Modern oil and gas extraction faces challenges, notably from the surplus of produced water, hampering hydrocarbon recovery and raising environmental and economic concerns. A promising solution is the injection of preformed particle gels (PPGs) into the reservoir's fractures and high permeability zones, facilitating production processes. This study introduces a novel class of inorganically cross-linked PPGs with exceptionally high swelling capacities, comprising sulfonated polyacrylamide crosslinked with aluminum attached to acetate, nitrate, sulfate, and lactate anions individually. These PPGs function as superabsorbents, capable of absorbing water at a ratio of 100−700 times their dry weight while maintaining adequate gel strength up to 2709 Pa. The study examines the influence of anionic groups attached to the aluminum on the swelling ratio, kinetics, and strength of the developed PPGs. It also reveals the impact of reservoir conditions, including temperature, salinity, and pH. The research explores the chemical compositions and cross-linking mechanisms by employing Fourier transform infrared spectroscopy (FTIR) spectroscopy and scanning electron microscopy (SEM) techniques. Thermogravimetric analysis (TGA) experiments further examine thermal stability. Results highlight the significant influence of anionic groups on PPG performance, with aluminum lactate providing the most robust and stable network structure, followed by aluminum sulfate, aluminum nitrate, and aluminum acetate, which offer the highest swelling PPG but are most sensitive under saline and diverse conditions. Notably, aluminum-based PPGs exhibit slow swelling kinetics, taking over 5 h. Furthermore, results showed that high cross-linker concentrations and increased salinity are associated with decreased PPG swelling ratios but enhanced mechanical strength. It is worth noting that PPG swelling and strength thrive within the pH range of 5−9 and below temperatures exceeding 75 °C, as conditions beyond these thresholds compromise their intricate three-dimensional (3D) network structures.