A fuzzy c-means assisted AIC workflow for arrival picking on downhole microseismic data
Name:
A_fuzzy_c_means_assisted_AIC_workflow_for_arrival_picking_on_downhole_microseismic_data_WITH_REFERENCES.pdf
Size:
339.9Kb
Format:
PDF
Description:
Accepted manuscript
Name:
A_fuzzy_c_means_assisted_AIC_workflow_for_arrival_picking_on_downhole_microseismic_data.pdf
Size:
337.4Kb
Format:
PDF
Description:
Accepted manuscript
Type
Conference PaperKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionEarth Science and Engineering Program
Extreme Computing Research Center
Physical Science and Engineering (PSE) Division
Date
2019-08-10Permanent link to this record
http://hdl.handle.net/10754/661915
Metadata
Show full item recordAbstract
We propose a workflow for automatic P- and S-wave arrival picking on downhole microseismic data. It uses conditional fuzzy c-means clustering to identify time intervals of possible wave arrivals. We classify the signal intervals as P- and S-wave using the first and second eigenvalues of the waveforms contained within. The Akaike information criterion (AIC) picker is then applied to the identified P- and S-wave intervals for arrival picking. Using real microseismic dataset examples, we show that the proposed workflow yields accurate arrival picks for both high and low signal-to-noise ratio waveforms. The identification of signal intervals, however, uses features based on amplitude, thus remains susceptible to high amplitude noise.Citation
Cano, E. V., Akram, J., Peter, D., & Eisner, L. (2019). A fuzzy c-means assisted AIC workflow for arrival picking on downhole microseismic data. SEG Technical Program Expanded Abstracts 2019. doi:10.1190/segam2019-3215089.1Publisher
Society of Exploration GeophysicistsConference/Event name
Society of Exploration Geophysicists International Exposition and Annual Meeting 2019, SEG 2019Additional Links
https://library.seg.org/doi/10.1190/segam2019-3215089.1ae974a485f413a2113503eed53cd6c53
10.1190/segam2019-3215089.1