System and method to identify high-impact discrete fracture model realizations for accelerated calibration of reservoir simulation models
The present disclosure describes a computer-implemented method that includes: receiving a seismic dataset of a surveyed subsurface of a reservoir, the seismic dataset comprising observed pressure and production data of the reservoir as well as a set of geological and geo-mechanical parameters representing physical features of the surveyed subsurface; generating multiple realizations of a discrete fracture network (DFN) based on a subset of the set of geological and geo-mechanical parameters; selecting, from the multiple realizations, one or more realizations based on a parameter with a value under a 10% quantile of a full range of likely values; performing a forward simulation for the reservoir based on the selected one or more realizations and the observed pressure and production data; determining that a misfit of the forward simulation is below a threshold based on evaluating an objective function; and producing a model of the reservoir based on the forward simulation.
1. A computer-implemented method to improve production forecasting accuracy for a reservoir, the computer-implemented method comprising:
receiving a seismic dataset of a surveyed subsurface of the reservoir under investigation, the seismic dataset comprising observed pressure and production data of the reservoir as well as a set of geological and geo-mechanical parameters representing physical features of the surveyed subsurface;
generating multiple realizations of a discrete fracture network (DFN) based on a subset of the set of geological and geo-mechanical parameters, wherein the multiple realizations are ranked in a number of quantiles, wherein each quantile represents at least one realization generated based on the subset of geological and geo-mechanical parameters with corresponding parameter values under the quantile of a full range of likely values, wherein the subset of geological and geo-mechanical parameters comprise: a fracture surface area, and a fracture length;
selecting, from the multiple realizations, one or more realizations generated based on the subset of geological and geo-mechanical parameters with corresponding parameter values ranked under a 10% quantile of the full range of likely values;
performing a forward simulation for the reservoir based on the selected one or more realizations and the observed pressure and production data;
in response to determining that a misfit of the forward simulation is reduced below a threshold, producing a 3D model of the reservoir based on the forward simulation; and
applying the 3D model to subsequently model the reservoir with improved production forecasting accuracy by virtue of the reduced misfit.
2. The computer-implemented method of claim 1 , further comprising:
performing production forecasting for the reservoir, at least in part, based on the 3D model.
3. The computer-implemented method of claim 1 , wherein the misfit is computed as a combination of misfits of watercut and pressure.
4. The computer-implemented method of claim 3 , wherein the misfit is computed as a combination of misfits of water rate and water production.
5. The computer-implemented method of claim 1 , wherein the set of geological and geo-mechanical parameters comprise:
a fracture orientation, fracture geometric properties and constraints, a fracture density or concentration, spatial components of paleo-stress, and an intrinsic fracture permeability model.
6. The computer-implemented method of claim 5 , wherein the fracture orientation comprises variogram attributes including major, minor and vertical correlation length.
7. The computer-implemented method of claim 1 , further comprising:
in response to determining that the misfit of the forward simulation is not below the threshold, selecting a new realization that has been generated, at least in part, based on the subset of geological and geo-mechanical parameters with corresponding parameter values under a 10% quantile of the full range of likely values; and
performing the forward simulation for the reservoir based on the selected new realization and the observed pressure and production data.
8. The computer-implemented method of claim 7 , further comprising:
computing the misfit based on the selected new realization.
9. The computer-implemented method of claim 7 , further comprising:
generating a plurality of history matched models based on iteratively selecting the realization of the DFN; and
ranking the plurality of history matched models based on misfits computed for respective history matched models.
10. A computer system comprising one or more processors configured to improve production forecasting accuracy for a reservoir by performing operations of:
receiving a seismic dataset of a surveyed subsurface of the reservoir under investigation, the seismic dataset comprising observed pressure and production data of the reservoir as well as a set of geological and geo-mechanical parameters representing physical features of the surveyed subsurface;
generating multiple realizations of a discrete fracture network (DFN) based on a subset of the set of geological and geo-mechanical parameters, wherein the multiple realizations are ranked in a number of quantiles, wherein each quantile represents at least one realization generated based on the subset of geological and geo-mechanical parameters with corresponding parameter values under the quantile of a full range of likely values, wherein the subset of geological and geo-mechanical parameters comprise: a fracture surface area, and a fracture length;
selecting, from the multiple realizations, one or more realizations generated based on the subset of geological and geo-mechanical parameters with corresponding parameter values ranked under a 10% quantile of the full range of likely values;
performing a forward simulation for the reservoir based on the selected one or more realizations and the observed pressure and production data;
in response to determining that a misfit of the forward simulation is reduced below a threshold, producing a 3D model of the reservoir based on the forward simulation; and
applying the 3D model to subsequently model the reservoir with improved production forecasting accuracy by virtue of the reduced misfit.
11. The computer system of claim 10 , wherein the operations further comprise:
performing production forecasting for the reservoir, at least in part, based on the 3D model.
12. The computer system of claim 10 , wherein the misfit is computed as a combination of misfits of watercut and pressure.
13. The computer system of claim 12 , wherein the misfit is computed as a combination of misfits of water rate and water production.
14. The computer system of claim 10 , wherein the set of geological and geo-mechanical parameters comprise:
a fracture orientation, fracture geometric properties and constraints, a fracture density or concentration, spatial components of paleo-stress, and an intrinsic fracture permeability model.
15. The computer system of claim 14 , wherein the fracture orientation comprises variogram attributes including major, minor and vertical correlation length.
16. The computer system of claim 10 , wherein the operations further comprise:
in response to determining that the misfit of the forward simulation is not below the threshold, selecting a new realization that has been generated, at least in part, based on the subset of geological and geo-mechanical parameters with corresponding parameter values under a 10% quantile of the full range of likely values; and
performing the forward simulation for the reservoir based on the selected new realization and the observed pressure and production data.
17. The computer system claim 16 , wherein the operations further comprise:
computing the misfit based on the selected new realization.
18. The computer system of claim 16 , wherein the operations further comprise:
generating a plurality of history matched models based on iteratively selecting the realization of the DFN; and
ranking the plurality of history matched models based on misfits computed for respective history matched models.