Skeletonization has been a part of morphological image processing for a wide variety of applications. The skeleton is important for object representation in different topics, such as image retrieval and computer graphics, character/pattern recognition and analysis of biomedical images. The purpose of the present work is to apply a sequential skeletonization algorithm on geophysical images, resulting from shallow depth mapping of archaeological sites. The accurate identification of curvilinear structures in geophysical images plays an important role in geophysical interpretation and the detection of subsurface structures. Experimental results on real data show that skeletonization comprises an important tool in image interpretation.