This paper address the modeling of crude oil operations in refineries assuming that all properties blend linearly Guidelines are given on how to generate a Resource Task Network superstructure that implicitly handles the complex logistics, while extending the scope of a well-known continuous-time formulation to variable recipe tasks with multiple input materials. The new single time grid formulation has the advantage of avoiding computationally inefficient big M constraints unline previously proposed unit-specific and priority-slot based models. Through the solution of a set of test problems from the literature, we show that the resulting mixed-integer nonlinear programs can be solved close to global optimality by the commerical solver GloMIQO for the objective of gross margin maximization but not for operating cost minimization. We also show that adopting a two-step MILP-NLP algorithm where the mixed-integer linear relaxation is derived from multiparametric disaggregation can reduce the optimality gap by orders of magnitude.