The overall objective of the ATLASS project is to reduce the number of unnecessary production wells within a hydrocarbon reservoir and increase the hydrocarbon recovery rate by identification of bypassed reserves. Sub- objectives to achieve this goal are: - To improve quantitative interpretation tools for time-lapse seismic data - To develop methods so that undrained sections of hydrocarbons can be identified - To improve placement of wells by using new time lapse analysing techniques - To estimate volumes of bypassed oil or gas - To provide guidelines on how to obtain precise information about production changes within a hydrocarbon reservoir - Ultimately to improve recovery factors and extraction of hydrocarbons. Existing techniques for gathering information on how a hydrocarbon reservoir is being drained are based on a mathematical model simulation. This model is continuously being updated as new wells are drilled into the reservoir. Seismic data is the most efficient tool to obtain reservoir information between wells, and if the acquisition of seismic data is repeated after some years of production, it is possible to interpret seismic changes in terms of production related effects. Some recent case studies (Duri, Gullfaks and Draugen) show that this qualitative interpretation (being able to discriminate between touched and untouched areas within the reservoir) technique has proved to be of commercial benefit to the actual fields. Some key results from the ATLASS project are: - A new method for removing acquisition footprints from 4D seismic data; - Method for discrimination between velocity and compaction changes; - A new method for removing water layer multiples from 4D seismic data; - Development of laboratory equipment for acoustic monitoring of long core flooding; - Methodology for combined use of 4C and streamer data; - Guidelines for how to assess uncertainties in quantitative time-lapse analysis; - New insight into key issues controlling the repeatability of 4D seismic data. Most of the above mentioned techniques have been tested on real field examples, with good results. This means that some of the key results obtained in the project already have been transferred into valuable results for the industry.