Seismic data have been established as a valuable source of information for the construction of reservoir simulation models, most commonly for determination of the modeled geologic structure, and also for population of static petrophysical properties (e.g. porosity, permeability). More recently, the availability of repeated seismic surveys over the time scale of years (i.e., 4D seismic) has shown promising results for the qualitative determination of changes in fluid phase distributions and pressure required for determination of areas of bypassed oil, swept volumes and pressure maintenance mechanisms. Quantitatively, and currently the state of the art in reservoir model characterization, 4D seismic data have proven distinctively useful for the calibration of geologic spatial variability which ultimately contributes to the improvement of reservoir development and management strategies. Among the limited variety of techniques for the integration of dynamic seismic data into reservoir models, streamline-based techniques have been demonstrated as one of the more efficient approaches as a result of their analytical sensitivity formulations. Although streamline techniques have been used in the past to integrate time-lapse seismic attributes, the applications were limited to the simplified modeling scenarios of two-phase fluid flow and invariant streamline geometry throughout the production schedule. This research builds upon and advances existing approaches to streamline-based seismic data integration for the inclusion of both production and seismic data under varying field conditions. The proposed approach integrates data from reservoirs under active reservoir management and the corresponding simulation models can be constrained using highly detailed or realistic schedules. Fundamentally, a new derivation of seismic sensitivities is proposed that is able to represent a complex reservoir evolution between consecutive seismic surveys. The approach is further extended to manage compositional reservoir simulation with dissolution effects and gravity-convective-driven flows which, in particular, are typical of CO2 transport behavior following injection into deep saline aquifers. As a final component of this research, the benefits of dynamic data integration on the determination of swept and drained volumes by injection and production, respectively, are investigated. Several synthetic and field reservoir modeling scenarios are used for an extensive demonstration of the efficacy and practical feasibility of the proposed developments.