Residual Oil Saturation Prediction and Monitoring with Time-lapse, Multi-component Seismic Data, Delhi Field, Louisiana

2013 ◽  
Author(s):  
T.L. Davis ◽  
A. Bibolova ◽  
D. Klepacki ◽  
H. Robinson
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Residual Oil ◽  
Oil Saturation ◽  
Residual Oil Saturation

Prediction of residual oil saturation by using the ratio of amplitude attributes of time-lapse seismic data

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. IM1-IM12 ◽  
Author(s):  
Meng Li ◽  
Zhen Liu ◽  
Minzhu Liu ◽  
Huilai Zhang
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Seismic Interpretation ◽  
Impedance Change ◽  
Residual Oil ◽  
Data Set ◽  
Oil Saturation ◽  
Residual Oil Saturation ◽  
Amplitude Difference ◽  
Fluid Saturation

Subtraction of baseline and monitoring seismic data is a common step in highlighting reservoir changes in time-lapse seismic interpretation. However, ambiguity exists in the interpretation of the amplitude difference, which is controlled by fluid change and reservoir thickness. To estimate the residual oil saturation quantitatively, we have developed a time-lapse seismic interpretation method that uses the ratio of amplitude attributes extracted from the baseline and monitoring seismic data. The relationship between impedance change and the ratio of the baseline and monitoring amplitude attributes is determined to avoid the influence of reservoir thickness. Subsequently, the fluid saturation is calculated from the impedance change by using a proper petrophysical relationship. We have tested our new method on a real time-lapse seismic data set from a water-flooded reservoir in the deepwater area of West Africa. The water-flooded area determined from the amplitude difference does not completely match the production logs because of the influence of variations in the reservoir thickness. However, the residual oil distribution calculated with the proposed method matches the production logs well. The connectivity of sandstone bodies is also evaluated based on an integrated interpretation of estimated oil saturation. With its simple principles and easy accessibility, our method improves the accuracy of time-lapse seismic data interpretation in water-flooded oil reservoirs. Furthermore, the quantitative interpretation of fluid change enables the time-lapse seismic technology to guide reservoir development directly.

Prediction of residual oil saturation and cap-rock integrity from time-lapse, multicomponent seismic data, Delhi Field, Louisiana

2013 ◽  
Vol 32 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Thomas L. Davis ◽  
Assem Bibolova ◽  
Sean O'Brien ◽  
Doug Klepacki ◽  
Holly Robinson
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Residual Oil ◽  
Oil Saturation ◽  
Residual Oil Saturation ◽  
Multicomponent Seismic ◽  
Cap Rock

Relationship between Residual Saturations and Wettability using Pore-Network Modeling

2021 ◽  
Author(s):  
Prakash Purswani ◽  
Russell T. Johns ◽  
Zuleima T. Karpyn
Keyword(s):  
Contact Angle ◽  
Oil Recovery ◽  
Network Modeling ◽  
Pore Network ◽  
Residual Oil ◽  
Residual Saturation ◽  
Oil Saturation ◽  
Pore Network Modeling ◽  
Residual Oil Saturation ◽  
Eor Processes

Abstract The relationship between residual saturation and wettability is critical for modeling enhanced oil recovery (EOR) processes. The wetting state of a core is often quantified through Amott indices, which are estimated from the ratio of the saturation fraction that flows spontaneously to the total saturation change that occurs due to spontaneous flow and forced injection. Coreflooding experiments have shown that residual oil saturation trends against wettability indices typically show a minimum around mixed-wet conditions. Amott indices, however, provides an average measure of wettability (contact angle), which are intrinsically dependent on a variety of factors such as the initial oil saturation, aging conditions, etc. Thus, the use of Amott indices could potentially cloud the observed trends of residual saturation with wettability. Using pore network modeling (PNM), we show that residual oil saturation varies monotonically with the contact angle, which is a direct measure of wettability. That is, for fixed initial oil saturation, the residual oil saturation decreases monotonically as the reservoir becomes more water-wet (decreasing contact angle). Further, calculation of Amott indices for the PNM data sets show that a plot of the residual oil saturation versus Amott indices also shows this monotonic trend, but only if the initial oil saturation is kept fixed. Thus, for the cases presented here, we show that there is no minimum residual saturation at mixed-wet conditions as wettability changes. This can have important implications for low salinity waterflooding or other EOR processes where wettability is altered.

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