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Artificial Intelligence helps solve the most complex problems at our feet | Health and Science

Artificial Intelligence helps solve the most complex problems at our feet |  Health and Science

 


Few technological advancements have captured minds – and fear – of humanity like AI. Whether robots escalate to subjugate their makers as in the Westworld series, or the malicious computer Hal 9000 from the classic 2001 movie: A Space Odyssey, machines that can learn are portrayed as threats to the world as we know it.

These futures contracts are clearly the work of fictional screenwriters. In fact, artificial intelligence, or AI, is working in the geosciences at the moment to help save the world and save lives. This topic is the focus of a virtual seminar series throughout the summer called “Machine Learning in Solid Earth Sciences,” a series that was hosted in Santa Fe in the pre-COVID-19 years.

We haven’t gotten to the point yet where the machines might think for themselves. So when we talk about artificial intelligence, it’s about the ability of computer algorithms to assimilate massive amounts of data and uncertainty and then identify patterns, learn from those patterns, and make predictions thousands of times faster than a human.

This is especially useful in the field of geosciences, where we look for patterns deep below the Earth’s surface to understand Earth’s processes and resources. In geology, there is a host of unknown possibilities, and separating one slice of information between the cacophony of natural noise is impossible for the human mind.

Earthquakes are a good example, because while we can predict many natural disasters in the world, alerting cities to an upcoming earthquake is still a long way off. But the answer may lie in artificial intelligence.

To find this answer, we study fault zones, which constantly tremble as one tectonic plate pushes against another, creating vibrational signals much like sound waves. Occasionally, deep in the Earth, the plates move subtly, causing a “slow slip” movement that is almost imperceptible to humans.

Each slow slide leads to random mixing of these sound waves. For years, scientists have dismissed this as hype, and random data is useless. However, recently, Los Alamos National Laboratory applied artificial intelligence to this data and discovered that it was hiding a host of information about seismic and seismic behavior. For example, two years ago, a study in Los Alamos trained an AI algorithm to slowly slide along the Cascadia subduction zone in the Pacific Northwest. By focusing on these seemingly random signals as the plates erupted together, the algorithm detected a clear pattern preceding slow slip, a kind of signature, that allowed scientists to predict an event in a few days.

The science is still young, but it has opened up an exciting new path that could one day lead to global earthquake prediction systems.

This same principle applies to our carbon capture and storage effort, as we remove carbon dioxide from an industrial process or the atmosphere and store it underground to reduce its impact on climate change. The goal is clearly to trap this gas thousands of feet below the surface of the Earth, under layers of rocks. Unfortunately, carbon dioxide is activated, so it must be stored underground in airtight areas to prevent it from leaking back into the atmosphere. This raises the question: How long will you stay underground?

First, with sensors, AI can help detect CO2 leaks, and look for consistent patterns that can then trigger a leak alert. Second, artificial intelligence could help us predict the fate of carbon dioxide over thousands of years. Will the carbon dioxide eventually solidify, making the site more attractive and less prone to leakage? Along with the geological data and historical information provided by scientists, AI can provide a set of scenarios, then identify the most likely outcome.

This forward-looking ability also helps predict water shortages in New Mexico. In our state, about half of the drinking water comes from underground. Farmers use the wells to grow vegetables, orchards and animal feed. In the future with less rain, it is imperative to know how much water is on the ground, and how much water is left on any given day or month.

This can be done with the help of groundwater modeling, which helps us understand where groundwater is moving. In one place, there may be a vast aquifer underneath. But 100 yards in any direction the water might have to flow around an underground rock formation, making the ground beneath that location dry. And all of this can change depending on how much water is pumped from one place.

Linked to groundwater flow and aquifer models, an AI algorithm can tell us that if Farmer Joe pumped out X number of gallons, he could disable his neighbor’s well. Artificial intelligence can then use the expected precipitation for any given region to predict how that will change within a year or a decade. Artificial intelligence can also provide daily insight into how much water is being removed from an aquifer, and this information can help municipalities set standards that will benefit farmer Joe and people who expect water to flow from their taps every time they turn to the nobility.

Humans’ complex interactions with their environment, especially the subterranean resources on which we depend, challenge our understanding, making them difficult to predict. And it becomes more complex with increasing population and changes in the environment and climate. Fortunately, complex problems with unknown results are precisely the best that AI can solve.

Harry Viswanathan is a geologist in the Computational Geosciences Group at Los Alamos National Laboratory, where he studies subsurface energy and ecosystems.

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