Sensitivity of time-lapse seismic data to pore pressure changes: Is quantification possible?

2005 ◽  
Vol 24 (12) ◽  
pp. 1250-1254 ◽  
Author(s):  
Ola Eiken ◽  
Richard Tøndel
Geophysics ◽  
2003 ◽  
Vol 68 (5) ◽  
pp. 1592-1599 ◽  
Author(s):  
Martin Landrø ◽  
Helene Hafslund Veire ◽  
Kenneth Duffaut ◽  
Nazih Najjar

Explicit expressions for computation of saturation and pressure‐related changes from marine multicomponent time‐lapse seismic data are presented. Necessary input is PP and PS stacked data for the baseline seismic survey and the repeat survey. Compared to earlier methods based on PP data only, this method is expected to be more robust since two independent measurements are used in the computation. Due to a lack of real marine multicomponent time‐lapse seismic data sets, the methodology is tested on synthetic data sets, illustrating strengths and weaknesses of the proposed technique. Testing ten scenarios for various changes in pore pressure and fluid saturation, we find that it is more robust for most cases to use the proposed 4D PP/PS technique instead of a 4D PP amplitude variation with offset (AVO) technique. The fit between estimated and “real” changes in water saturation and pore pressure were good for most cases. On the average, we find that the deviation in estimated saturation changes is 8% and 0.3 MPa for the estimated pore pressure changes. For PP AVO, we find that the corresponding average errors are 9% and 1.0 MPa. In the present method, only 4D PP and PS amplitude changes are used in the calculations. It is straightforward to include use of 4D traveltime shifts in the algorithm and, if reliable time shifts can be measured, this will most likely further stabilize the presented method.


SPE Journal ◽  
2010 ◽  
Vol 15 (04) ◽  
pp. 1077-1088 ◽  
Author(s):  
F.. Sedighi ◽  
K.D.. D. Stephen

Summary Seismic history matching is the process of modifying a reservoir simulation model to reproduce the observed production data in addition to information gained through time-lapse (4D) seismic data. The search for good predictions requires that many models be generated, particularly if there is an interaction between the properties that we change and their effect on the misfit to observed data. In this paper, we introduce a method of improving search efficiency by estimating such interactions and partitioning the set of unknowns into noninteracting subspaces. We use regression analysis to identify the subspaces, which are then searched separately but simultaneously with an adapted version of the quasiglobal stochastic neighborhood algorithm. We have applied this approach to the Schiehallion field, located on the UK continental shelf. The field model, supplied by the operator, contains a large number of barriers that affect flow at different times during production, and their transmissibilities are highly uncertain. We find that we can successfully represent the misfit function as a second-order polynomial dependent on changes in barrier transmissibility. First, this enables us to identify the most important barriers, and, second, we can modify their transmissibilities efficiently by searching subgroups of the parameter space. Once the regression analysis has been performed, we reduce the number of models required to find a good match by an order of magnitude. By using 4D seismic data to condition saturation and pressure changes in history matching effectively, we have gained a greater insight into reservoir behavior and have been able to predict flow more accurately with an efficient inversion tool. We can now determine unswept areas and make better business decisions.


Geophysics ◽  
2005 ◽  
Vol 70 (6) ◽  
pp. O39-O50 ◽  
Author(s):  
Øyvind Kvam ◽  
Martin Landrø

In an exploration context, pore-pressure prediction from seismic data relies on the fact that seismic velocities depend on pore pressure. Conventional velocity analysis is a tool that may form the basis for obtaining interval velocities for this purpose. However, velocity analysis is inaccurate, and in this paper we focus on the possibilities and limitations of using velocity analysis for pore-pressure prediction. A time-lapse seismic data set from a segment that has undergone a pore-pressure increase of 5 to 7 MPa between the two surveys is analyzed for velocity changes using detailed velocity analysis. A synthetic time-lapse survey is used to test the sensitivity of the velocity analysis with respect to noise. The analysis shows that the pore-pressure increase cannot be detected by conventional velocity analysis because the uncertainty is much greater than the expected velocity change for a reservoir of the given thickness and burial depth. Finally, by applying amplitude-variation-with-offset (AVO) analysis to the same data, we demonstrate that seismic amplitude analysis may yield more precise information about velocity changes than velocity analysis.


Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. WA135-WA148 ◽  
Author(s):  
Matthew Saul ◽  
David Lumley

Time-lapse seismology has proven to be a useful method for monitoring reservoir fluid flow, identifying unproduced hydrocarbons and injected fluids, and improving overall reservoir management decisions. The large magnitudes of observed time-lapse seismic anomalies associated with strong pore pressure increases are sometimes not explainable by velocity-pressure relationships determined by fitting elastic theory to core data. This can lead to difficulties in interpreting time-lapse seismic data in terms of physically realizable changes in reservoir properties during injection. It is commonly assumed that certain geologic properties remain constant during fluid production/injection, including rock porosity and grain cementation. We have developed a new nonelastic method based on rock physics diagnostics to describe the pressure sensitivity of rock properties that includes changes in the grain contact cement, and we applied the method to a 4D seismic data example from offshore Australia. We found that water injection at high pore pressure may mechanically weaken the poorly consolidated reservoir sands in a nonelastic manner, allowing us to explain observed 4D seismic signals that are larger than can be predicted by elastic theory fits to the core data. A comparison of our new model with the observed 4D seismic response around a large water injector suggested a significant mechanical weakening of the reservoir rock, consistent with a decrease in the effective grain contact cement from 2.5% at the time/pressure of the preinjection baseline survey, to 0.75% at the time/pressure of the monitor survey. This approach may enable more accurate interpretations and future predictions of the 4D signal for subsequent monitor surveys and improve 4D feasibility and interpretation studies in other reservoirs with geomechanically similar rocks.


Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. O1-O11 ◽  
Author(s):  
Alexey Stovas ◽  
Martin Landrø

We investigate how seismic anisotropy influences our ability to distinguish between various production-related effects from time-lapse seismic data. Based on rock physics models and ultrasonic core measurements, we estimate variations in PP and PS reflectivity at the top reservoir interface for fluid saturation and pore pressure changes. The tested scenarios include isotropic shale, weak anisotropic shale, and highly anisotropic shale layers overlaying either an isotropic reservoir sand layer or a weak anisotropic sand layer. We find that, for transverse isotropic media with a vertical symmetry axis (TIV), the effect of weak anisotropy in the cap rock does not lead to significant errors in, for instance, the simultaneous determination of pore-pressure and fluid-saturation changes. On the other hand, changes in seismic anisotropy within the reservoir rock (caused by, for instance, increased fracturing) might be detectable from time-lapse seismic data. A new method using exact expressions for PP and PS reflectivity, including TIV anisotropy, is used to determine pressure and saturation changes over production time. This method is assumed to be more accurate than previous methods.


2013 ◽  
Vol 61 (5) ◽  
pp. 1022-1034 ◽  
Author(s):  
Margarita Corzo ◽  
Colin MacBeth ◽  
Olav Barkved

Geophysics ◽  
2001 ◽  
Vol 66 (3) ◽  
pp. 836-844 ◽  
Author(s):  
Martin Landrø

Explicit expressions for computing saturation‐ and pressure‐related changes from time‐lapse seismic data have been derived and tested on a real time‐lapse seismic data set. Necessary input is near‐and far‐offset stacks for the baseline seismic survey and the repeat survey. The method has been tested successfully in a segment where pressure measurements in two wells verify a pore‐pressure increase of 5 to 6 MPa between the baseline survey and the monitor survey. Estimated pressure changes using the proposed relationships fit very well with observations. Between the baseline and monitor seismic surveys, 27% of the estimated recoverable hydrocarbon reserves were produced from this segment. The estimated saturation changes also agree well with observed changes, apart from some areas in the water zone that are mapped as being exposed to saturation changes (which is unlikely). Saturation changes in other segments close to the original oil‐water contact and the top reservoir interface are also estimated and confirmed by observations in various wells.


