Clustering characteristics of gas-extraction induced seismicity in the Groningen gas field
Notice bibliographique
Résumé
SUMMARY The Groningen gas field in the north of the Netherlands is one of the largest gas fields in the world. Since the early 1990s induced seismicity has been recorded. The largest magnitude event observed so far was a Mw = 3.6 event at the town of Huizinge in 2012. The risk posed by the induced events urged the necessity to build comprehensive seismological models capable of explaining the spatial-temporal distribution of the recorded seismicity and evaluating the regional seismic hazard and risk. The link between the occurrence of the seismicity and pressure depletion due to the production of the gas has been firmly established. However, the construction of comprehensive seismological models as well as hazard assessment is complicated by the fact that it is difficult to distinguish between induced and clustered events (events triggered by stress transfer of preceding, neighbouring events). This paper explores the contribution of clustered populations (i.e. aftershocks) to the Groningen induced seismic catalogue based on a statistical methodology in the time–space–magnitude domain. Specifically, the distributions of space–time distances between pairs of nearest-neighbour earthquakes, referred to as cluster style, is analysed. The cluster style of the Groningen induced seismicity is found to be very diffuse and characterized by a very low proportion of fore-/aftershock sequences and swarms (∼5 per cent) and a large proportion of repeater events (∼10 per cent). In contrast to human-induced seismicity in other regions, the background seismicity rate of Groningen is very low. Temporal variations in background seismicity rates can be related to changes in fault loading rates induced by gas production. Furthermore, a significant amount of independent, coincidental events (events occurring very close in time, but long distances apart) are observed. As the large gas field is fully connected, loading of the faults occurs roughly simultaneously throughout the field. Hence, the statistical probability of events occurring very close in time, but spatially far apart is significantly larger than in areas of fluid-injection induced seismicity The significant amount of repeaters and coincidental events cause an overabundance of events at intermediate time- and space-distances. This is further enhanced by the larger location errors in the catalogue increasing the estimated space-distance for non-relocated events. The diffusivity due to this overabundance of events at intermediate time- and space-distances, and the low-proportion of true fore-/aftershocks renders the statistical method used incapable of deriving a proper mode-separation value. However, this is not unique to this method. Any statistical method aimed at resolving two populations will break down if one of the populations analysed is too small. Hence, it is advisable to use caution when distinguishing fore-/aftershocks sequences or swarms for induced seismicity where the relative proportion of clustered events may be significantly lower than for tectonic events. In addition, given the small proportion of clustering and the general uncertainty in earthquake statistics, the results of this paper indicate that a distinction for earthquake risk modelling in Groningen is unnecessary.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».