Beo v1.0: numerical model of heat flow and low-temperature thermochronology in hydrothermal systems

Abstract

Abstract. Low-temperature thermochronology can provide records of the thermal history of the upper crust and can be a valuable tool to quantify the history of hydrothermal systems. However, existing model codes of heat flow around hydrothermal systems do not include low-temperature thermochronometer age predictions. Here I present a new model code that simulates thermal history around hydrothermal systems on geological timescales. The modelled thermal histories are used to calculate apatite (U–Th)∕He (AHe) ages, which is a thermochronometer that is sensitive to temperatures up to 70 ∘C. The modelled AHe ages can be compared to measured values in surface outcrops or borehole samples to quantify the history of hydrothermal activity. Heat flux at the land surface is based on equations of latent and sensible heat flux, which allows more realistic land surface and spring temperatures than models that use simplified boundary conditions. Instead of simulating fully coupled fluid and heat flow, the code only simulates advective and conductive heat flow, with the rate of advective fluid flux specified by the user. This relatively simple setup is computationally efficient and allows running larger numbers of models to quantify model sensitivity and uncertainty. Example case studies demonstrate the sensitivity of hot spring temperatures to the depth, width and angle of permeable fault zones, and the effect of hydrothermal activity on AHe ages in surface outcrops and at depth.

Long-wavelength late-Miocene thrusting in the north Alpine foreland: implications for late orogenic processes

“…Paleo-heat flux is notoriously difficult to constrain (Louis et al, 2019). However, as shown from a compilation of geothermal springs within the Alps, heat flux variations are spatially localized (Luijendijk et al, 2020). Consequently, this should be reflected in local outliers within the data set, for instance a suite of very young ages within a region.…”

Heat Flow Transport Model by Gauss-Seidel Type Iteration Methods for Gas and Solid Materials

“…The high value of conduction from the gas materials, whereas metal material shows the low value of conduction may due to the distance between the atomic is close to each other (Lu et al, 2020). The equation (10 and 11) clearly shows that the high thermal conductivity coefficient values will produce high heat flow for conduction and for convection process (Luijendijk, 2019). The convection process strongly depends on the convection coefficient (h), as shown in equation 6, which may due to the molecular properties of materials (Defraeye, Blockenc, & Carmeliet, 2013).…”

Determining the Lifespan of Hydrothermal Systems Using Thermochronology and Thermal Modeling

“…Hydrothermal modeling was completed using a combination of Beo v1.0 (Luijendijk, 2019) and QTQt (Gallagher, 2012). Beo v1.0 models for advective and conductive heat flow along a fault plane, providing thermal histories for any point within a defined finite element mesh (Figure 3) (Luijendijk, 2019), replicating fluid flow along a fault and generating thermal histories for points within the surrounding bedrock (Figure 3). Variables such as fault angle, fluid flux, exhumation rate and surface temperature can be altered or added to allow realistic systems to be constructed (Figure 3).…”

“…Following the end of compression in the Paleocene, the Omineca belt has been in a state of extension, underlain by a thin lithosphere and high surface heat flux (Fraser et al, 2021;Parrish et al, 1988). The RMT acts as (Luijendijk, 2019). The approach models advective and conductive upwards heat flow along a single fault plane and within a defined finite element mesh (Luijendijk, 2019).…”

“…Our pilot study shows that modeling results are consistent with the observed thermochronological data and long-term hot spring activity at CRHS is required to affect the thermochronometric systems measured. Our approach could be improved if a multi-sample transect study was implemented (Louis et al, 2019;Luijendijk, 2019). Future studies of hot springs should incorporate sampling at various locations and distances from the spring to improve the modeling, something that was not possible here due to the lack of exposed bedrock (debris and heavy vegetation).…”