This paper investigates the modeling method for optimizing well cluster wellhead target allocation and proposes a solution based on an improved shuffled frog leaping algorithm. Aiming to minimize the total horizontal displacement of targets and considering the requirement that the wellhead-to-target segments on the horizontal plane should intersect as little as possible, an optimization model for wellhead target allocation is established. The improved shuffled frog leaping algorithm is introduced, which includes steps such as randomly generating the initial frog population, memetic grouping, local search, and global search to optimize the wellhead target allocation scheme. Finally, using a large well cluster at a specific well site as an example, the wellhead target allocation is solved using both the ant colony algorithm and the improved shuffled frog leaping algorithm. The performance of the two algorithms is compared in terms of average horizontal displacement per well, average program running time, number of iterations, and the number of intersections of wellhead-to-target lines.