Fracking: How far from faults?
- 2.6k Downloads
Induced earthquakes and shallow groundwater contamination are two environmental concerns associated with the interaction between hydraulic fracturing (fracking) operations and geological faults. To reduce the risks of fault reactivation and faults acting as fluid conduits to groundwater resources, fluid injection needs to be carried out at sufficient distances away from faults. Westwood et al. (Geomechanics and geophysics for geo-energy and geo-resources, pp 1–13, 2017) suggest a maximum horizontal respect distance of 433 m to faults using numerical modelling, but its usefulness is limited by the model parameters. An alternative approach is to use microseismic data to infer the extent of fracture propagation and stress changes. Using published microseismic data from 109 fracking operations and analysis of variance, we find that the empirical risk of detecting microseismicity in shale beyond a horizontal distance of 433 m is 32% and beyond 895 m is 1%. The extent of fracture propagation and stress changes is likely a result of operational parameters, borehole orientation, local geological factors, and the regional stress state. We suggest a horizontal respect distance of 895 m between horizontal boreholes orientated perpendicular to the maximum horizontal stress direction and faults optimally orientated for failure under the regional stress state.
KeywordsEarthquakes Faults Fracking Hydraulic fracturing Induced Microseismicity
Induced earthquakes caused by hydraulic fracturing (fracking) have been documented in Canada, the United Kingdom (UK) and the United States of America (USA) (Wilson et al. 2017). The occurrence of felt fracking-induced earthquakes is rare but earthquakes up to magnitude 4.6 have been induced (BCOGC 2015) and the smallest reported felt fracking-induced earthquake had magnitude 1.5 (BGS 2017), making fracking-induced earthquakes a matter of public concern. In the paper “Horizontal respect distance for hydraulic fracturing in the vicinity of existing faults in deep geological reservoirs: a review and modelling study”, Westwood et al. (2017) use numerical modelling to investigate how far from faults fluid injection for fracking should be carried out to avoid felt, induced seismicity. They conclude that the maximum horizontal respect distance is 433 m. This horizontal respect distance may also be important for reducing the risk of shallow groundwater contamination; it has been proposed that faults may act as fluid conduits between shales and shallow groundwater resources (Kissinger et al. 2013; Birdsell et al. 2015).
We applaud Westwood et al. (2017) in providing the first analysis of this kind, however a number of factors were kept constant in the modelling scenarios and no uncertainty estimates or sensitivity analyses were carried out on: injection volume, injection rate, Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio, pore pressure, coefficient of friction, friction angle, cohesion, fracture aperture, permeability, compressibility, fracture orientation, or depth. Furthermore, the modelling did not include poroelastic effects. Changes in the model parameters and the inclusion of poroelasticity may lead to different horizontal respect distances. We propose that there is an alternative approach. Microseismic data has been used to suggest a vertical respect distance of 600 m between fracked reservoirs and aquifers (Davies et al. 2012, 2013a), and this research now forms the basis of UK legislation (Infrastructure Act 2015). The purpose of this comment is to augment the study by Westwood et al. (2017) by using microseismic data to empirically determine a horizontal respect distance to faults.
2 Fracking related micro and macroseismicity
Microseismic events are weak earthquakes (the British Geological Survey classify microseismic events as those with magnitudes less than two) of natural or anthropogenic origin. Microseismic monitoring is routinely used during fracking fluid injection to track fracture propagation and infer the extent of stimulated fractures (Mayerhofer et al. 2010). Microseismicity associated with these processes is usually too small to be felt by humans at the surface. Monitoring may also detect seismicity related to the reactivation of pre-existing geological faults (e.g. Kratz et al. 2012). Fault reactivation can be identified by spatial trends in microseismic events or from the occurrence of larger macroseismic events (Davies et al. 2013b). Macroseismic events are more likely to be felt by humans at the surface. The reactivation of faults indicates that injected fluid has reached the fault plane or has perturbed the stress state of the fault without reaching it itself. Microseismic monitoring can thus provide a measure of fracture propagation length and the extent of stress changes beyond the induced fractures.
Peer-reviewed literature and conference papers were searched for plan-view maps or cross sections of fracked boreholes with microseismic data. Maps and cross sections without borehole geometries or scale bars were excluded and scales were adjusted where necessary. The horizontal distances between the furthest detected microseismic events and the associated fluid injection stages were measured. When no stage intervals were shown or it was unclear which stage related to which cluster of microseismic events, the perpendicular distance between the furthest detected microseismic event and the borehole was measured. Where the distance between the furthest detected microseismic event and the borehole was ambiguous because microseismic data from adjacent boreholes overlapped, the distance between the outer borehole and the furthest outer microseismic event was measured. Microseismic event location errors were ignored because most sources did not provide error values. All distances were converted to SI units. The injection volumes, injection rates, and reservoir lithologies were noted where possible.
