Real-time determination of mud slowness, formation type, and monopole slowness picks in downhole applications
An acoustic logging system identifies hydrocarbon formation types by a real-time model-constrained mud wave slowness determination method using borehole guided waves. The system also combines data processing from different acoustic waveform processing techniques using an information sharing procedure, for example, using monopole source data and dipole source data, to further improve the processing results and to achieve more stable and reliable real-time shear slowness answers.
1. A downhole acoustic logging method, comprising:
acquiring acoustic waveforms of a borehole extending along a formation;
determining whether a formation type of the formation is hard or soft using the acquired waveforms, wherein a hard formation has a formation shear slowness lower than a mud wave slowness and a soft formation has a formation shear slowness higher than the mud wave slowness;
identifying slowness picks using the formation type; and
determining a characteristic of the formation using the slowness picks.
2. The method of claim 1 , wherein determining the formation type comprises:
determining slowness asymptotes of the acquired waveforms;
extracting Scholte wave slowness from the slowness asymptotes;
calculating mud wave slowness using the Scholte wave slowness; and
comparing the mud wave slowness and shear wave slowness to determine the formation type.
3. The method of claim 2 , wherein determining the slowness asymptotes comprises:
calculating a dispersion response of the acquired waveforms;
determining full-frequency dispersion estimates by minimizing a misfit between theoretical dispersion curves and measured dispersion curves; and
determining the slowness asymptotes from the full-frequency dispersion estimates.
4. The method of claim 2 , wherein identifying the slowness picks comprises:
determining a searching range of the shear wave slowness using the mud wave slowness, compressional wave travel time, and compressional wave slowness;
determining a travel time of the shear wave slowness using the mud wave slowness and the compressional wave travel time;
generating a semblance map using the searching range and travel time; and
identifying the slowness picks of the semblance map.
5. The method of claim 1 , wherein:
the determination of formation type is performed in real-time; or
monopole wave processing of a first waveform acquisition is applied to constrain the determination of the formation type.
6. The method of claim 5 , wherein dipole wave processing of the first waveform acquisition is applied to constrain the identification of the slowness picks.
7. The method of claim 6 , wherein:
the dipole wave processing of the first waveform acquisition is applied to constrain a monopole wave processing of a second waveform acquisition; and
the second waveform acquisition is acquired at a different time or borehole depth than the first waveform acquisition.
8. The method of claim 1 , wherein the mud wave slowness is determined by averaging mud wave slownesses over a borehole target zone.
9. An acoustic logging system, comprising:
an acoustic logging tool communicably coupled to a processor; and
a memory coupled to the processor having instructions stored therein, which when executed by the processor, cause the processor to perform operations comprising:
acquiring acoustic waveforms of a borehole extending along a formation;
determining whether a formation type of the formation is hard or soft using the acquired waveforms, wherein a hard formation has a formation shear slowness lower than a mud wave slowness and a soft formation has a formation shear slowness higher than the mud wave slowness;
identifying slowness picks using the formation type; and
determining a characteristic of the formation using the slowness picks.
10. The system of claim 9 , wherein determining the formation type comprises:
determining slowness asymptotes of the acquired waveforms;
extracting Scholte wave slowness from the slowness asymptotes;
calculating mud wave slowness using the Scholte wave slowness; and
comparing the mud wave slowness and shear wave slowness to determine the formation type.
11. The system of claim 10 , wherein determining the slowness asymptotes comprises:
calculating a dispersion response of the acquired waveforms;
determining full-frequency dispersion estimates by minimizing a misfit between theoretical dispersion curves and measured dispersion curves; and
determining the slowness asymptotes from the full-frequency dispersion estimates.
12. The system of claim 10 , wherein identifying the slowness picks comprises:
determining a searching range of the shear wave slowness using the mud wave slowness, compressional wave travel time, and compressional wave slowness;
determining a travel time of the shear wave slowness using the mud wave slowness and the compressional wave travel time;
generating a semblance map using the searching range and travel time; and
identifying the slowness picks of the semblance map.
13. The system of claim 9 , wherein:
the determination of formation type is performed in real-time; or
monopole wave processing of a first waveform acquisition is applied to constrain the determination of the formation type.
14. The system of claim 13 , wherein dipole wave processing of the first waveform acquisition is applied to constrain the identification of the slowness picks.
15. The system of claim 14 , wherein:
the dipole wave processing of the first waveform acquisition is applied to constrain a monopole wave processing of a second waveform acquisition; and
the second waveform acquisition is acquired at a different time or borehole depth than the first waveform acquisition.
16. The system of claim 9 , wherein the mud wave slowness is determined by averaging mud wave slownesses over a borehole target zone.
17. The system of claim 9 , wherein the acoustic waveforms are acquired using an acoustic logging tool positioned along a wireline or drilling assembly.
18. A non-transitory computer-readable medium comprising instructions which, when executed by at least one processor, causes the processor to perform the method of claim 1 .