuming that the highest amplitude marks the best mineralisation.

Complementary Measurements

Common active electromagnetic methods introduce a changing field and measure the resulting response, which is influenced by the electrical properties of the ground. They can help investigate conductive material, but interpretation also depends on surrounding ground and survey configuration.^[4]

Conductivity is not specific to a payable commodity. USGS descriptions of Earth MRI surveys identify graphite and pyrrhotite as examples of conductive minerals. Magnetic, electromagnetic and radiometric observations can provide complementary information about geological features, but their sensitivity and the ground they investigate differ.^[5]

Induced polarisation examines electrical polarisation behaviour, including processes at interfaces between grains and fluids. Metallic minerals can contribute to the response, but so can clays and other conditions affecting those interfaces. Chargeability or complex resistivity should therefore not be translated directly into a metal grade. The EPA's method description explicitly discusses both metallic-mineral and clay-related applications.^[6]

Complementarity is strongest when measurements test different explanations. Two processed images generated from the same original survey may highlight different features without constituting independent confirmation. A useful interpretation explains what additional constraint each dataset contributes rather than counting the number of coincident coloured anomalies.

Survey Geometry, Scale and Data Quality

The acquisition design should be evaluated against the target's expected position, orientation and dimensions. Stations or lines that fail to sample the relevant spatial change may leave an important feature unresolved. The practical issue is not just the number of measurements, but their distribution relative to the question being asked.^[1]

Positioning and acquisition records must remain associated with the measurements. For gravity, corrections and accurate elevation information are integral to isolating the geological signal. For magnetics, temporal variation in the Earth's field must be distinguished from spatial variation associated with the ground. Corrected and original records serve different purposes and should not be confused.^[3][2]

A useful quality review asks whether a feature persists across repeat observations, whether it corresponds to an acquisition or processing boundary, and whether nearby infrastructure could explain it. A discrepancy should be investigated before it becomes part of a geological interpretation. More elaborate modelling does not repair an unidentified positioning or measurement problem.

Geoscience Australia explains how geophysical observations can be presented as profiles and interpolated grids, with processing used to emphasise geological information. Interpolated cells are representations derived from the observations; making the cells smaller does not add observations between survey lines.^[7]

Modelling and Non-Unique Interpretation

Forward modelling predicts a response for an assumed distribution of physical properties. Inversion seeks a compatible model from measurements. Non-uniqueness, noise and simplified physics mean that the smallest numerical misfit need not identify the best geological explanation. Regularisation introduces constraints, such as smoothness, and balances data fit against model behaviour.^[8]

A close fit therefore does not establish a unique geological body. Interpretation should identify the assumed geometry, property bounds, data-error assumptions and poorly constrained regions. Features chiefly imposed by those assumptions are not measured underground boundaries.^[8]

The engineering implication is to distinguish a useful target model from a final geological model. A target model can justify where to obtain discriminating evidence even when several geometries remain plausible. Its quality is partly demonstrated by whether the proposed follow-up can distinguish those alternatives.

Smoothness favours gradual changes, while fine model cells can suggest unsupported detail. Checking whether a target persists under defensible changes in regularisation and other assumptions is more informative than relying on one detailed image.^[8]

Geological Integration and Follow-Up

Interpretation should bring physical-property results into the same spatial framework as mapping and sampling, while retaining their different evidence bases. A mapped structure might help explain an anomaly, but the association needs to be examined rather than accepted because the two appear close on a display.

A hypothetical electromagnetic target illustrates the issue. A test hole intersects conductive rock without the expected mineral enrichment. The physical response may have been explained while the proposed commodity target has failed. Alternatively, the intersection may account for only part of the observed response. Deciding between those outcomes requires comparing the encountered geology with the original geometry and response assumptions, not simply recording whether the hole was mineralised.

The follow-up decision should identify which uncertainty remains: source identity, source position, continuity or commodity content. Repeating the same survey at greater density may help one of those questions but not another. Physical sampling and geological interpretation are what connect a geophysical target to the material actually present.

Reporting the Result and Its Limits

A useful technical deliverable preserves survey configuration, locations, processing history, quality checks and model assumptions. It distinguishes recorded measurements from corrected profiles, interpolated grids and inversion-derived models; a grid cell is not automatically a measurement location. Geoscience Australia's account of gridding and image processing explains why products derived from the same measurements can differ.^[7]

The concluding statement should explain what has been detected, what explanations remain viable and what next observation would discriminate between them. Exploration value lies in reducing uncertainty about the ground, not in making an anomaly look more like an orebody than the evidence warrants.