Similarity search in texts, notably biological sequences, has received substantial attention in the last few years. Numerous filtration and indexing techniques have been created in order to speed up the resolution of the problem. However, previous filters were made for speeding up pattern matching, or for finding repetitions between two sequences or occurring twice in the same sequence. In this talk, we present an algorithm called NIMBUS for filtering sequences prior to finding repetitions occurring more than twice in a sequence or in more than two sequences. NIMBUS uses gapped seeds that are indexed with a new data structure, called a bi-factor array, that is also presented in this paper. Experimental results show that the filter can be very efficient: preprocessing with NIMBUS a data set where one wants to find functional elements using a multiple local alignment tool such as GLAM, the overall execution time can be reduced from 10 hours to 6 minutes while obtaining exactly the same results.