Curvature attributes are powerful tools for visualization and interpretation of structural features in seismic data. Such measures may highlight faults and subtle fractures that were not evident in amplitude data, providing important information to the interpreter to build the geological model of the area of interest. This paper presents a method for estimating volumetric curvature attributes in post-stack seismic data. Using amplitude volume, an horizon identifier attribute is computed, in order to represent seismic horizons as level surfaces. Thus, the gradient of this attribute provides a coherent estimate of volumetric normal field. Formulas for the calculation of curvature in implicit surfaces are used to compute several curvature attributes useful in the delineation and prediction of important stratigraphic features. Tests with synthetic and real data show that the proposed method is able to provide consistent estimates of attributes of curvature at low cost processing. Three horizon identifer attributes are evaluated: instantaneous phase, vertical derivative and ridge attribute.