Water flooding has been used successfully in heavy and viscous oil fields since last fifty years. Though characterized by low recoveries and high cost due to adverse mobility ratio, waterflood is still an attractive option before embarking on expensive EOR solutions. One of the key elements to success of waterfloods in heavy oil is well and reservoir management. This paper illustrates the use of daily production data to set up systems that indicate the health of waterflood through use of classical techniques so that they are readily available on a demand to know basis for any hierarchy of production systems; field pattern, groups, individual patterns etc. The observations and results can then be applied to take proactive measures for preventive management. To manage water floods in a dynamic scenario, reservoir engineers need to watch them closely, analyze them for anomalous behavioral trends in a continuous fashion and be able to apply remedial measures as they manifest themselves. This can not be done through numerical simulation models, first, because of the high cost and time constraints and secondly because the models usually are highly simplified and are constructed using an average property data. Numerous techniques have been developed by various people working on waterfloods around the world in last 4 decades. Most of these techniques are in the form of diagnostic plots based on easily available data. This paper is an effort to put many such methodologies in a structured format which will enable the engineer to monitor the floods in a systematic and step wise manner. It is intended to move personnel involved in waterfloods up a learning curve and provide them with a toolset to not only measure but improve the flood efficiency. It will assist reservoir engineer's production technologists and development geologists who are involved in or are contemplating waterflood operations. Introduction Reservoirs communicate with engineers through production data. This language, if interpreted correctly can lead the engineer to understand the sub-surface flow process and thereby improve the efficiency of the system. This paper uses only production data with general use software applications like spreadsheet/ data base systems etc to develop tools that help the engineer to understand the message of reservoirs. The paper reviews and explains in detail along with application on live data, techniques to estimate volumetric sweep efficiency, prediction of pressure response (using net voidage), interpretation of injection behavior (Hall's Plot), predicting water source in a oil producer (WOR techniques), using heterogeneity index to priorities options and prediction of ultimate recovery through X-plot calculations and a host of minor techniques that help in understanding & visualization of waterflood behavior.
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