The advantages of 2.5D (2D geology, 3D source) airborne electromagnetic inversion in 3D geological mapping applications compared to the more commonly used CDI transforms or 1D inversions are demonstrated using examples from different geological settings.2.5 D inversion sections show:
(a) greater depth resolution,
(b) complex/real body geometries, not just layers and plates ( e.g. synclines ),
(c) tend to minimize the causative body dimensions compared to other methods, due to better constraints,
(d) data from whole survey lines can be inverted within a single inversion attempt.

The technology is realized using the numerical solutions afforded by the 2D finite-element method. This enables the accurate simulation of 3D source excitation inclusive of topography, non-conforming boundaries and very high resistivity contrasts. Solution is accurate for geo-electrical cross-section which is relatively constant along a strike length that exceeds the AEM system footprint.

Completely new inversion solver with adaptive regularization algorithm allows the incorporation of a misfit to the reference model and the model smoothness function.

We allow the use of a starting or reference geology/resistivity model to influence the inversion and the software is or can be incorporated within a 3D geological modelling software with an intelligent graphical user interface.
For speed, the software has been parallelized using Intel MPI and can be used on standard computing hardware or computing clusters. Data from survey lines with lengths exceeding 30 kilometres can be inverted on laptop computers.

Numbers of examples are used to demonstrate the viability of using 2.5 D models to invert the data at a survey scale.

Anisotropy is the property of being directionally dependent, as opposed to isotropy, which implies identical properties in all directions. It can be defined as a difference, when measured along different axes, in a material’s physical or mechanical properties (wording taken from Wikipedia).Anisotropy occurs anywhere and anytime, and not only in nature. It could be described e.g. as someone walking in a city where streets are busy with traffic. How easy, or how difficult, will be for that person: to walk along the traffic on the sidewalk? or to cross the same busy street? His walking speed will definitely be reduced when trying to cross the street where traffic goes in one direction.

Mathematically, anisotropy can be quantified with tensor algebra and analysis. Anisotropy is described as a tensor where the elements represent one specific property changing in different directions. In Physics, anisotropy tensors are found e.g. in Thermodynamics, Continuum Mechanics (hydraulic and elastic waves), Magnetism, and Electromagnetics. For example, the deformation in a specific direction of elastic bodies, when subjected to a force with a different direction, is described in the the Law of Hook. The stiffness tensor describes the elastic properties of the material being deformed.

Also, materials are a lot of times electrically anisotropic. This means they have different electrical properties when current flows in different directions. For example, a crystal of graphite consists microscopically of a stack of sheets, and current flows very easily through each sheet, but moves much less easily from one sheet to the next. In an analogy, this was described above as someone trying to cross a busy street. The conductivity tensor in the Law of Ohm describes the direction-dependency of the electric properties of the material when being exposed to a current flowing in different directions.

In Geology, anisotropy can be observed in many scales: from crustal scales (fault systems and unconformities), to deposit scales (veining due to hydrothermal fracturing), and to microscopic scales, since most common rock-forming minerals are anisotropic, including quartz and feldspar.

In the exploration of oil and gas, geophysicists have been using regularly, and since a long time, the concept of anisotropy. Geological formations with distinct layers of sedimentary material can exhibit electrical anisotropy, meaning this that electrical conductivity in one direction (e.g. parallel to a layer), is different from that in another (e.g. perpendicular to a layer). That property, sometimes called channeling, is being used to identify hydrocarbon-bearing sands in sequences of sand and shale. Hydrocarbon-bearing sands have high resistivity, whereas shales have lower resistivity.

The geological scale where mineral explorers are mostly interested in is the deposit scale. A stock-work, for example, a geological expression being common in many ore deposit types such as in porphyries, is a complex system of structurally-controlled or randomly oriented veins, which are many times sulphide-bearing and very conductive. That vein system, allowing electrical current in one direction, but restricting it in another direction, should have a specific signature in the geophysical data acquired over the deposit.
Is anisotropy an effect that mineral geophysicists prefer to avoid? Could that effect help us find and characterize an ore deposit?

Since the early 90’s, SJ Geophysics has been continually developing and experimenting with unconventional IP array designs. Current customized arrays utilized with the Volterra acquisition system make use of cross-line dipoles to improve the azimuthal distribution of the data. A key aspect of any IP survey, the selected array design must meet the survey objectives determined at the start of the project.In the mineral exploration industry, survey design rarely gets the time and attention that it deserves. Rather, surveys are acquired by essentially “shooting in the dark” using last week’s parameters in the hopes that the target of interest will become illuminated and the picture more clear. Unfortunately, this approach simply doesn’t work. A well defined survey objective and a-priori geologic information must be taken into consideration during the survey evaluation and design process in order to get the best results.

All to often the survey objectives are overlooked by the potential client when requesting a survey and replaced with “How deep can I see?” Their hope is to have an answer in 30 seconds. In trying to answer this question for clients, the importance of good array design becomes important.

Simple 2D-inline arrays have evolved into complex customizable arrays such as the diamond array that incorporate dipoles in multiple directions to maximize signal coupling and improve surface resolution.  An examination of receiver arrays and how they affect the resulting data collected will be discussed. Data examples from real world surveys will be provided to illustrate the benefits of 3DIP array designs. A key example is the Ootsa Property, owned by Gold Reach Resources. In 2013, SJ Geophysics took the initiative to re-survey the Seel deposit to compare their new 3DIP acquisition equipment and survey methods against an older IP survey acquired using conventional 2DIP and early 3DIP systems. The benefits of advanced 3D array designs is evident in the resulting inversion models.