Methods, systems and devices for predicting reservoir properties
Methods, devices and computer-readable media for predicting hydrocarbon production rates for a subterranean formation are described. A method includes: receiving or generating, by at least one processor, well logs from data collected from at least one well in the subterranean formation; generating from the well logs a predicted production rate log for the at least one well; receiving, by the at least one processor, a field dataset for the subterranean formation, the field dataset including field data at locations in 3-dimensions of a volume of the subterranean formation; identifying the predicted production rate log for the at least one well as one or more targets, determining a transform relating the field data and the predicted rate log for the at least one well; and using the transform, generating a predicted production rate for each location of the volume of the subterranean formation.
1. A method of detecting reservoir properties over a three-dimensional volume of a subterranean formation, the method comprising:
obtaining, well logs from core samples or borehole devices of at least one well in the subterranean formation;
generating, with at least one processor, from the well logs a predicted production rate log for the at least one well;
obtaining a field dataset for the subterranean formation, the field dataset including field data collected for locations in 3-dimensions of a volume of the subterranean formation with a plurality of sensing devices positioned to remotely detect the field data for the locations of the volume;
identifying the predicted production rate log for the at least one well as one or more targets, determining a transform relating the field data and the predicted rate log for the at least one well; and
using the transform, generating a predicted production rate for each of the locations in 3-dimensions of the volume of the subterranean formation.
2. The method of claim 1 wherein determining the transform comprises applying at least one of a linear regression, a genetic algorithm, a neural network analysis, or a multi-parameter estimation method.
3. The method of claim 1 wherein the well logs include logs for porosity, saturation, permeability and bitumen column height.
4. The method of claim 1 wherein the field data includes at least one of seismic data, gravity data, electrical resistivity data or electro-magnetic data.
5. The method of claim 1 wherein the field data includes wide-angle seismic data.
6. The method of claim 5 wherein the wide-angle seismic data is collected from seismic waves having an angle of incidence greater than 45 degrees.
7. The method of claim 1 wherein the field data includes density data.
8. The method of claim 1 wherein the predicted production rate log generated from the well logs is based on the equation:
Q=C L √{square root over (ΦΔ S o KH )}
where C is a constant, L represents a horizontal length of the well, Φ represents fractional porosity, ΔS o represents a difference between initial oil saturation and residual oil saturation to steam, K represents permeability, and H represents reservoir height.
9. The method of claim 1 comprising: generating a three-dimensional visual representation of at least a portion of the subterranean formation using the predicted production rates for the locations of the volume corresponding to the portion of the subterranean formation.
10. The method of claim 1 comprising: determining a predicted production rate for identified drainage areas or positioned wells using the predicted production rates for the locations of the volume corresponding to locations of the identified areas or positioned wells in the subterranean formation.
11. The method of claim 1 comprising: determining a constant factor C for generating the predicted production rate log for the at least one well and the predicted production rate for each location of the volume of the subterranean formation; wherein determining the constant factor C is based on measured or simulated well data.
12. A device for expanding reservoir properties from well log data over a three-dimensional volume of a subterranean formation, the device comprising: at least one processor configured for:
obtaining well logs from core samples or borehole devices of at least one well in the subterranean formation;
generating from the well logs a predicted production rate log for the at least one well;
obtaining a field dataset for the subterranean formation, the field dataset including field data collected for locations in 3-dimensions of a volume of the subterranean formation with a plurality of sensing devices positioned to remotely detect the field data for the locations of the volume;
identifying the predicted production rate log for the at least one well as one or more targets, determining a transform relating the field data and the predicted rate log for the at least one well; and
using the transform, generating a predicted production rate for each of the locations in 3-dimensions of the volume of the subterranean formation.
13. The device of claim 12 wherein determining the transform comprises applying at least one of: a linear regression, a genetic algorithm, a neural network analysis, or a multi-parameter estimation method.
14. The device of claim 12 wherein the well logs include logs for porosity, saturation, permeability and bitumen column height.
15. The device of claim 12 wherein the field data includes at least one of seismic data, gravity data, electrical resistivity data or electro-magnetic data.
16. The device of claim 12 wherein the field data includes seismic data collected from seismic waves having an angle of incidence greater than 45 degrees.
17. The device of claim 12 wherein the field data includes density data.
18. The device of claim 12 wherein the predicted production rate log generated from the well logs is based on the equation:
Q=C L √{square root over (ΦΔ S o KH )}
where C is a constant, L represents a horizontal length of the well, Φ represents fractional porosity, ΔS o represents a difference between initial oil saturation and residual oil saturation to steam, K represents permeability, and H represents reservoir height.
19. The device of claim 12 wherein the at least one processor is configured for: generating a three-dimensional visual representation of at least a portion of the subterranean formation using the predicted production rates for the locations of the volume corresponding to the portion of the subterranean formation.
20. The device of claim 12 wherein the at least one processor is configured for: determining a predicted production rate for identified drainage areas or positioned wells using the predicted production rates for the locations of the volume corresponding to locations of the identified areas or positioned wells in the subterranean formation.
21. The device of claim 12 comprising: the at least one processor is configured for: determining a constant factor C for generating the predicted production rate log for the at least one well and the predicted production rate for each location of the volume of the subterranean formation; wherein determining the constant factor C is based on measured or simulated well data.
22. A non-transitory computer-readable medium or media having stored thereon, computer-readable instructions which when executed by at least one processor, configure the at least one processor for:
obtaining well logs from core samples or borehole devices of at least one well in the subterranean formation;
generating from the well logs a predicted production rate log for the at least one well;
obtaining a field dataset for the subterranean formation, the field dataset including field data collected for locations in 3-dimensions of a volume of the subterranean formation with a plurality of sensing devices positioned to remotely detect the field data for the locations of the volume;
identifying the predicted production rate log for the at least one well as one or more targets, determining a transform relating the field data and the predicted rate log for the at least one well; and
using the transform, generating a predicted production rate for each of the locations in 3-dimensions of the volume of the subterranean formation.