  Minimum miscibility pressure (MMP) prediction plays an important role in
design and operation of nitrogen based enhanced oil recovery processes. In this
work, a comparative study of statistical and machine learning methods used for
MMP estimation is carried out. Most of the predictive models developed in this
study exhibited superior performance over correlation and predictive models
reported in literature.