2000 ◽  
Vol 3 (06) ◽  
pp. 517-524
Author(s):  
J.K. Hughes

Summary The propagation of elastic waves in rocks is determined by the bulk modulus, shear modulus, and bulk density of the rock. In porous rocks all these properties are affected by the distribution of pore space, the geometry and interconnectivity of the pores, and the nature of the fluid occupying the pore space. In addition, the bulk and shear moduli are also affected by the effective pressure, which is equivalent to the difference between the confining (or lithostatic) pressure and pore pressure. During production of hydrocarbons from a reservoir, the movement of fluids and changes in pore pressure may contribute to a significant change in the elastic moduli and bulk density of the reservoir rocks. This phenomenon is the basis for reservoir monitoring by repeated seismic (or time-lapse) surveys whereby the difference in seismic response during the lifetime of the field can be directly related to changes in the pore fluids and/or pore pressure. Under suitable conditions, these changes in the reservoir during production can be quantitatively estimated by appropriate repeat three-dimensional (3D) seismic surveys which can contribute to understanding of the reservoir model away from the wells. The benefit to reservoir management is a better flow model which incorporates the information derived from the seismic data. What are suitable conditions? There are two primary factors which determine whether the reservoir changes we wish to observe will be detectable in the seismic data:the magnitude of the change in the elastic moduli (and bulk density) of the reservoir rocks as a result of fluid displacement, pressure changes, etc.;the magnitude of the repeatability errors between time-lapse seismic surveys. This includes errors associated with seismic data collection, ambient noise and data processing. The first is the signal component and the second the noise component. Previous reviews of seismic monitoring suggest that for 3D seismic surveys a signal-to-noise (S/N) ratio of 1.0 is sufficient for qualitative estimation of reservoir changes. Higher S/N ratios may allow quantitative estimates. After a brief examination of the rock physics affecting the seismic signal, we examine the second factor, repeatability errors, and use a synthetic seismic model to illustrate some of the factors which contribute to repeatability error. We also use two land 3D surveys over a Middle East carbonate reservoir to illustrate seismic repeatability. The study finds that repeatability errors, while always larger than desired, are generally within limits which will allow production-induced changes in seismic reflectivity to be confidently detected. Introduction Seismic data have been used successfully for many decades in the petroleum industry and have contributed significantly to the discovery of new fields throughout the world. Initially, seismic surveys were primarily an exploration tool, assisting in the identification of potential hydrocarbon structural and stratigraphic traps for drilling targets. With the introduction of 3D seismic surveys in the 1970's, accurate geological structural mapping became possible while the use of new seismic attributes as hydrocarbon indicators improved the success rate of discovery wells. More recently seismic data have also contributed to a better reservoir description away from the wells by making use of the correlation between suitable seismic attributes and petrophysical quantities such as porosity and net to gross, and by incorporating robust geostatistical methods for estimating the static reservoir model. Better seismic acquisition technology, improved seismic processing methods and an overall improvement in signal to noise have led to further 3D seismic surveys over producing fields primarily for better imaging of the reservoir and improved reservoir characterization. The concept of using repeated seismic surveys (time-lapse seismic) for monitoring changes in the reservoir due to production was suggested in the 1980's,1-3 and early tests were done by Arco in the Holt Sand fireflood4 from 1981-83. Over the last few years, the number of publications relating to time-lapse seismic [often referred to as four-dimensional (4D) seismic] has increased dramatically. Prior to time-lapse seismic monitoring, seismic data have been the domain of geologists and geophysicists, but the possibility of monitoring fluid displacements and pressure changes in a producing reservoir, away from the wells, has direct relevance to reservoir engineers and reservoir management. More exciting possibilities have been introduced by the use of time-lapse seismic data in combination with production history matching5 for greater refinement in optimization of the reservoir model. It is important, however, that reliable criteria are used to assess the feasibility of seismic monitoring.6


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