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Geometrical features of fractures such as size (length) distribution exert fundamental control on the seismic-thermal-hydraulic-mechanical processes in the Earth’s crust. However, characterization of fracture network at depth remains a major challenge. This limits placing constraints on the statistical relationship between fracture network and injection-induced seismic hazard during underground fluid injection operations. Here, we propose a methodology to integrate borehole data, outcrop analogues and computer simulations to constrain the fractal Discrete Fracture Network (DFN) model of the target rock mass. The method allows a direct comparison with recorded microseismic events. We applied the proposed methodology to the Basel Enhanced Geothermal System (EGS), Switzerland, and found that rupture size distribution exhibits higher power-law exponents than fracture size distribution. This can indicate that larger fractures are prone to partial rather than complete rupture due to pore-pressure increase. To quantify hazard, we developed a novel maximum possible magnitude <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="italic">max</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> model, combining a dual power-law DFN model with the characteristic length of pore-pressure diffusion. The approach assumes a conservative, worst-case scenario in which the largest critically stressed fault governs the seismic hazard. The derived formulation can be calibrated to any specific site, provided that the fracture network and the hydrogeological conditions of the subsurface system are well-characterized. To account for parameter uncertainties, Monte Carlo simulations can be performed to estimate both the possible range and the most probable value of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>max</mml:mtext> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> . The methodology was successfully tested on the Basel site, providing <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m3"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>max</mml:mtext> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> of 3.4, in a close agreement with the observed <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m4"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>w</mml:mtext> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> 3.2. This framework provides a physics-based tool for seismic hazard assessment in engineered subsurface projects including EGS, geological <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m5"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mtext>CO</mml:mtext> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and Hydrogen storage.