The ability to accurately simulate and optimize fully integrated oil and gas fields is of critical importance in the development and operation of an asset. To this end, a novel and comprehensive framework for simulating fields comprised of connected reservoirs, wells, and production facilities is presented. Individual field components may be connected to each other through physical equipment such as pipes, and operations may be subject to field-wide constraints, such as limits on total production of green house gases. The proposed framework allows for simulation of the evolution of such a field, optimization of the field under various constraint choices, and planning and scheduling of the entire field operations. The framework is founded on representing each component using appropriate sets of Models, Equations and Variables (MEV) combined with a common Physical Property Manager that ensures a consistent calculation methodology, and uses grid-level partitioning to support parallelism. The MEV system operates in concert with customized nonlinear and linear equation solvers to generate updated values for variables in all the different sub-systems, regardless of their originating component. Optimizers in the system manipulate the same variables employed in the MEV solution process to assemble objective functions, act on decision variables, and satisfy constraints. These variables may also be parameterized to support uncertainty analysis or design possibilities. The componentized nature of the equation set allows the ability to plug in alternate custom technologies to replace or augment capabilities. The framework supports multiple fidelities for modelling the components, and enables the use of different coupling styles between them. Choices range from using simple proxy models for certain components, to explicit one- and two-way coupling of more rigorous models, up to solving a fully coupled, detailed field representation. It will be demonstrated that this approach allows for efficient simulation of the combined systems under different constraints.