Method for obtaining estimates of a model parameter so as to characterise the evolution of a subsurface volume over a time period
US-2018003840-A1 · Jan 4, 2018 · US
US10705237B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10705237-B2 |
| Application number | US-201515324400-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 10, 2015 |
| Priority date | Jul 11, 2014 |
| Publication date | Jul 7, 2020 |
| Grant date | Jul 7, 2020 |
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Disclosed is a method for characterizing the evolution of a subsurface volume over time. The method comprises providing a first and second surveys of the reservoir with a first and second sets of seismic traces, performing an inversion to obtain estimates of changes having occurred between said first time and said second time in terms of at least one model parameter; wherein the subsurface volume is divided into regions according to a high order discrete classification attributed in accordance with the region's geologic characteristics, and said inversion is constrained per region of subsurface volume. The regions of subsurface volume may be geological layers.
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The invention claimed is: 1. A method for characterising the evolution of a subsurface volume over time, said method comprising: providing a first survey of the subsurface volume with a first set of seismic traces corresponding to a first time; providing a second survey of the subsurface volume with a second set of seismic traces corresponding to a second time; performing an inversion to obtain estimates of changes having occurred between said first time and said second time in terms of at least one model parameter; and wherein said subsurface volume is divided into regions according to a high order discrete classification attributed in accordance with the region's geologic characteristics, and said inversion is constrained per region of subsurface volume. 2. The method as claimed in claim 1 , wherein said inversion comprises inverting for coefficients of a regional function at each spatial location within a region, wherein said regional function describes how the model parameter varies within a region. 3. The method as claimed in claim 2 wherein said coefficients of the regional function are region-dependent coefficients, said region-dependent coefficients being dependent on the region of subsurface volume they correspond to. 4. The method as claimed in claim 2 wherein said regional function comprises a forward modelling operator imposing a region-dependent constraint, said region-dependent constraint being dependent on the region of subsurface volume. 5. The method as claimed in claim 4 wherein said forward modelling operator expands the coefficients of the regional function at each spatial location to every seismic sample point within the region. 6. The method as claimed in claim 4 wherein the region-dependent constraint is that the model parameter is constant within each region. 7. The method as claimed in claim 1 further comprising: constructing an analytic filter operable to shift at least one seismic trace in dependence of a time varying parameter; and performing the inversion to obtain estimates of the time varying parameter such that the analytic filter aligns the first survey and the second survey. 8. The method as claimed in claim 7 wherein the analytic filter comprises a plane wave destruction filter, and is a time domain analogue of a frequency domain phase shift operator operable to impose a constant time shift to a plane wave model of a seismic trace. 9. The method as claimed in claim 7 wherein the analytic filter is such that the time varying parameter is a function of the analytic filter instead of being a function of at least one of the second set of seismic traces. 10. The method as claimed in claim 7 , wherein the inversion is further regularized spatially in two directions substantially parallel with the surface, and regularized in the direction normal to the surface across region boundaries only, and not within the regions. 11. The method of claim 7 , wherein the time varying parameter is one of time shift, time strain, and velocity change. 12. The method as claimed in claim 1 wherein said regions of subsurface volume comprise geological layers. 13. The method as claimed in claim 1 wherein said high order discrete classification comprises facies. 14. The method as claimed in claim 1 wherein the model parameter is one of time strain, time shift or relative velocity change. 15. The method as claimed in any of claim 1 wherein said inversion is performed with layer positions of said subsurface volume being predetermined and fixed; the inversion being performed to obtain estimates of changes between layers, according to a function describing the expected model parameter change within each layer. 16. The method as claimed in claim 1 further comprising the step of using the results of said method to aid hydrocarbon recovery from a reservoir. 17. The method as claimed in claim 1 further comprising the step of using the estimated changes having occurred between said first time and said second time in the prediction of the future evolution of said subsurface volume. 18. A non-transitory computer-program product comprising a computer-usable medium having computer-readable program code embodied therein, the computer-readable program code adapted to be executed to implement a method comprising the steps of claim 1 .
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Previously recorded data, e.g. time-lapse or 4D · CPC title
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