Bubble accumulation and its role in the evolution of magma reservoirs in the upper crust

Abstract

Volcanic eruptions transfer huge amounts of gas to the atmosphere. In particular, the sulfur released during large silicic explosive eruptions can induce global cooling. A fundamental goal in volcanology, therefore, is to assess the potential for eruption of the large volumes of crystal-poor, silicic magma that are stored at shallow depths in the crust, and to obtain theoretical bounds for the amount of volatiles that can be released during these eruptions. It is puzzling that highly evolved, crystal-poor silicic magmas are more likely to generate volcanic rocks than plutonic rocks. This observation suggests that such magmas are more prone to erupting than are their crystal-rich counterparts. Moreover, well studied examples of largely crystal-poor eruptions (for example, Katmai, Taupo and Minoan) often exhibit a release of sulfur that is 10 to 20 times higher than the amount of sulfur estimated to be stored in the melt. Here we argue that these two observations rest on how the magmatic volatile phase (MVP) behaves as it rises buoyantly in zoned magma reservoirs. By investigating the fluid dynamics that controls the transport of the MVP in crystal-rich and crystal-poor magmas, we show how the interplay between capillary stresses and the viscosity contrast between the MVP and the host melt results in a counterintuitive dynamics, whereby the MVP tends to migrate efficiently in crystal-rich parts of a magma reservoir and accumulate in crystal-poor regions. The accumulation of low-density bubbles of MVP in crystal-poor magmas has implications for the eruptive potential of such magmas, and is the likely source of the excess sulfur released during explosive eruptions.

The origin of a zoned ignimbrite: Insights into the Campanian Ignimbrite magma chamber (Campi Flegrei, Italy)

“…10), particularly in this volatile-rich environment where bubbles tend to accumulate in the crystal-poor zone (e.g. Parmigiani et al, 2016). The crystalpoor cap fed the initial stages of the eruption characterized by a plinian phase, which deposited fallout layers (PPF), followed by the development of pyroclastic density currents generating the main ignimbritic body (LPFU, WGI).…”

Generalized three-dimensional lattice Boltzmann color-gradient method for immiscible two-phase pore-scale imbibition and drainage in porous media

“…Multiphase fluid flows in porous media finds its application in several environmental and industrial fields, such as dense, nonaqueous phase liquid (DNAPL) soils decontamination [1], CO2 storage in natural porous reservoirs [2], enhanced oil recovery [3], and migration of volcanic gas in evolved magmatic systems [4,5].…”

From magma ascent to ash generation: investigating volcanic conduit processes by integrating experiments, numerical modeling, and observations

“…Moreover, dike pathways through the crust may not be vertical and may not coincide with pre-existing weaknesses in the host rock as is often assumed . Dike pathways are often tortuous as evidenced by recent studies [Bagnardi et al 2013] and strongly influenced by the distribution of surface loads [Maccaferri et al 2014, Corbi et al 2015, layering [Rivalta et al 2005, Maccaferri et al 2010 and faulting [Passarelli et al 2015. In addition to this, there are problems with the terminology used to define magma chambers: there is confusion when we refer to what different techniques are detecting at different time scales.…”

“…In order to advance the comprehension of the processes occurring at the microscale and how these processes govern the macroscale dynamics of the eruption, all modelers agreed that the following processes, parameters and properties need an improved description to model conduit magma ascent: bubble and crystal shapes, size distributions, nucleation, growth, deformation, degassing, permeability, rheology, reservoir (magma chamber)/conduit size and geometry and elastic response of the host rock. One can study these microscale processes by using novel numerical methods [Parmigiani et al 2016] or the technological advances that allow 4D experiments [Fife et al 2012]. In theory, the use of population balance equations allows us to describe some of the relevant microscale processes at the macroscopic scale, but the computational costs for this approach are extremely high.…”