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| Titel |
Causality between expansion of seismic cloud and maximum magnitude of induced seismicity in geothermal field |
| VerfasserIn |
Yusuke Mukuhira, Hiroshi Asanuma, Takatoshi Ito, Markus Häring |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250130797
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| Publikation (Nr.) |
 EGU/EGU2016-11106.pdf |
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| Zusammenfassung |
| Occurrence of induced seismicity with large magnitude is critical environmental issues
associated with fluid injection for shale gas/oil extraction, waste water disposal, carbon
capture and storage, and engineered geothermal systems (EGS). Studies for prediction of the
hazardous seismicity and risk assessment of induced seismicity has been activated recently.
Many of these studies are based on the seismological statistics and these models use the
information of the occurrence time and event magnitude. We have originally developed
physics based model named “possible seismic moment model” to evaluate seismic activity
and assess seismic moment which can be ready to release. This model is totally
based on microseismic information of occurrence time, hypocenter location and
magnitude (seismic moment). This model assumes existence of representative parameter
having physical meaning that release-able seismic moment per rock volume (seismic
moment density) at given field. Seismic moment density is to be estimated from
microseismic distribution and their seismic moment. In addition to this, stimulated rock
volume is also inferred by progress of microseismic cloud at given time and this
quantity can be interpreted as the rock volume which can release seismic energy
due to weakening effect of normal stress by injected fluid. Product of these two
parameters (equation (1)) provide possible seismic moment which can be released from
current stimulated zone as a model output. Difference between output of this model
and observed cumulative seismic moment corresponds the seismic moment which
will be released in future, based on current stimulation conditions. This value can
be translated into possible maximum magnitude of induced seismicity in future.
As this way, possible seismic moment can be used to have feedback to hydraulic
stimulation operation in real time as an index which can be interpreted easily and
intuitively.
Possible seismic moment is defined as equation (1), where D is seismic moment density
(Mo/m3) and V stim is stimulated rock volume (m3).
Mopossible = D ∗ V stim(1)
We applied this conceptual model to real microseismic data set from Basel EGS project
where several induced seismicity with large magnitude occurred and brought constructive
damage. Using the hypocenter location determined by the researcher of Tohoku Univ., Japan
and moment magnitude estimated from Geothermal Explorers Ltd., operating company, we
were able to estimate reasonable seismic moment density meaning that one representative
parameter exists and can characterize seismic activity at Basel at each time step. With
stimulated rock volume which was also inferred from microseismic information, we
estimated possible seismic moment and assess the difference with observed value.
Possible seismic moment significantly increased after shut-in when the seismic
cloud (stimulated zone) mostly progressed, resulting that the difference with the
observed cumulative seismic moment automatically became larger. This suggests that
there is moderate seismic moment which will be released in near future. In next
few hours, the largest event actually occurred. Therefore, our proposed model was
successfully able to forecast occurrence of the large events. Furthermore, best forecast of
maximum magnitude was Mw 3 level and the largest event was Mw 3.41, showing
reasonable performance in terms of quantitative forecast in magnitude. Our attempt to
assess the seismic activity from microseismic information was successful and it also
suggested magnitude release can be correlate with the expansion of seismic cloud as
the definition of possible seismic moment model indicates. This relationship has
been observed in microseismic observational study and several previous study also
suggested their correlation with stress released rock volume. Our model showed
harmonic results with these studies and provide practical method having clear physical
meaning to assess the seismic activity in real time, based on microseismic data. |
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