Main parameters characterizing water flooded reservoir performance are displaced recoverable oil reserves and composite water-oil ratio, and these must be considered for a justified estimate of base oil production. In practice, to estimate displaced recoverable oil reserves, oil-displacement-by-water characteristics based on mathematical relationships are used.
In this work, the authors demonstrate how to use a widely known empirical method of oil displacement characteristics for interval and probabilistic estimates of displaced recoverable oil reserves. The objective was to create a simple, easy-to-understand, reliable, and computerizable tool to estimate displaced recoverable oil reserves by wells, and to forecast oil production in mid- and long-term.
It is well known that oil and fluid production, and water cut may fluctuate in different periods. This complicates building mathematical relationships and decreases reliability of estimates. The paper discloses some of the factors that may contribute to these fluctuations: change of wells’ operation conditions, seasonal changes (well performance in warm and cold seasons), oil enhancement operations in the well under consideration or in neighboring production and injection wells, increase of water cut resulting from oil drainage process, downhole failures, etc.
It should be noted that most of Tatneft assets have entered closing stage of development, and sustained oil production is only possible due to a large number of different EOR/IOR jobs. This is the reason why the curve characterizing the oil displacement process is not strictly linear.
To smooth data in these cases, yearly well performance data rather than monthly well performance are used, which usually results in data roughening and, consequently, decreases reliability of well performance estimates.
To be able to forecast well performance in the long term, one must estimate displaced oil reserves performance for the recent period and for a lengthier period (1-3 years).
To do this, the authors suggest using a probabilistic method providing for an interval estimate of change of displaced oil reserves, and for a statistic estimate of probable displaced reserves (Р90/Р50/Р10 estimates).
The authors offer three basic approaches to select probable displaced oil reserves to be used for further forecast of base oil production: to be limited to the most probable (Р90), less probable (Р50), or the least probable (Р10) scenario; to be guided by the largest value of displaced oil reserves distribution density in the interval under consideration, and to combine both approaches.
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