# title
On the Impact of Clogging in Aquifer Thermal Energy Storage (ATES) under Constant-Rate and Constant-Head Injection-Extraction Scenarios

# abstract
Aquifer thermal energy storage (ATES) offers a promising approach for seasonal energy storage and decarbonization of heating and cooling systems. However, with long-term injection-extraction operations, well clogging often occurs due to various reasons, including the presence of suspended solids and chemical precipitation. Therefore, the temperature distribution and recovery efficiency of ATES systems can be adversely affected by clogging. This study investigates a two-zone confined aquifer system using a combination of analytical solutions and high-resolution numerical simulations conducted in COMSOL Multiphysics. Scenarios with and without clogging are evaluated under constant-rate and constant-head injection-extraction conditions. Results show that clogging significantly alters hydraulic head distributions, with steep hydraulic gradients forming near the well under both injection modes. In the constant-rate injection case, although the well injection pressure and hydraulic gradient near the well will rise in the clogging case due to the reduced permeability of the clogging zone, the Darcian velocities remain the same in the clogging and non-clogging cases if the same injection rate is maintained for both cases, resulting in minimal differences in thermal transport and recovery efficiency. In contrast, constant-head injection is highly sensitive to clogging, as reduced hydraulic conductivities lead to lower flow rates, smaller thermal plumes, greater heat losses, and a measurable decline in recovery efficiency over 15years. This study underscores the critical importance of accurately representing near-well hydraulic conditions in ATES modeling. It provides new insights into how operational strategies and subsurface near-well clogging influence thermal energy recovery, offering practical guidance for the design, control, and optimization of resilient ATES systems.

# authors[].organizations[].label
Texas A&M Engineering Experiment Station (TEES)