Parameter tuning of differential evolution algorithm for microseismic location
- Lei Li (Central South University) | Yujiang Xie (University of Hamburg) | Dirk Gajewski (University of Hamburg) | Yuyang Tan (University of Science and Technology of China) | Jingqiang Tan (Central South University)
- Document ID
- Society of Exploration Geophysicists
- 2018 SEG International Exposition and Annual Meeting, 14-19 October, Anaheim, California, USA
- Publication Date
- Document Type
- Conference Paper
- 2018. Society of Exploration Geophysicists
- Microseismic, Passive imaging, Stacking, Optimization
- 0 in the last 30 days
- 11 since 2007
- Show more detail
Fast and accurate source location is crucial for microseismic monitoring. Stochastic optimization algorithm is derivative-free and just need random solutions as the initial model, and it is quite suitable for non-linear seismic location problem. In this work, we utilize differential evolution, which is a fast and robust global optimization method and belongs to evolutionary algorithms, to speed up microseismic location with waveform-based methods. Parameter tuning of differential evolution for two waveform-based location methods, namely diffraction stacking and cross correlation stacking, is studied and reference ranges of individual parameters are obtained. Field data examples indicate that parameter tuning is necessary to ensure the performance of differential evolution, and the convergence features of the imaging functions of different stacking operators for microseismic source location can be revealed.
Presentation Date: Wednesday, October 17, 2018
Start Time: 9:20:00 AM
Location: Poster Station 15
Presentation Type: Poster
|File Size||483 KB||Number of Pages||5|
Bischoff,M.,L.Fischer,S.Wehling-Benatelli,R.Fritschen,T.Meier, andW.Friederich,2010,Spatio-temporal characteristics of mining induced seismicity in the eastern Ruhr-area,inJ.Ritter, andA.Oth,eds.,Cahiers du Centre Europe en de Geodynamique et de Seismologie:The European Center for Geodynamics and Seismology (ECGS)30.
Cesca,S., andF.Grigoli,2015,Full waveform seismological advances for microseismic monitoring:Advances in Geophysics,56,169–228,10.1016/bs.agph.2014.12.002.
Das,S., andP. N.Suganthan,2011,Differential evolution: A survey of the state-of-the-art:IEEE Transactions on Evolutionary Computation,15,4–31,10.1109/TEVC.2010.2059031.
Gajewski,D.,D.Anikiev,B.Kashtan,E.Tessmer, andC.Vanelle,2007,Localization of seismic events by diffraction stacking:77th Annual International Meeting, SEG,Expanded Abstracts,1287–1291,10.1190/1.2792738.
Gharti,H. N.,V.Oye,M.Roth, andD.Kuehn,2010,Automated microearthquake location using envelope stacking and robust global optimization:Geophysics,75,no.4,MA27–MA46,10.1190/1.3432784.
Lagos,S. R.,J. I.Sabbione, andD. R.Velis,2014,Very fast simulated annealing and particle swarm optimization for microseismic event location:84th Annual International Meeting, SEG,Expanded Abstracts,2188–2192,10.1190/segam2014-1216.1.
Lagos,S. R., andD. R.Velis,2018,Microseismic event location using global optimization algorithms: An integrated and automated workflow:Journal of Applied Geophysics,149,18–24,10.1016/j.jappgeo.2017.12.004.
Li,L.,D.Becker,H.Chen,X. M.Wang, andD.Gajewski,2018,A systematic analysis of correlation-based seismic location methods:Geophysical Journal International,212,659–678,10.1093/gji/ggx436.
Li,L.,Y. J.Xie,H.Chen,X. M.Wang, andD.Gajewski,2017,Improving the efficiency of microseismic imaging with particle swarm optimization:79th Annual International Conference and Exhibition, EAGE,Extended Abstracts,WeB411,10.3997/2214-4609.201701260.
Pesicek,J. D.,D.Child,B.Artman, andK.Cieslik,2014,Picking versus stacking in a modern microearthquake location: Comparison of results from a surface passive seismic monitoring array in Oklahoma:Geophysics,79,no.6,KS61–KS68,10.1190/geo2013-0404.1.
Ruzek,B., andM.Kvasnicka,2001,Differential evolution algorithm in the earthquake hypocenter location:Pure and Applied Geophysics,158,667–693,10.1007/PL00001199.
Storn,R., andK.Price,1997,Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces:Journal of Global Optimization,11,341–359,10.1023/A:1008202821328.
Verdon,J. P.,J.Kendall,S. P.Hicks, andP.Hill,2017,Using beamforming to maximise the detection capability of small, sparse seismometer arrays deployed to monitor oil field activities:Geophysics Prospecting,65,1582–1596,10.1111/1365-2478.12498.
Walda,J., andD.Gajewski,2017,Determination of wavefront attributes by differential evolution in the presence of conflicting dips:Geophysics,82,no.4,V229–V239,10.1190/geo2016-0346.1.