Global physics-based database of injection-induced seismicity
Abstract. Fluid injection into geological formations for energy resource development frequently induces (micro)seismicity. If intensely shaking the ground, induced earthquakes may cause injuries and/or economic loss, with the consequence of jeopardizing the operation and future development of these geoenergy projects. To achieve an improved understanding of the causes of induced seismicity, develop forecasting tools, and manage the associated risks, a careful examination of seismic data from reported cases of induced seismicity and the parameters controlling them is necessary. However, these data are hardly gathered together and are time-consuming to collate as they come from different disciplines and sources. Here, we present a publicly available, multi-physical database of injection-induced seismicity (Kivi et al., 2022a; https://doi.org/10.20350/digitalCSIC/14813), sourced from an extensive review of published documents. Currently, it contains 158 datasets of induced seismicity driven by various subsurface energy-related applications worldwide. Each dataset covers a wide range of variables, delineating general site information, host rock properties, in situ geologic and tectonic conditions, fault characteristics, conducted field operations, and recorded seismic activities. We publish the database in flat-file formats (i.e., .xls and .csv tables) to facilitate its dissemination and utilization by geoscientists while keeping it directly readable by computer codes for convenient data manipulation. The multi-disciplinary content of this database adds unique value to databases focusing only on seismicity data. In particular, the collected data aims at facilitating the understanding of the spatiotemporal occurrence of induced earthquakes, the diagnosing of potential triggering mechanisms, and the developing of scaling relations of maximum possible earthquake magnitudes and operational parameters. Conclusively, the database will boost research in seismic hazard forecasting and mitigation, paving the way for increasing contributions of geoenergy resources to meeting net-zero carbon emissions.
Iman R. Kivi et al.
Status: open (until 28 Apr 2023)
RC1: 'Comment on essd-2022-448', Kwang-Il Kim, 06 Mar 2023
- AC1: 'Reply on RC1', Iman Rahimzadeh Kivi, 16 Mar 2023 reply
Iman R. Kivi et al.
[Dataset] Global physics-based database of injection-induced seismicity https://doi.org/10.20350/digitalCSIC/14813
Iman R. Kivi et al.
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This paper presents comprehensive physics-based database of injection-induced seismicity with descriptions related to its physical and statistical implications for understanding and forecasting of induced seismicity. I think the database adequately covers the vast range of physical parameters from worldwide injection-related geo-energy applications. The manuscript is well written and structured. I see the paper as a useful contribute to ESSD, if the below minor comments are handled appropriately.
1. This study seems not to discriminate the term “induced” and “triggered”, although both terms indicate different nucleation mechanism in some studies (Dahm et al., 2015; McGarr et al., 2002, Ellsworth et al. 2019). Particularly, Ellsworth et al. (2019) classified the mainshock of the Mw 5.5 Pohang earthquake as triggered seismicity, which was initiated by anthropogenic forcing and propagated beyond the bounds of the stimulated region. Other seismic events that occurred during hydraulic stimulations were termed as induced seismicity, of which magnitudes are limited to within the spatial dimension of the stimulated volume (Kim et al., 2022). As mentioned in the manuscript, Mw 5.5 Pohang earthquake is regarded as a representative counter-example of magnitude scaling relations driven by McGarr (2014), but McGarr and Majer (2023) argue that the relationship is intended for earthquakes induced, not triggered. Thus, some descriptions regarding the term “induced” and “triggered” might be needed in the manuscript for the further understanding of the physical mechanism of seismicity.
2. In Figure 5, parameters with the logarithmic scale of y-axis such as permeability, maximum injection rate, maximum injection volume show that the mean value is plotted outside of the boxplot probably due to extremely large or small value of outliers. Particularly, the permeability for “research” is generally one or two order lower than the permeability for “geothermal”, but mean values of both types indicate contrasting result. Mean values calculated by excluding the outliers can better represent the characteristics of the given parameters.
1. L172. The project number is missing in first column of the given excel file.
2. Host rock properties in Figure 2. There is a typo in the unit of thermal expansion coefficient. (1/°K → 1/K)
3. L193: “hydrogeological” properties needs to be changed to “thermal and hydrogeological” properties, as thermal conductivity and thermal expansion coefficient are included in the reservoir rock properties.
Dahm T, Cesca S, Hainzl S, Braun T, Krüger F. Discrimination between induced, triggered, and natural earthquakes close to hydrocarbon reservoirs: a probabilistic approach based on the modeling of depletion-induced stress changes and seismological source parameters. J Geophys Res Solid Earth. 2015;120(4):2491–2509. https://doi.org/10.1002/2014JB011778.
McGarr A, Simpson D, Seeber L. Case Histories of Induced and Triggered Seismicity in International Handbook of Earthquake And Engineering Seismology. San Diego, CA: Acad. Press; 2002.
Ellsworth WL, Giardini D, Townend J, Ge S, Shimamoto T. Triggering of the Pohang, Korea, earthquake (Mw 5.5) by enhanced geothermal system stimulation. Seismol Res Lett. 2019;90(5):1844–1858.
McGarr A. Maximum magnitude earthquakes induced by fluid injection. J Geophys Res Solid Earth. 2014;119(2):1008–1019. https://doi.org/10.1002/2013JB010597.
McGarr A, Majer EL. The 2017 Pohang, South Korea, Mw 5.4 main shock was either natural or triggered, but not induced. Geothermics. 2023;107. 102612.