Analyzing the success of recent enhanced geothermal systems (EGS) projects such as the Frontier Observatory for Research in Geothermal Energy (FORGE), Red and Cape Stations, key findings such as circulation rate dependence on the size of the stimulated volume and networks are evident. This paper proposes some optimization aspects at the scale of each fracture and completion scheme at large. Four aspects are modeled and explored: 1. High Temperatures and Proppant Transport: High temperatures lead to lower viscosities and significantly accentuates proppant settling and sand duning ; hence, the transport of lightweight proppant is considered. 2. Polylactic Acid-Based Degradable Fiber: The use of polylactic acid-based degradable fiber in proppant slurry can lower friction pressure and enhance proppant transport. Both these aspects are critical for uniform fracture conductivity and effective heat exchange. These processes have been modeled using a novel multiphysics particle-in-cell slurry flow model, which tracks mass loss-based degradation and digitized material profiles. 3. Thermoelastic Stress Alterations: The impact of thermoelastic stress alterations during fracturing has been given less importance due to the fracturing fluid cooling down the temperature transient. A conceptual model, issues related to accurately scaling up this physics in numerical models, and the criticality of embedding these effects in the fracturing phase for EGS models is discussed . 4. Other considerations: Other critical considerations such as the proppant demobilization impact, geochemical processes coupling framework, choice of proppant, etc. have been discussed. All numerical modeling is conducted on a calibrated FORGE stress and leakoff model with accurate structural dip. The considerations are expected to provide multiple answers for various optimization phases in the recent future of EGS, not just in hot-dry-rock scenarios but also in slightly permeable basement rock scenarios such as the eastern part of North America and Asia. Cost analysis for optimization has also been presented where required.

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