Dependence of Waterflood Remaining Oil Saturation on Relative Permeability, Capillary Pressure, and Reservoir Parameters in Mixed-Wet Turbidite Sands

1996 ◽  
Vol 11 (02) ◽  
pp. 87-92 ◽  
Author(s):  
G.J. Hirasaki
2020 ◽  
Vol 10 (8) ◽  
pp. 3649-3661
Author(s):  
Meiling Zhang ◽  
Jiayi Fan ◽  
Yongchao Zhang ◽  
Yinxin Liu

Abstract The water cutting rate is recorded dynamically during the production process of a well. If the remaining oil saturation of the reservoir can be deduced based on the water cutting rate, it will give guidance to improve the reservoir recovery and can save expensive drilling costs. In the oil–water two-phase seepage experiment on core samples, the oil and water relative permeability reflects the relationship between the water cutting rate and water saturation, that is, percolating saturation formula. The relative permeability test data of 17 rock samples from six seal coring wells in Daqing Changyuan were used to optimize and construct the coefficients of the index percolating saturation formula that vary with the pore structure parameters of reservoirs, to form an index percolating saturation formula with variable coefficients that is more consistent with the regional geological characteristics of the reservoir. Based on this, the formula of water saturation calculated by the water cutting rate is deduced. And the high-precision formula for calculating the irreducible water saturation and residual oil saturation by effective porosity, absolute permeability, and shale content is given. The derivative formula of water saturation on the water cutting rate was established, and the parameters of 17 rock samples were calculated. It was found that the variation velocity of water saturation of each sample with the water cutting rate presented a “U” shape, which was consistent with the actual characteristics that the variation velocity of the water saturation in the early, middle, and late stages of oilfield development first decreased, then stabilized, and finally increased rapidly. The research results were applied to the prediction of remaining oil saturation in the research area, and the water saturation about six producing wells was calculated by using their present water cutting rates, and the remaining oil distribution profile was predicted effectively. The analysis of four layers of two newly drilled infill wells and reasonable oil recovery suggestions were given to achieve good results.


2007 ◽  
Vol 10 (02) ◽  
pp. 191-204 ◽  
Author(s):  
Shehadeh K. Masalmeh ◽  
Issa M. Abu-Shiekah ◽  
Xudong Jing

Summary An oil/water capillary transition zone often contains a sizable portion of a field's initial oil in place, especially for those carbonate reservoirs with low matrix permeability. The field-development plan and ultimate recovery may be influenced heavily by how much oil can be recovered from the transition zone. This in turn depends on a number of geological and petrophysical properties that influence the distribution of initial oil saturation (Sor) against depth, and on the rock and fluid interactions that control the residual oil saturation (Sor), capillary pressure, and relative permeability characteristics as a function of initial oil saturation. Because of the general lack of relevant experimental data and the insufficient physical understanding of the characteristics of the transition zone, modeling both the static and dynamic properties of carbonate fields with large transition zones remains an ongoing challenge. In this paper, we first review the transition-zone definition and the current limitations in modeling transition zones. We describe the methodology recently developed, based on extensive experimental measurements and numerical simulation, for modeling both static and dynamic properties in capillary transition zones. We then address how to calculate initial-oil-saturation distribution in the carbonate fields by reconciling log and core data and taking into account the effect of reservoir wettability and its impact on petrophysical interpretations. The effects of relative permeability and imbibition capillary pressure curves on oil recovery in heterogeneous reservoirs with large transition zones are assessed. It is shown that a proper description of relative permeability and capillary pressure curves including hysteresis, based on experimental special-core-analysis (SCAL) data, has a significant impact on the field-performance predictions, especially for heterogeneous reservoirs with transition zones. Introduction The reservoir interval from the oil/water contact (OWC) to a level at which water saturation reaches irreducible is referred to as the capillary transition zone. Fig. 1 illustrates a typical capillary transition zone in a homogeneous reservoir interval within which both the oil and water phases are mobile. The balance of capillary and buoyancy forces controls this so-called capillary transition zone during the primary-drainage process of oil migrating into an initially water-filled reservoir trap. Because the water-filled rock is originally water-wet, a certain threshold pressure must be reached before the capillary pressure in the largest pore can be overcome and the oil can start to enter the pore. Hence, the largest pore throat determines the minimum capillary rise above the free-water level (FWL). As shown schematically in Fig. 2, close to the OWC, the oil/water pressure differential (i.e., capillary pressure) is small; therefore, only the large pores can be filled with oil. As the distance above the OWC increases, an increasing proportion of smaller pores are entered by oil owing to the increasing capillary pressure with height above the FWL. The height of the transition zone and its saturation distribution is determined by the range and distribution of pore sizes within the rock, as well as the interfacial-force and density difference between the two immiscible fluids.


SPE Journal ◽  
2019 ◽  
Vol 25 (01) ◽  
pp. 481-496 ◽  
Author(s):  
Pål Østebø Andersen

Summary Many experimental studies have investigated smart water and low-salinity waterflooding and observed significant incremental oil recovery after changes in the injected-brine composition. The common approach to model such enhanced-oil-recovery (EOR) mechanisms is by shifting the input relative permeability curves, particularly including a reduction of the residual oil saturation. Cores that originally display oil-wetness can retain much oil at the outlet of the flooded core because of the capillary pressure being zero at a high oil saturation. This end effect is difficult to overcome in highly permeable cores at typical laboratory rates. Injecting a brine that changes the wetting state to less-oil-wet conditions (represented by zero capillary pressure at a lower oil saturation) will lead to a release of oil previously trapped at the outlet. Although this is chemically induced incremental oil, it represents a reduction of remaining oil saturation, not necessarily of residual oil saturation. This paper illustrates the mentioned issues of interpreting the difference in remaining and residual oil saturation during chemical EOR and hence the evaluation of potential smart water effects. We present a mathematical model representing coreflooding that accounts for wettability changes caused by changes in the injected composition. For purpose of illustration, this is performed in terms of adsorption of a wettability-alteration (WA) component coupled to the shifting of relative permeability curves and capillary pressure curves. The model is parameterized in accordance with experimental data by matching brine-dependent saturation functions to experiments where wettability alteration takes place dynamically because of the changing of one chemical component. It is seen that several effects can give an apparent smart water effect without having any real reduction of the residual oil saturation, including changes in the mobility ratio, where the oil already flowing is pushed more efficiently, and the magnitude of capillary end effects can be reduced because of increased water-wetness or because of a reduction in water relative permeability giving a greater viscous drag on the oil.


Author(s):  
A. Syahputra

Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.


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