January 4th, 2025: This post investigates the cause of crustal-scale electrical conductivity anomalies observed in magnetotelluric (MT) imaging of mineral provinces, specifically in the Olympic Dam region of Australia and the Southeast Missouri Iron Province (SMIP) in the United States and is derived from and a review of Graphite as an electrically conductive indicator of ancient crustal-scale fluid flow within mineral systems, Benjamin S. Murphy, Jan Marten Huizenga, Paul A. Bedrosian, Earth and Planetary Science Letters, 202s, https://doi.org/10.1016/j.epsl.2022.117700
The research concludes that these regional scale conductivity anomalies are most likely due to graphite precipitation from CO2-rich magmatic fluids. This challenges previously published interpretations that loosely attributed conductivity to metasomatism along fluid pathways.
The authors propose a model where mantle-derived melts transport CO2-rich fluids into the crust. As these fluids cool, graphite precipitates, forming conductive zones at mid- to lower-crustal levels. The study uses a quantitative approach to calculate the amount of carbon mobilized from the mantle and the resulting electrical conductivity, finding that even small amounts of well-connected graphite can produce significant conductivity anomalies.
This study represents a not unexpected advance in our understanding of crustal conductivity anomalies and their relationship to mineral systems. The authors’ approach is rigorous and well-reasoned, their conclusions are supported by evidence, and their work has important implications for mineral exploration.
Key Findings:
- Graphite is the primary cause of crustal-scale electrical conductivity anomalies observed in MT imaging in the Olympic Dam region and the SMIP, not free fluids, metallic sulfides/oxides, or silicate minerals.
- Graphite precipitates from cooling, CO2-rich magmatic fluids exsolved from mantle-derived melts at mid- to lower-crustal depths.
- A small, bulk-average volume fraction of graphite (4.16 × 10−6) can produce a significant conductivity anomaly if the graphite is well-connected.
- The model suggests that deep CO2-rich fluids which precipitate graphite are not the same fluids that directly drive ore mineralization at shallower crustal levels; instead, the ore-forming fluids are likely derived from more evolved melts and mixed with near-surface fluids.
- The depth range of the conductivity anomalies may reflect the spatial location of pressure and temperature conditions most conducive to graphite precipitation.
The study focused on the Olympic Dam region in Australia and the Southeast Missouri Iron Province (SMIP) in the United States as premier examples of areas with observed spatial relationships between lithosphere-scale electrical conductivity anomalies and iron oxide-apatite (IOA) and iron oxide-copper-gold (IOCG) deposits.


Olympic Dam Region:
- The Olympic Dam IOCG deposit is located in South Australia and contains 2.95 billion tonnes of ore grading 1.2% Cu, 0.04% U, 0.5 g/t Au and 6 g/t Ag and significant REEs and iron
- It is an intra-cratonic, Mesoproterozoic deposit and is of a magmatic-hydrothermal origin.
- The genetic models for deposits in the region invoke mantle-derived magmatism in an extensional setting to provide heat and fluids, as well as metals
- Magnetotelluric (MT) imaging reveals highly conductive, steeply dipping pipe- or sheet-like conductors at mid to lower crustal depths, as well as moderately conductive “fingers” that extend into the upper crust beneath individual deposits.
- The coincident conductivity anomalies have been loosely interpreted as the signature of metasomatism along crustal-scale magmatic fluid pathways.
- The study proposes that these conductivity anomalies are specifically due to graphite precipitation from CO2-rich magmatic fluids.

Southeast Missouri Iron Province (SMIP):
- The SMIP is located in the midcontinent of the United States and contains Mesoproterozoic-aged IOA-IOCG deposits. The SMIP hosts eight major and numerous minor magnetite and hematite deposits. It is hosted by the Middle Proterozoic Saint Francois granite-rhyolite terrane
- Similar to the Olympic Dam region, the SMIP deposits are considered magmatic-hydrothermal in origin with genetic models invoking mantle-derived magmatism in an extensional setting.
- MT imaging in the SMIP reveals highly conductive zones at mid-lower crustal depths, with moderately conductive “fingers” extending into the upper crust beneath deposits.
- The conductive zones beneath the SMIP are associated with domains of low magnetic susceptibility, which suggests that metallic oxides are not the cause of the high conductivity values.
- The carbon isotope data from the iron deposit within the SMIP suggest a mantle origin for carbon.
- The study reports a strong spatial relationship between conductivity anomalies and magnetic susceptibility and IOA and IOCG deposits.

