The Stanford model shows how fluids open faults to trigger earthquake swarms

The new fault simulator depicts how interactions between pressure, friction, and spiraling fluid across the fault zone can lead to slow-moving earthquakes and seismic swarms.

Written by Josie Garthwaite

Earthquakes can be sudden bursts of collapsing energy in a home, and Earth’s torsion when segments of the planet’s crust for a long time slide into place due to friction.

“We usually think of the plates on both sides of the fault as they move, deform and build up stresses, and then an earthquake occurs,” said Stanford University geophysicist Eric Dunham.

But deep down, these boulders can slide steadily on top of each other, crawling along cracks in the earth’s crust at the rate your nails grow.

There is a boundary between the creeping lower portion of the fault, and the upper portion that may remain closed for centuries at a stretch. For decades, scientists have puzzled over what controls these boundaries, their movements and their relationship to major earthquakes. One of the most important unknowns is how fluid and pressure travel along faults, and how this causes faults to slip.

The new physics-based bug simulator developed by Dunham and colleagues provides some answers. The model shows how the fluid is proportional to its height and gradually begins to weaken the error. In the decades before major earthquakes, they appear to push boundaries, or lock in depth, a mile or two up.

Migratory flocks

The research, published September 24 in Nature Communications, suggests that as pulses of high-pressure fluid approach the surface, they could trigger swarms of earthquakes – chains of earthquakes that cluster in a local area, usually over the course of a week or so. Often the vibration from these seismic swarms is too subtle to be noticed, but not always: a swarm near the southern tip of the San Andreas Fault in California in August 2020, for example, caused an earthquake measuring 4.6 magnitude enough to cause a jolt in Surrounding cities. .

Each earthquake in a swarm has its own sequence of aftershocks, as opposed to one large major shock followed by several aftershocks. “Earthquake swarms often involve the migration of these events along a fault in some directions, horizontal or vertical,” said Dunham, senior author of the research and associate professor of geophysics at Stanford University’s School of Earth, Energy and Environmental Sciences (Stanford Earth). .

The emulator shows how this relay works. While much advanced seismic modeling in the past 20 years has focused on the role of friction in opening faults, the new work explains the interactions between fluid and pressure in the fault zone using a simplified two-dimensional model of the fault that cuts vertically across the entire Earth’s crust, similar to the San Fracture. Andreas in California.

“Through computer modeling, we were able to discover some of the root causes of the erratic behavior,” said lead author Weiqiang Zhu, a graduate student in geophysics at Stanford University. “We have found that the ebb and flow of pressure around a fault may play a greater role than friction in dictating its force.”

Underground valves

Faults in the Earth’s crust are always saturated with liquids – mostly water, but water blurring the differences between liquid and gas. Some of these fluids originate in the Earth’s abdomen and migrate to the top; Some come from the top when rain breaks out or energy developers inject fluids as part of oil, gas, or geothermal projects. “Increases in pressure in this fluid can push outward on fault walls and make the fault slip easier,” said Dunham. “Or, if the pressure drops, this creates suction that holds the walls together and prevents slipping.”

For decades, studies of rocks extracted from fault areas have revealed telltale cracks, mineral-filled veins and other signs that pressure can fluctuate greatly during and between major earthquakes, leading geologists to theorize that water and other fluids play an important role in triggering earthquakes and The effect is when the largest earthquakes hit. “The rocks themselves tell us that this is an important process,” said Dunham.

Recently, scientists have documented that the injection of fluids related to energy processes can lead to seismic swarms. Seismologists have linked oil and gas wastewater disposal wells, for example, to the dramatic increase in earthquakes in parts of Oklahoma starting in 2009. And they have discovered that earthquake swarms migrate along faults faster or slower in different environments, be it under A volcano around the geothermal process or within oil and gas reservoirs, possibly due to the large variation in fluid production rates, Denham explained. But the modeling did not untangle the network of physical mechanisms behind the observed patterns.

Dunham and Chu’s work is based on the concept of faults as valves, which geologists first introduced in the 1990s. “The idea is that fluids ascend along faults intermittently, even if these fluids are released or injected at a steady, steady rate,” Dunham explained. In the decades to thousands of years between large earthquakes, mineral deposition and other chemical processes blocked the rift zone.

With the fault valve closed, fluid builds up and pressure builds up, weakening the fault and forcing it to slip. Sometimes this movement is so slight that it does not shake the ground, but is sufficient to break the rocks and open the valve, allowing the fluid to resume its ascent.

New modeling shows for the first time that when these pulses are transmitted upward along the fault, they can form seismic swarms. “The concept of a faulty valve, an intermittent release of fluid, is an old idea,” said Dunham. “But the occurrence of earthquake swarms in our fault valve simulations was completely unexpected.”

Expectations and their limits

The model provides quantitative predictions about the speed at which a high-pressure fluid pulse travels along the fault, opens the pores, leads to slipping and causes some phenomena: changes in lock depth, in some cases, slowing of fault movements or combinations of small earthquakes in other areas. These predictions can then be tested against actual seismic activity along the fault – in other words, when and where small or slow-moving earthquakes end up occurring.

For example, one set of simulations, in which the error was set to close and stop fluid transmission within three or four months, projected just over an inch of slipping along the fault around the lock depth directly over a year, with the cycle being repeated every A few years. This particular simulation closely matches the patterns of the so-called slow-slip events observed in New Zealand and Japan – a sign that the basic operations and mathematical relationships embedded in the algorithm are on target. Meanwhile, simulations with the use of stamping over the years caused the depth of the lock to rise as pressure pulses rose higher.

Changes in lock depth can be estimated from GPS measurements of ground surface deformation. However, Dunham said the technology is not an indicator of earthquakes. This would require a more complete knowledge of the processes that affect fault slip, as well as information about particular fault geometry, stress, rock formation and fluid pressure, he explained, “at a level of detail that is impossible, given that most work takes place many miles underground. “.

Instead, the model offers a way to understand the processes: how changes in fluid pressure lead to slip faults; How sliding and sliding the crack breaks the rock and makes it more permeable; And how does this increased porosity allow fluid to flow more easily.

In the future, this understanding could help guide risk assessments related to ground fluid injection. According to Dunham, “The lessons we learned about how fluid flow pairs with frictional slip are applicable to naturally occurring earthquakes as well as induced earthquakes that occur in oil and gas reservoirs.”

Co-authors include Callie L Alison, an 18-year-old doctorate in geophysics and a postdoctoral fellow at the University of Maryland, and Yu Yon Yang, a doctoral student in computational and mathematical engineering at Stanford University.

This research was supported by the National Science Foundation and the Southern California Earthquake Center.

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