Offshore oil and gas exploration companies frequently need to deal with problems related to the efficient use of their resources. In this work, we address a ship scheduling problem associated with offshore oil and gas logistics. The problem can be seen as a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. In this analogy, vessels represent the available machines that must perform tasks in subsea oil wells, and batches are voyages executed by the vessels, defining which wells to visit each time it leaves the port. We developed a simheuristic using embedded Monte Carlo simulation for the stochastic variant of the problem. The results show a significant improvement in the solutions dealing with uncertainties compared to solutions generated by a deterministic method. The use of simulation within a metaheuristic framework proved to be a promising approach, being able to deal with the stochastic problem, with little extra computational effort required.