Critical Minerals - Case Studies

Lithium brine projects live or die on understanding basin geometry, brine-saturated units, freshwater recharge zones, and faults/compartments—not just on “finding something conductive.” In salt flats, the subsurface can be extremely conductive (~0.1 Ω·m), which limits the depth and usefulness of many common EM tools.

What the industry uses today (Argentina example: Pozuelos salt flat)

A multi-physics workflow in the Pozuelos salt flat (NW Argentina) shows what works in practice:

• ERT (Electrical Resistivity Tomography) along salt-flat margins to map the freshwater–brine contact and recharge pathways. 
• Full-tensor AMT/MT to characterize the conductive column and basement, identifying multiple conductive units interpreted as brine-saturated systems. 
• Gravity to delineate basin geometry and major structures, then integrate with MT for depth-to-basement mapping and fault interpretation. 

Here, in Argentina, we use the KMS-820 acquisition system. It is one of the few systems that can actually measure the lithium-brine resistivity contrast accurately, because the KMS-820 is designed to follow large instantaneous dynamic range changes. The interpretation is done using standard interpretation techniques as shown below.

In the magnetotelluric profile, the blue colors indicate conductive strata, which we infer as being rich in lithium (confirmed). Critically, the results were tied to exploration/monitoring wells and rolled into a 3D static model below. Here, all of the measurements are integrated and the profile location is shown. The interpretation is confirmed by drilling

Adding CSEM for improved resolution (Saudi Arabia example: high-power land CSEM in a salt-flat setting)

A high-power CSEM field test in eastern Saudi Arabia (Half Moon Bay / Dammam Peninsula) demonstrated that land CSEM can acquire and invert high-quality data and detect very low-resistivity targets consistent with economic brines. Key results reported from inversions include:

• A very low resistivity layer (< 1 Ω·m) appearing consistently below ~300–350 m in multiple soundings. 
• At several stations, a layer of about 0.3 Ω·m starting around 300–350 m depth, with ~1 km thickness. 
• In a far-offset sounding (~20 km), a deeper ~0.1 Ω·m conductor interpreted at roughly ~3 km depth.

Very low resistivity can be caused by brines, clays, or both. The Argentina study makes this ambiguity explicit for deeper conductive units, and the correct path is always integration with geology and exploratory boreholes. 

In the image below, both the CSEM and the MT measurements are seing the conductive lithuim-brine layer.

Why method choice matters for mapping ultra-conductive salars

In the Pozuelos case, several commonly used methods can fail to reach meaningful depth in a ~0.1 Ω·m environment, including TEM, CSAMT, and SCSAMT (skin depth limits and/or insufficient field components for realistic geology). (Curcio et al. 2022)

This sets up a clear positioning for CSEM:

• MT/AMT is an effective “basin-scale” passive tool (conductive column + basement).
• CSEM adds a controlled, designable source that can be optimized for signal-to-noise and survey objectives, and used to tighten uncertainty in priority areas (especially where investment decisions need higher confidence).

How ETI applies CSEM to lithium / critical minerals exploration

ETI workflow

1. Basin screening: MT/AMT + gravity to define basin geometry, faults, and conductive units.
2. Hydrology targeting: ERT or TEM to map freshwater–brine interfaces at margins and recharge zones. 
3. CSEM infill over priority blocks: deploy land CSEM to test and refine key conductive targets (thickness, continuity, compartmentalization), using inversion-led interpretation as shown in the Saudi case. 
4. Integrate with wells → static model: convert geophysics into a 3D model aligned with drilling and resource planning (the Pozuelos approach). 

What this delivers

• Better targeting of drilling and pumping tests
• Clearer mapping of structural controls (faults/compartments) that impact brine movement
• A faster path from “geophysical anomaly” to a bankable subsurface model (static now, dynamic later).