Reservoir Waterflood Residual Oil Saturation from Laboratory Tests
- J.J. Rathmell (Atlantic Richfield Co.) | P.H. Braun (Atlantic Richfield Co.) | T.K. Perkins (Atlantic Richfield Co.)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- February 1973
- Document Type
- Journal Paper
- 175 - 185
- 1973. Society of Petroleum Engineers
- 1.6.9 Coring, Fishing, 5.2.2 Fluid Modeling, Equations of State, 1.11 Drilling Fluids and Materials, 5.4.1 Waterflooding, 5.2 Reservoir Fluid Dynamics, 4.1.5 Processing Equipment, 1.2.3 Rock properties, 5.1 Reservoir Characterisation, 4.1.9 Tanks and storage systems, 5.6.2 Core Analysis, 1.10 Drilling Equipment, 4.1.2 Separation and Treating, 5.5.2 Core Analysis, 5.2.1 Phase Behavior and PVT Measurements, 2.4.3 Sand/Solids Control, 5.7.2 Recovery Factors, 5.3.4 Reduction of Residual Oil Saturation, 4.6 Natural Gas
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Core oil saturations routinely determined by retort distillation can be used to evaluate waterflooding residual oil saturation. The cores must be taken with water-base muds having a filtrate loss in excess of 5 cc at bottom-hole conditions, and the surface oil saturation of the cores must be adjusted for the bleeding and shrinkage that occur during lifting.
Waterflooding is usually the process chosen for secondary oil recovery. Most tertiary oil recovery prospects are in reservoirs that either have been or are prospects are in reservoirs that either have been or are being waterflooded. The principal role of the tertiary process is then to recover oil that is left in a process is then to recover oil that is left in a waterflooded reservoir. Tertiary processes often feature the injection of fluids having higher mobilities than water. Examples of such fluids are lean gas, rich gas, LPG, CO2, and air. Even when water is injected with such fluids, vertical and horizontal sweep efficiency normally does not exceed that for water. Tertiary processes can usually at best recover the oil left in processes can usually at best recover the oil left in the water-swept region; that is, residual oil to waterflooding. An accurate knowledge of the residual oil saturation is imperative for reliably evaluating the economic success of a tertiary recovery process. Because uncertainties in waterflood sweep efficiency make residual oil saturation difficult to evaluate with an oil material balance on the reservoir, a technique that measures that saturation in situ is desirable. Among the various techniques that have been proposed are the following: 1. Measuring in situ with logs, 2. Measuring the oil content of cores taken with the pressure core barrel from the water-swept region, 3. Measuring the oil content of cores that have been cut using a water-base mud but depressured during lifting, and 4. Waterflooding in the laboratory.
This paper presents the results of a theoretical and experimental study of Methods 3 and 4. First, we consider the factors that affect the result of laboratory waterfloods, using previously published information and our own experimental results, and we arrive at a preferred technique for such measurements. Second, we consider the factors that affect core oil saturation at the surface and arrive at a technique for adjusting this saturation to achieve a measure of waterflooding residual oil saturation. Finally, we compare residual oil saturation from these two sources. We generally find excellent agreement between residual saturation measured by our best laboratory waterflood technique and adjusted routine core oil saturations.
Factors Affecting Laboratory Waterflooding Residual Oil Saturations
Reservoir core samples must be judiciously selected for laboratory waterfloods to evaluate residual oil saturation. One may be guided in this selection from sandstone reservoirs by concepts of reservoir inhomogeneities. The first step in a study of reservoir inhomogeneities - the identification and classification of the major sand and shale units - is perhaps most important to sample selection for laboratory tests, Within a sand unit, variations in grain size and grain size distribution are usually small.
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