Generating a high-resolution lithology model for subsurface formation evaluation
Examples of techniques for generating a high-resolution lithology model for subsurface formation evaluation are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes determining, by a processing device, a low-resolution lithology volumetric model. The method further includes comparing, by the processing device, the low-resolution lithology volumetric model to a high-resolution imaging log. The method further includes calculating, by the processing device, a dynamic boundary curve for each of a plurality of moving windows. The method further includes generating, by the processing device, the high-resolution lithology model based at least in part on the calculated dynamic boundary curve for each of the plurality of moving windows. The method further includes controlling a drilling operation based at least in part on the high-resolution lithology model.
1. A computer-implemented method for generating a high-resolution lithology model, the method comprising:
determining, by a processing device, a low-resolution lithology volumetric model;
comparing, by the processing device, the low-resolution lithology volumetric model to a high-resolution imaging log;
calculating, by the processing device, a dynamic boundary curve for each of a plurality of moving windows;
generating, by the processing device, the high-resolution lithology model based at least in part on the calculated dynamic boundary curve for each of the plurality of moving windows; and
controlling drilling equipment based at least in part on the high-resolution lithology model.
2. The computer-implemented method of claim 1 , further comprising, prior to determining the low-resolution lithology volumetric model:
defining, by the processing device, a commonly used lithology reference model.
3. The computer-implemented method of claim 2 , wherein defining the commonly used lithology reference model is based at least in part on one or more of a known mineral composition, a known porosity, and a known fluid saturation.
4. The computer-implemented method of claim 2 , further comprising:
calculating, by the processing device, tool parameters for the defined commonly used lithology reference model.
5. The computer-implemented method of claim 4 , wherein the tool parameters are one or more of a density response, a compensated neutron response, an acoustic response, a nuclear magnetic resonance response, a spectroscopy elemental weight fraction response, and a tool response from logging equipment.
6. The computer-implemented method of claim 4 , further comprising:
assigning, by the processing device, uncertainty values for each of a plurality of input logs.
7. The computer-implemented method of claim 6 , further comprising:
applying, by the processing device, a probabilistic approach based on the defined commonly used lithology reference model.
8. The computer-implemented method of claim 1 , wherein the high-resolution lithology model indicates a subsurface material type at each depth level of an earth formation.
9. The computer-implemented method of claim 8 , wherein the subsurface material type is one of sand, carbonate, and shale.
10. The computer-implemented method of claim 1 , wherein controlling the drilling equipment comprises adjusting at least one of a rate of penetration, a weight on bit, a depth of a drill bit, and a trajectory of the drill bit.
11. A system comprising:
drilling equipment;
a memory comprising computer readable instructions; and
a processing device for executing the computer readable instructions for performing a method for generating a high-resolution lithology model, the method comprising:
determining, by the processing device, a low-resolution lithology volumetric model;
comparing, by the processing device, the low-resolution lithology volumetric model to a high-resolution imaging log;
calculating, by the processing device, one or more dynamic boundary curves for each of a plurality of moving windows;
generating, by the processing device, the high-resolution lithology model based at least in part on the calculated dynamic boundary curve for each of the plurality of moving windows; and
controlling the drilling equipment based at least in part on the high-resolution lithology model.
12. The system of claim 11 , wherein the method further comprises, prior to determining the low-resolution lithology volumetric model:
defining, by the processing device, a commonly used lithology reference model;
calculating, by the processing device, tool parameters for the defined commonly used lithology reference model;
assigning, by the processing device, uncertainty values for each of a plurality of input logs; and
applying, by the processing device, a probabilistic approach based on the defined commonly used lithology reference model.
13. The system of claim 11 , wherein the high-resolution lithology model indicates a subsurface material type at each depth level of an earth formation.
14. The system of claim 13 , wherein the subsurface material type is one of sand, carbonate, shale, evaporate, igneous, and coal.
15. The system of claim 11 , wherein controlling the drilling equipment comprises adjusting at least one of a rate of penetration, a weight on bit, a depth of a drill bit, and a trajectory of the drill bit.
16. The system of claim 11 , wherein the method further comprises preforming reservoir assessment and designing completion and production strategies based at least in part on the high-resolution lithology model.