Geophysical surveys are performed when information about the earth’s subsurface is desired but direct sampling through expensive and invasive techniques such as drilling or trenching is insufficient, impractical or ill-advised. A survey may be as large as the whole Earth, as small as the top few meters of the subsurface, or anywhere in between.
During a geophysical survey, energy is put into the earth and responses are recorded at the surface, in the air or in boreholes. Resulting data reveal information about the earth because the behavior of the energy within the ground is controlled by the distribution of the earth’s physical properties. For instance, one basic physical property is magnetic susceptibility, which describes a rock’s ability to become magnetized. This physical property provides information on rock type and structures because the rock’s magnetic susceptibility relates directly to mineral type, to the chemical alteration processes. A second important physical property is electrical conductivity, which quantifies a material’s ability to carry electrical current. Figure 2 illustrates one way that a geophysical survey can be carried out to provide information about the subsurface distribution of electrical conductivity.
Figure 2. An example of how the distribution of a physical property (electrical conductivity in this case) can be measured to provide information about geologic materials.
a.
The physical properties under this surface are unknown. A geophysical survey- DC resistivity in this case - is used to generate data.
b.
Current is injected into the ground, and resulting voltages are measured as electrode geometry varies. In this case, voltages get smaller as electrodes are separated further and further apart.
c.
Inversion of this data set produces an estimate of a "layered earth" or 1D model of the relevant physical property - electrical conductivity.
d.
Interpretation converts the model into geologic information.
Evidently, the application of geophysics to problems involving earth’s subsurface is a non-trivial process and should be conducted through the seven-step procedure.
Traditionally, useful information was extracted from geophysical field results by examining maps or line profiles of raw or filtered survey data. Such images are useful for estimating locations and quantities of buried materials, and to help choose locations for more invasive (and expensive) techniques such as drilling. For example, large scale maps of magnetic or gravity data often show geologic structure, or identify an anomalous region that might be associated with a desired target. As an example Figure 3 shows the magnetic data acquired at the Bathurst region of New Brunswick. The major features observed are related to geologic structure.
Fig. 2 Figure 3. Tetatouche Antiform - Total Magnetic Field, from “Airborne Geophysical Survey of the Bathurst Mining Camp”, Geological Survey of Canada website.¶
Historically, in mineral exploration, the identification of an anomalous region was often the endpoint of the analysis, and the image was used to plan the location of a drill hole. Unfortunately, the success rate was generally poor. At best, data maps provide some information about the lateral extent of a body but little information about what is happening at depth. Quantitative analysis, in particular inversion, is required to obtain 3D information.
The goal of the inverse problem is to find a mathematical model of the earth that produced the field observations. That is “what subsurface physical property distribution caused the data that were observed at the surface?” Earlier inversion solutions involved characterizing the earth by a few prisms or layers and finding geometrical and physical properties of these simplified earth models.
Due to the earth’s extreme complexity, useful models often need to have many parameters, usually more than the number of data. This means that the problem of finding a model (i.e. estimating values for every parameter) is one in which there are more unknowns that data. Such problems do not have unique solutions, and this nonuniqueness is exacerbated when data are noisy or inaccurate. Formal inversion methods address these issues using well defined mathematical techniques. An appendix explains inversion in a little more detail.
Some benefits of applying rigorous inversion can be seen by comparing traditional map and pseudosection plots of the raw data to the information in 3D and 2D models obtained by inversion.