Exploration Implications:
The study has significant implications for mineral exploration, particularly for magmatic-hydrothermal iron oxide-apatite (IOA) and iron oxide-copper-gold (IOCG) deposits.
- MT imaging can be used to identify the deep roots of mineral systems by targeting crustal-scale electrical conductivity anomalies resulting from graphite precipitation. These anomalies can serve as vectors toward potential ore deposits, even though the graphite itself may not be directly associated with the ore.
- The study suggests that a bulk-average graphite volume fraction of 4.16 × 10−6, when well-connected, will produce a conductivity anomaly of approximately 100 S/m.
- The association of graphite with fluid pathways highlights the role of magmatic fluids in these mineral systems which could help identify areas with potential for ore formation.
- The study emphasizes that not all conductivity anomalies are related to ore mineralization, so complementary geological, geochemical, and geophysical data are crucial to determine the validity of hydrothermal graphite precipitation in any specific context.
- The depth range of the observed conductivity anomalies may provide information on paleo-pressure and temperature conditions and the redox state of magmatic fluids.
- Exploration efforts should focus on identifying areas where magmatic redox conditions are near the fayalite-magnetite-quartz (FMQ) buffer, as this is conducive to graphite precipitation. Systems with highly oxidized magmatic fluids, such as porphyry copper systems, are less likely to have conductive anomalies caused by graphite precipitation.
- The model proposes that graphite precipitation occurs at mid- to lower-crustal levels, while mineralization occurs at upper-crustal levels. Therefore, graphite is not expected to be exposed in the upper crust.
- Examination of exposed lower crustal sections could provide additional insights for assessing the role of hydrothermal graphite precipitation in mineral systems.
- Upper crustal, moderately conductive “fingers” that extend from the lower crustal anomalies may also be explained by hydrothermal graphite, possibly formed during wall-rock hydration reactions.
- The Sri Lankan vein graphite deposits may be an analogue for the type of graphite that may be found beneath Olympic Dam and the SMIP. The graphite in Sri Lanka is distributed in vain-like networks along a large corridor and is thought to have formed from mantle-derived fluids.

Potential Limitations and Areas for Further Research:
The study offers a robust explanation for deep crustal conductivity anomalies and the authors systematically evaluate and rule out other potential causes such as free fluids, metallic sulfides/oxides, and silicate minerals based on physical, chemical, and geological constraints. The quantitative modeling is compelling and is supported by various other geological, geochemical, and geophysical observations.
There are a number of limitations however and areas for further study:
- Model Assumptions: The model makes some simplifying assumptions, such as a constant fluid oxygen fugacity (fO2) during graphite precipitation, and a simplified P/T path. While the authors justify these assumptions, the sensitivity of the results to these assumptions could be explored further. For example, the model assumes that the wall rock buffers O2 such that the fluid is held at a constant fO2 during graphite precipitation but if this assumption is violated, then less graphite would precipitate.
- Uncertainty in Graphite Distribution: While the study addresses the issue of graphite interconnection, the actual distribution of graphite at depth is unconstrained. The authors recognize that graphite is likely concentrated along discrete fluid pathways, but further work could focus on understanding the factors that control the development of these pathways, and hence the distribution of graphite.
- Laboratory vs. Field Scale: The study recognizes the challenges in applying laboratory measurements of electrical conductivity to field scales. While it effectively uses mixing laws to address this issue, further studies that directly compare laboratory and field observations could help constrain the interpretation of MT data.
- Limited Analogs: The study uses Sri Lankan vein graphite deposits as an analog, but more examples from other settings would strengthen the argument, particularly in relation to the moderately conductive “fingers” in the upper crust. The authors also note that there is a lack of laboratory experiments on rocks containing fluid-precipitated graphite.
- Redox Conditions: The model is sensitive to the redox conditions of the magmatic fluids. The study acknowledges this, but further research could explore the factors that control magmatic redox conditions and how they influence graphite precipitation.
Overall Assessment:
Despite these limitations, by highlighting the role of graphite precipitation from CO2-rich magmatic fluids, they provide a new and valuable framework for interpreting MT data in the context of magmatic-hydrothermal ore deposit formation. The authors identify several avenues for further research, and the model presented in this paper can help to better understand how to vector towards ore deposits by integrating MT data within a mineral systems framework.
References
Selway, K., 2018 Developing meaningful interpretations for MT Models