Big Data

Geologists Turn to Big Data to Uncover New Minerals

Scientists at the Carnegie Institute for Science have turned to big data mining as they seek to discover new mineral deposits. This turn of events is likely to have an impact on how minerals are discovered and studied.  The scientists who are involved in among others; oil, gas, copper and gold exploration have resulted in techniques similar to those used by Netflix and Amazon to sift through huge volumes of data and get useful insights into the existence of mineral deposits.

Dr. Robert Hazen, the executive director of the Deep Carbon Observatory at the Carnegie Institute for Science says that minerals occur on Earth in clusters. He adds that just like the way humans have social networks such as Facebook, minerals too have networks.

Currently, there are more than 5200 known naturally occurring minerals. These have already been found and catalogued in different locations across the world. This gives mineralogists sufficient data points to work with but extracting insights from the data has remained a challenge.

In a recent paper published in the American Mineralogist, the scientists explain how they have applied the network theory to gain useful insights into the existence and distribution of copper and chromium deposits over time. The approach is expected to lead to the discovery of new mineral deposits.

Network theory is used to analyse complex connections and interactions among different objects. The method has previously been used to predict the spread of diseases, the structure of biological systems or the internet. Using this approach, the Carnegie team designated each known mineral as a “node” and each location where two minerals were found together was designated as a connection between the nodes. This generated a 3D network which helps in the identification of trends and clusters that point the scientists to where the mineral deposits can be found.

Dr. Shaunna Morrisson, one of the lead authors of the paper says that the quest for new mineral deposits has been incessant for a long time. However, the discovery has been largely a matter of luck as opposed to scientific prediction. He adds that this is likely to change, thanks to big data.

The new technique can also be applied to predict the existence of minerals that have never been known before. For instance, the Carnegie team has predicted the existence of 145 unknown carbon containing minerals, out of which, ten minerals including abellaite parisite have since been discovered. However, the new minerals have no known economic application yet.

The network theory is also used in understanding how the earth’s geology has changed over time as well as how it has been affected by living organisms. The authors describe the changes in the distribution of copper containing minerals with the change in oxygen concentration in the earth’s atmosphere.

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