Available trained models¶
gempa [9] provides many models trained on and applied to different data sets at different scales of epicentral distances, source depths and source types. They are listed in table deepc-models. Use these model names for configuration of modelWeights which exists for each sub-picker:
spicker.deepcSR.modelWeights
The corresponding DL models are installed with the dlmodels package. When
installing deepc by gsm, dlmodels is installed automatically.
A typical installation directory is /home/data/dlmodels.
Event classification models¶
Currently, gempa doesn’t provide a model for event classification.
model name |
event types |
applications |
training data |
|---|---|---|---|
pncx-if-3 |
earthquake, anthropogenic event, mining |
signals from earthquakes and machinery in mining environment at epicentral distance of tens of meters up to 10 km |
mine |
pncx-if-10 |
earthquake, anthropogenic event, mining |
signals from earthquakes and machinery in mining environment at epicentral distance of tens of meters up to 10 km |
mine |
Phase classification models¶
model name |
specifics |
applications |
training data |
|---|---|---|---|
pnc-cb-1_4 |
P, S, Noise |
(re-) classify phase hints for picks |
Joint time prediction and phase classification models¶
The Seismology Benchmark collection, SeisBench [23], has published many pre-trained picker models. gempa provides converted versions of some of these models and also in-house trained ones. These models predict probabilities for P, S, and Noise for each sample of a trace. DeepC post-processes their predictions to phase classification and onset refinement of a given trigger.
EqTransformer¶
The following models are trained on the SeisBench implementation of EqTransformer [22].
model name |
specifics |
applications |
training data |
|---|---|---|---|
eq-et |
60 s, 100 Hz |
regional data |
ETHZ [1] |
eq-ge |
60 s, 100 Hz |
teleseismic data |
GEOFON [2] |
eq-in |
60 s, 100 Hz |
regional data |
INSTANCE [3] |
eq-iq |
60 s, 100 Hz |
regional data |
Iquique [4] |
eq-ne |
60 s, 100 Hz |
regional data |
NEIC [5] |
eq-or |
60 s, 100 Hz |
regional data |
original EqTransformer weights [22] |
eq-sc |
60 s, 100 Hz |
regional data |
SCEDC [6] |
eq-st |
60 s, 100 Hz |
regional data |
STEAD [7] |
PhaseNet¶
The following models are trained on the SeisBench adaptions of PhaseNet [28].
model name |
specifics |
applications |
training data |
|---|---|---|---|
pn-et |
30.01 s, 100 Hz |
regional data |
ETHZ [1] |
pn-ge |
30.01 s, 100 Hz |
teleseismic data |
GEOFON [2] |
pn-in |
30.01 s, 100 Hz |
regional data |
INSTANCE [3] |
pn-iq |
30.01 s, 100 Hz |
regional data |
Iquique [4] |
pn-ne |
30.01 s, 100 Hz |
regional data |
NEIC [5] |
pn-or |
30.01 s, 100 Hz |
regional data |
original PhaseNet weights [28] |
pn-sc |
30.01 s, 100 Hz |
regional data |
SCEDC [6] |
pn-st |
30.01 s, 100 Hz |
regional data |
STEAD [7] |
pn-in_vl-74 |
30.01 s, 100 Hz |
regional data |
INSTANCE [3], Vogtland |
pn-in_vl-97 |
30.01 s, 100 Hz, all-comps-normalized |
regional data |
INSTANCE [3], Vogtland |
pn-vl-91 |
30.01 s, 100 Hz, all-comps-normalized |
regional data |
Vogtland |
pn-vp |
30.01 s, 100 Hz |
volcanic data |
VCSEIS [8] |
pnv-bq-0 |
60 s, 100 Hz |
volcanic data? |
BQCombined |
pnv-bq-10 |
30 s, 100 Hz |
volcanic data? |
BQCombined |
pnv-il_vc-2 |
15 s, 100 Hz |
volcanic data? |
Iceland, VCSEIS_hawaii [8] |
pnv_15s-et-0 |
15 s, 100 Hz |
regional |
ETHZ [1] |
pnv_15s-il-2 |
15 s, 100 Hz |
regional |
Iceland |
pnv_30s-et-sb |
30 s, 100 Hz |
regional |
Iceland |
pnv_60s-et-0 |
60 s, 100 Hz |
regional |
Iceland |