Injectivity decline during brine reinjection poses a significant challenge in the geothermal industry, with reported cases of substantial injectivity reduction and in severe cases, complete well shutdown. Among the reasons behind these issues, chemical processes play a key role due to potential changes in the fluid properties throughout the operation cycle. When reinjected, the fluid with altered chemical composition mixes with in situ fluids, potentially triggering mineral precipitation, which can obstruct flow and reduce injectivity. To better characterize the mechanisms behind the mixing-induced mineral precipitation processes, we performed a series of core-flooding experiments combined with high-resolution imaging techniques. Our study focuses on the direct visualization of barite precipitation fronts in Berea sandstone and characterizes their spatial and temporal evolution under varying flow conditions. Pressure response and time-resolved 2D scanning were analyzed to capture real-time changes in the system, whereas post-experiment micro-CT scanning, electron microprobe analysis, and mass spectrometry were employed to examine the morphology and distribution of the mineral deposits. Our results highlight the critical role of flow velocities on the kinetics of mixing-induced precipitation and demonstrate how mineral accumulation may significantly reduce permeability. These findings provide valuable insights into the dynamics of mineral precipitation in porous media, highlighting the impact of flow conditions on formation damage in geothermal systems.

The number of geothermal operations worldwide has been actively growing over the last decades. To increase their efficiency, prevent reservoir depletion and avoid environmental issues, produced water is commonly reinjected. Despite these benefits of fluid reinjection, various clogging problems resulting in injectivity decline have been reported by field operators. Research on individual clogging mechanisms is published in various studies. However, fluid injectivity problems are still widely faced, leading to decreased overall productivity and even abandonment of some wells. Therefore, it is essential to better understand reasons of fluid pathway clogging processes and especially their interactions to efficiently predict and prevent them. In this research, we present a theoretical analysis of different clogging mechanisms. The influence of various parameters on different clogging mechanisms from existing experimental studies and field reports has been reviewed and summarized. Additionally, we compared these experimental literature concepts with a real case study of a running geothermal field facing clogging problems in the Netherlands. The study includes a detailed analysis of production data, as well as fluid and filter sample analyses. Results show correlation patterns between concentration changes of chemical species in the fluid, as well as influence of injection parameters (temperature, flow rate) on injectivity. The outcomes were compared to literature examples to generalize the conclusions. This will allow an improved understanding of processes occurring in geothermal fluids during fluid production and reinjection. As a next step of this research, more field data will be analyzed to identify similar trends and correlations as well as the interdependency of injectivity problems.

The primary goal of this study is to build new and integrated conceptual models for a high temperature field in Indonesia. Providing new data, combining models, visualizing them in 3D is significant to refine previous 2D traditional models, which are limited for reservoir characterization and wellplacement. During field utilization, constantly updating conceptual models helps to verify the pre-existing models and to renew spatial description of the geothermal system. The new geology models aim to refine the description of subsurface units, the fault models help to renew outdated knowledge on structures, temperature and hydrothermal models aim to eludicate new spatial temperature distribution, and geochemistry models serve to link structures with fluid chemistry. New and pre-exisiting subsurface datasets are investigated, processed in Leapfrog and interpreted integratively. The current geology model confirmed the dominant rock types in the Lahendong reservoir: breccia and andesite with a minor fraction of tuff. Also, it shows the spatial distribution of feed-zones with respect to the geological units. The new fault model revealed that the southern reservoir is more structurally controlled than the northern reservoir. A major thrust fault in the south has a vital role as a fluid pathway because the surrounding rocks have low porosity. The updated temperature models show no changes with respect to the temperature range of 250-350 oC compared to previous studies. However, the current model revealed that the southern reservoir still contains higher temperatures than the northern as evidently manifested by the dome-shape of temperature lines. Recent studies suggested local cooling in the southern reservoir, as suggested by the decline of temperatures around faults. The geochemistry model unveils barrier and conductor structures based on electrical conductivity of fluids The current models significantly improve the former subsurface knowledge/studies. They also support a better reservoir characterization and visualization in 3D. The models will be a proper basis for the onward numerical models to identify reservoir behavior in future production scenarios/ operation.