Editorial Feature

Leveraging Quantum Sensors for Advanced Geological Surveying Techniques

Geological surveying using quantum sensors allows us to understand the subsurface of Earth with precision, accuracy and higher depth penetration as compared to traditional geological surveying techniques. This article discusses how quantum sensors can be employed in geological surveying, commercial examples, and recent relevant studies.

Leveraging Quantum Sensors for Advanced Geological Surveying Techniques

Image Credit: CodexSerafinius/Shutterstock.com

Geological Surveying Techniques that use Quantum Sensors

Quantum sensing can be employed in geological surveying by several techniques and tools that utilize quantum sensors, such as quantum gravity gradiometers, magnetometers, and quantum resonance imaging.

Gravity gradiometry is a fundamental tool in geological surveying that provides information about subsurface density variations. Quantum gravity gradiometers operate by creating highly sensitive quantum interferometers using cold atoms or Bose-Einstein condensates, which enables measuring the tiny differences in gravitational force at different points, providing detailed information about the geological structures beneath the Earth's surface. This provides a more accurate and high-resolution gravity map, aiding in the identification of potential mineral deposits or geological faults.

Similarly, geological formations exhibit magnetic field variations, which are utilized as sensing mechanisms for geological surveying. Quantum sensors, such as magnetometers based on nitrogen-vacancy (NV) centers in diamond, operate by detecting the quantum properties of electrons within the diamond lattice, enabling geoscientists to map magnetic anomalies with high accuracy and identify subsurface structures and geological features.

Another technique is quantum resonance imaging, which involves utilizing quantum sensors to detect the interactions between subsurface materials and external electromagnetic fields, providing detailed images of the subsurface and revealing the distribution of different geological materials.

Recent Developments

Bayesian Inference in Tunnel Detection

A recent study introduces a practical quantum gravity gradient sensor designed to overcome limitations in gravity cartography caused by long measurement times and vibrational noise. The sensor achieves a statistical uncertainty of 20 E and demonstrates sub-meter spatial resolution in geological surveying.

The researchers successfully detected and located a 2-meter tunnel with high precision using Bayesian inference. The sensor's hourglass configuration, based on cold atom gravity gradiometry, effectively minimizes noise from various sources, allowing robust and compact operation in the field.

The study envisions applications in mapping aquifers, archaeology, soil property assessment, and infrastructure construction, providing an advanced tool for improved underground exploration. As per the study, future enhancements could further enhance sensitivity and reduce measurement times, making quantum gravity sensors increasingly practical for diverse applications within the next 5–10 years.

Borehole-Deployable Quantum Gravity Sensors

Another study focuses on deploying cold atom-based sensors down boreholes for improved gravity surveys. Quantum technology gravity sensors, utilizing atom interferometry, demonstrate the potential for increased survey speeds and reduced calibration needs.

The researchers successfully developed a borehole-deployable magneto-optical trap with a compact size, robustness, and environmental resilience suitable for borehole conditions. This system generated atom clouds at 1-meter intervals in a 50-meter deep borehole, simulating in-borehole gravity surveys. The breakthrough aims to address the drawbacks of traditional borehole gravity sensors, offering higher precision and overcoming challenges related to size, weight, power consumption, and environmental conditions.

Mineral Exploration using SQUIDs

Superconducting quantum interference devices (SQUIDs) were explored in a 2022 study, showcasing developments in airborne vector magnetometers with ultra-low noise and high dynamic range. The study introduced an airborne full tensor gradiometer instrument and a ground-based transient electromagnetic method using SQUID-based receivers.

Additionally, a novel airborne quantum sensor-based system for audio-frequency magnetotellurics (QAMT) was presented, demonstrating its capability to extract magnetic field vectors and transfer functions for passive electromagnetic methods. The research highlighted successful demonstrations and performance evaluations, emphasizing the potential of quantum magnetometers, including SQUIDs, in advancing geophysical exploration tools for mineral exploration and subsurface imaging.

Commercial Examples

Several companies are involved in developing and producing quantum sensors for commercial geological surveying applications.


SBQuantum employs quantum sensors, specifically quantum magnetometers utilizing nitrogen vacancy diamonds, to conduct advanced geological surveys, enabling precise, localized magnetic modeling of the Earth. Their dashboard allows clients to explore and navigate based on hidden fluctuations in the Earth's magnetic field.

