The paper considers nonparametric empirical Bayes estimation of residual survival function at age t using a Dirichlet process prior V(a). Empirical Bayes estimators are proposed for the case where both the function ${alpha}$(0, $chi$] and the size a(R$^$+/) are unknown. It is shown that the proposed empirical Bayes estimators are asymptotically optimal at a rate n$^$-1/, where n is the number of past data available for the present estimation problem. Therefore, the result of Lahiri and Park (1988) in which a(R$^$+/) is assumed to be known and a rate n$^$-1/ is achieved, is extended to a(R$^$+/) unknown case.