TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractOptimum management of oil and gas reservoirs is a continuous, iterative process which encompasses monitoring the reservoir, interpreting the monitoring data, and deciding from the results how best to continue reservoir development and executing those decisions. Monitoring data vary widely in time and space scales.Temporally, they range from continuous to infrequent, episodic measurements; spatially, they range from local well-centric to global reservoir measurements.The reservoir management workflow similarly operates at multiple, parallel time-space scales. A "fast" workflow loop handles continuous well and surface network data (e.g. pressure, temperature, and rate), using fast data handling and fast decision-making to optimize hydrocarbon delivery. A "slow" workflow loop assimilates episodic reservoir data (e.g. time-lapse seismic and borehole reservoir measurements) to optimize reservoir drainage.Reservoir monitoring data are assimilated at the most appropriate time into the reservoir shared earth model, which feeds both the "fast" and "slow" workflow loops. A continuing industry challenge is to determine the best way to do this, since the types of monitoring data are diverse and the volume of data to assimilate is often vast.This paper begins with a review of reservoir monitoring data that are available today, with a focus on the range of time-space scales. A reservoir management workflow is introduced which has multiple time scales appropriate for these data. The paper concludes with a review of key challenges: (1) to develop improved interpretation technologies to unify and integrate the fast well-network centric and slow reservoir-centric workflow loops for faster conversion of measurement signals into information, and (2) to provide fuller support for uncertainties, including determining how the level of uncertainty in the reservoir model changes when assimilating monitoring data.