Induced seismicity in the Khibiny Massif (Kola Peninsula)

1995 ◽  
Vol 145 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Elena O. Kremenetskaya ◽  
Victor M. Trjapitsin
Keyword(s):  
Kola Peninsula ◽  
Induced Seismicity ◽  
Khibiny Massif

Induced Seismicity in the Khibiny Massif (Kola Peninsula)

1995 ◽  
pp. 29-37 ◽  
Author(s):  
Elena O. Kremenetskaya ◽  
Victor M. Trjapitsin
Keyword(s):  
Kola Peninsula ◽  
Induced Seismicity ◽  
Khibiny Massif

Crystal Structure of Niobium-Rich Lomonosovite with Symmetry P1 from the Khibiny Massif (Kola Peninsula)

2020 ◽  
Vol 65 (3) ◽  
pp. 422-427
Author(s):  
R. K. Rastsvetaeva ◽  
V. A. Zaitsev ◽  
I. V. Pekov
Keyword(s):  
Crystal Structure ◽  
Kola Peninsula ◽  
Khibiny Massif

Mining-Induced Seismicity in the Kola Peninsula Mines

2013 ◽  
Vol 7 (7) ◽  
Author(s):  
Anatoly Kozyrev ◽  
Viktor Panin ◽  
Iuliia Fedotova
Keyword(s):  
Kola Peninsula ◽  
Induced Seismicity ◽  
Mining Induced Seismicity

Polezhaevaite-(Ce), NaSrCeF6, a new mineral from the Khibiny massif (Kola Peninsula, Russia)

2010 ◽  
Vol 95 (7) ◽  
pp. 1080-1083 ◽  
Author(s):  
V. N. Yakovenchuk ◽  
E. A. Selivanova ◽  
G. Y. Ivanyuk ◽  
Y. A. Pakhomovsky ◽  
J. A. Korchak ◽  
...  
Keyword(s):  
Kola Peninsula ◽  
New Mineral ◽  
Khibiny Massif

scholarly journals High-temperature behaviour of astrophyllite and magnesioastrophyllite from Khibiny massif (Kola peninsula, Russia)

2015 ◽  
Vol 71 (a1) ◽  
pp. s293-s293
Author(s):  
Elena S. Zhitova ◽  
Maria G. Krzhizhanovskaya ◽  
Sergey V. Krivovichev ◽  
Victor N. Yakovenchuk
Keyword(s):  
High Temperature ◽  
Kola Peninsula ◽  
Temperature Behaviour ◽  
Khibiny Massif

X-ray photoelectron spectrometry and binding energies of Be 1s and O 1s core levels in clinobarylite, BaBe2Si2O7, from Khibiny massif, Kola peninsula

2008 ◽  
Vol 59 (9) ◽  
pp. 1329-1334 ◽  
Author(s):  
V.V. Atuchin ◽  
V.G. Kesler ◽  
V.K. Sapozhnikov ◽  
V.N. Yakovenchuk
Keyword(s):  
Kola Peninsula ◽  
Binding Energies ◽  
X Ray ◽  
Khibiny Massif

Induced seismicity in large-scale mining in the kola peninsula and monitoring to reveal informative precursors

1996 ◽  
Vol 147 (2) ◽  
pp. 263-276 ◽  
Author(s):  
N. N. Melnikov ◽  
A. A. Kozyrev ◽  
V. I. Panin
Keyword(s):  
Kola Peninsula ◽  
Induced Seismicity ◽  
Large Scale

STRONTIOFLUORITE, SrF2, A NEW MINERAL SPECIES FROM THE KHIBINY MASSIF, KOLA PENINSULA, RUSSIA

2010 ◽  
Vol 48 (6) ◽  
pp. 1487-1492 ◽  
Author(s):  
V. N. Yakovenchuk ◽  
G. Y. Ivanyuk ◽  
Y. A. Pakhomovsky ◽  
E. A. Selivanova ◽  
J. A. Korchak ◽  
...  
Keyword(s):  
Kola Peninsula ◽  
Mineral Species ◽  
New Mineral ◽  
Khibiny Massif ◽  
New Mineral Species

scholarly journals Accurate determination of phase arrival times using autoregressive likelihood estimation

1994 ◽  
Vol 37 (3) ◽  
Author(s):  
G. Kvaerna
Keyword(s):  
Standard Deviation ◽  
Kola Peninsula ◽  
Accurate Determination ◽  
Onset Time ◽  
Likelihood Estimation ◽  
Array Data ◽  
Arrival Times ◽  
Khibiny Massif ◽  
Better Than

We have investigated the potential automatic use of an onset picker based on autoregressive likelihood estimation. Both a single component version and a three component version of this method have been tested on data from events located in the Khibiny Massif of the Kola peninsula, recorded at the Apatity array, the Apatity three component station and the ARCESS array. Using this method, we have been able to estimate onset times to an accuracy (standard deviation) of about 0.05 s for P-phases and 0.15 0.20 s for S phases. These accuracies are as good as for analyst picks, and are considerably better than the accuracies of the current onset procedure used for processing of regional array data at NORSAR. In another application, we have developed a generic procedure to reestimate the onsets of all types of first arriving P phases. By again applying the autoregressive likelihood technique, we have obtained automatic onset times of a quality such that 70% of the automatic picks are within 0.1 s of the best manual pick. For the onset time procedure currently used at NORSAR, the corresponding number is 28%. Clearly, automatic reestimation of first arriving P onsets using the autoregressive likelihood technique has the potential of significantly reducing the retiming efforts of the analyst.

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