SBQuantum aims to revolutionize various industries, including mining, navigation for autonomous vehicles, defense, security, and even space exploration.

Nomad Atomics

Nomad Atomics' suite includes compact cold-atom gravimeters for optimized performance, highly accurate globe sensors with sensitivity and zero drift, and robust instruments tested under extreme conditions. These sensors provide high accuracy by exploiting the quantum properties of atoms, enabling advanced field applications in resource monitoring, exploration, and navigation without reliance on external systems.


The precision and sensitivity offered by quantum technologies enable geoscientists to obtain more accurate and detailed information about geological structures, mineral deposits, and environmental conditions.

Although quantum sensors have immense potential in geological surveying, challenges like the complexity of quantum technologies, the need for specialized expertise, and the development of robust field-deployable quantum sensors must be addressed for their widespread adoption.

However, as research and development in quantum sensing progress, the future of geological surveying with enhanced quantum sensor-based exploration techniques looks bright.

More from AZoQuantum: Harnessing Quantum Computing for Breakthroughs in Artificial Intelligence

References and Further Reading

Choi, C. Q. (2022). New Quantum Sensor Sees Beneath the Beneath. IEEE Spectrum. [Online] Available at: https://spectrum.ieee.org/quantum-sensors-gravity-birmingham

SBQUantum. https://sbquantum.com/

Nomad Atmoics. https://www.nomadatomics.com/

Stray, B., Lamb, A., Kaushik, A., Vovrosh, J., Rodgers, A., Winch, J., ... & Holynski, M. (2022). Quantum sensing for gravity cartography. Nature. https://doi.org/10.1038/s41586-021-04315-3

Vovrosh, J., Wilkinson, K., Hedges, S., McGovern, K., Hayati, F., Carson, C., ... & Holynski, M. (2023). Magneto-optical trapping in a near-suface borehole. Plos one. https://doi.org/10.1371/journal.pone.0288353

Stolz, R., Schiffler, M., Becken, M., Thiede, A., Schneider, M., Chubak, G., ... & Terblanche, O. (2022). SQUIDs for magnetic and electromagnetic methods in mineral exploration. Mineral Economics. https://doi.org/10.1007/s13563-022-00333-3

Pilkington, Ben. (2022, March 10). Gravity Sensors: Innovations and Applications. AZoSensors. Retrieved on February 11, 2024 from https://www.azosensors.com/article.aspx?ArticleID=2482

Abbasi, Ibtisam. (2023, August 07). Real-Time Environmental Monitoring With Quantum Sensors. AZoQuantum. Retrieved on February 11, 2024 from https://www.azoquantum.com/Article.aspx?ArticleID=444

Ali, Owais. (2023, September 21). A Closer Look at Quantum Sensing's Applications. AZoSensors. Retrieved on February 11, 2024 from https://www.azosensors.com/article.aspx?ArticleID=289

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Taha Khan

Written by

Taha Khan

Taha graduated from HITEC University Taxila with a Bachelors in Mechanical Engineering. During his studies, he worked on several research projects related to Mechanics of Materials, Machine Design, Heat and Mass Transfer, and Robotics. After graduating, Taha worked as a Research Executive for 2 years at an IT company (Immentia). He has also worked as a freelance content creator at Lancerhop. In the meantime, Taha did his NEBOSH IGC certification and expanded his career opportunities.  


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Khan, Taha. (2024, February 13). Leveraging Quantum Sensors for Advanced Geological Surveying Techniques. AZoQuantum. Retrieved on April 14, 2024 from https://www.azoquantum.com/Article.aspx?ArticleID=496.

  • MLA

    Khan, Taha. "Leveraging Quantum Sensors for Advanced Geological Surveying Techniques". AZoQuantum. 14 April 2024. <https://www.azoquantum.com/Article.aspx?ArticleID=496>.

  • Chicago

    Khan, Taha. "Leveraging Quantum Sensors for Advanced Geological Surveying Techniques". AZoQuantum. https://www.azoquantum.com/Article.aspx?ArticleID=496. (accessed April 14, 2024).

  • Harvard

    Khan, Taha. 2024. Leveraging Quantum Sensors for Advanced Geological Surveying Techniques. AZoQuantum, viewed 14 April 2024, https://www.azoquantum.com/Article.aspx?ArticleID=496.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.