Using mathematical morphology in an attribute workflow to improve the interpretability of salt bodies in the Gulf of Mexico

Source abstract

Seismic attributes such as Gray Level Co-occurrence Matrix (GLCM) are well established as tools for interpreting seismic data through manual, automated, and quantitative methods. However, since most attributes are based upon a calculation window, many have difficulty in accurately localizing boundaries of geological bodies. Such limitation can often be mitigated through the use of smaller calculation windows. Unfortunately, smaller windows often lead to increased instability resulting in increased variability within a given facies type. In this abstract, we propose the use of mathematical morphology to reduce the variance of seismic attributes