Analysis of variance (ANOVA) and multiple and partial regression were used to determine statistically significant factors and covariates. Lithology was taken as a factor with three levels (coal, sandstone, or shale) and the covariates were injection volume and injection rate. The Anderson–Darling test was used to assess the normality of the data prior to analysis and if necessary the data were transformed. The ANOVA was performed with and without the covariates, but inclusion of the covariates severely limited the size of the dataset. Therefore, multiple regression was used to understand the role of injection volume and rate, and partial regression analysis was used to estimate the relative importance of these covariates in explaining microseismic distance variation. All statistical significance was judged at the 95% probability of being greater than zero.
5.1 Limitations of microseismic data
All determined microseismic locations have an error associated with them, which may increase or decrease the inferred extent of fractures and stress changes. Additionally, detection will only be complete above a particular magnitude. This magnitude can be calculated from a Gutenberg-Richter plot and is dependent on the sensitivity, location, and type of monitoring equipment (Johnston and Shrallow 2011; Warpinski 2014). Biased detection can lead to misleading microseismic maps (Warpinski 2014) and, if the array is particularly poorly designed, the reactivation of faults could be missed and the inferred extent of stimulation could be entirely controlled by the detection limit. Even for well-designed arrays stress changes may occur beyond recorded microseismic clouds (Lacazette and Geiser 2013).
5.2 Orientation of horizontal boreholes, maximum horizontal stress, and faults
5.3 Horizontal respect distance
Westwood et al. (2017) used numerical modelling to provide a maximum horizontal respect distance of 433 m between fracking fluid injection and faults. However, numerical modelling is limited by the selected model parameters. An alternative approach is to use microseismic data and measure the horizontal distances between fluid injection points and the furthest detected microseismic events. Using a sample set of 109 fracking examples, we find that the empirical risk of detecting microseismicity in shale beyond a horizontal distance of 433 m is 32% and beyond 895 m is 1%. Fracking operations in shales generally had their furthest detected microseismic events at greater distances than those in coals and sandstones. Injection volume and rate both showed statistically significant relationships with the distance to the furthest detected microseismic event. However, there was no evidence that fluid injection parameters explained the microseismic distance differences between lithologies. The extent of fracture propagation and stress changes is likely a result of operational parameters, borehole orientation, local geological factors, and the regional stress state. We suggest a horizontal respect distance of 895 m between horizontal boreholes orientated perpendicular to the maximum horizontal stress direction and faults optimally orientated for failure in their regional stress state. Until further analysis is done using more extensive datasets with known operational parameters and regional stress settings, applying a horizontal respect distance of 895 m between fracking fluid injection points and all faults may be a cautionary approach.
Miles Wilson is funded by a Durham Doctoral Studentship and this research was also carried out as part of the ReFINE (Researching Fracking) consortium led by Newcastle and Durham Universities. ReFINE has been funded by the Natural Environment Research Council (UK), Total, Shell, Chevron, GDF Suez, Centrica and Ineos. The results are solely those of the authors. We thank the ReFINE Independent Science Board for spending time prioritising the research and advice on effective governance. We thank two anonymous reviewers who helped improve the manuscript.
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- British Columbia Oil and Gas Commission (BCOGC) (2015) August seismic event determination. Industry Bulletin 2015–32. https://www.bcogc.ca/node/12951/download. Accessed 11 Oct 2017
- British Geological Survey (BGS) (2017) Earthquakes induced by hydraulic fracturing operations near Blackpool, UK. http://www.earthquakes.bgs.ac.uk/research/BlackpoolEarthquakes.html. Accessed 11 Oct 2017
- Infrastructure Act (2015) Chapter 7, PART 6 Energy, Section 50, Onshore hydraulic fracturing: safeguardsGoogle Scholar
- Johnston R, Shrallow J (2011) Ambiguity in microseismic monitoring. In: 2011 SEG annual meeting. Society of Exploration GeophysicistsGoogle Scholar
- Kilpatrick JE, Eisner L, Williams-Stroud S, Cornette B, Hall M (2010) Natural fracture characterization from microseismic source mechanisms: a comparison with FMI data. In: 2010 SEG annual meeting. Society of Exploration GeophysicistsGoogle Scholar
- Kratz M, Hill A, Wessels S (2012) Identifying fault activation in unconventional reservoirs in real time using microseismic monitoring. In: SPE/EAGE European unconventional resources conference & exhibition—from potential to productionGoogle Scholar
- Mayerhofer MJ, Lolon E, Warpinski NR, Cipolla CL, Walser DW, Rightmire CM (2010) What is stimulated reservoir volume? In: SPE shale gas production conference. Society of Petroleum EngineersGoogle Scholar
- Warpinski NR (2014) A review of hydraulic-fracture induced microseismicity. In: 48th US rock mechanics/geomechanics symposium. American Rock Mechanics AssociationGoogle Scholar
- Westwood RF, Toon SM, Styles P, Cassidy NJ (2017) Horizontal respect distance for hydraulic fracturing in the vicinity of existing faults in deep geological reservoirs: a review and modelling study. In: Geomechanics and geophysics for geo-energy and geo-resources, pp 1–13Google Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.