Abstarct: Hydraulic fracturing, as one of the most effective well stimulation techniques, plays a pivotal role in enhancing the operational productivity of low-permeability reservoirs. However, the high costs associated with these operations necessitate rigorous pre-operational studies, such as numerical modeling and sensitivity analysis of influential parameters, to mitigate operational failure risks and optimize return on investment. In this regard, the present research aims to design and model hydraulic fracturing operations baxsed on real field data, focusing on the Sarvak Formation in the Ahvaz oilfield one of the key carbonate reservoirs in southwestern Iran characterized by low permeability. Utilizing reservoir pressure data, fluid properties, and well specifications obtained from the National Iranian South Oil Company (NISOC), along with the specialized FracPro software, this study establishes a precise frxamework for evaluating the impact of fracturing fluid type and injection rate patterns on fracture performance. It represents a practical step toward intelligent engineering decision-making for analogous wells. The primary objective of this research is to design and model hydraulic fracturing operations using authentic field data. The study concentrates on the Sarvak Formation in the Ahvaz oilfield, a critical carbonate reservoir in southwestern Iran that, due to its low permeability, requires advanced stimulation techniques such as hydraulic fracturing to optimize hydrocarbon recovery. In such reservoirs, precise fracturing design is essential for improving production efficiency. The data employed including reservoir pressure, fluid properties, and specifications of the selected well were sourced from NISOC and modeled in the specialized FracPro software. Four baxseline scenarios were designed and evaluated baxsed on various combinations of fracturing fluids (linear fluids and crosslixnked gels) and injection rate patterns (constant and ramped). Additionally, a black-box optimization algorithm was implemented to identify the optimal parameter combination. Results revealed that Scenario 1 (constant-rate injection with linear fluid) generated the longest fracture length (102.5 ft) but the lowest conductivity, whereas Scenario 3 (ramped injection with the same fluid) produced the shortest length (87.7 ft) alongside the highest conductivity (391 mD·ft). These differences indicate that linear fluids, when injected at a constant rate, create longer but narrower fractures, while ramped injection yields wider and more conductive fractures. Scenario 4 (S4) achieved the best balance between length and conductivity. The black-box algorithmic optimization recommended a thermally stable fluid combined with a gradual ramped injection rate pattern as the superior strategy for similar carbonate reservoirs.