An integrated approach to characterize hydraulic fracturing-induced seismicity in shale reservoirs

Hui, Gang; Chen, Shengnan; Chen, Zhangxing; Gu, Fan

doi:10.1016/j.petrol.2020.107624

Cited by 31 publications

(23 citation statements)

References 89 publications

(419 reference statements)

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“…In this study, a continuous fault zone is used as an approximation. Prior works suggested that the spatial distribution of induced events (x, y coordinates) could define the possible length and width of inferred faults, corroborated by the three dimensional seismic interpretation results (Hui et al, 2021). Therefore, the possible length and width of the inferred fault in this case are estimated to be approximately 900 and 520 m, respectively.…”

Section: Characterization Of the Inferred Fault And Hydraulic Fractursupporting

confidence: 68%

“…This uncertainty in event hypocenters would pose a negative effect on the simulation work, such as the uncertainty in the fault size and spatial distribution. In this scenario, the available three dimensional seismic reflection data could facilitate determining the relatively reliable location of the inferred fault (Hui et al., 2021). In addition, the in‐situ stress tensors and pore pressure are derived from the treatment and logging data, which also have uncertainty in the stress and pressure estimation.…”

Section: Discussionmentioning

confidence: 99%

“…The measured TOC of other key wells (well 05-18, 14-06, and 08-20) is averaged to be 2.64 ± 0.3%, lower than that in the Fox Creek area, indicating less susceptibility of fault stability in terms of low TOC content (Eyre et al, 2019). The average formation density of 2,671 ± 250 kg/m 3 is obtained from the available logging data of nearby wells (Hui et al, 2021). The geomechanical properties such as Young's modulus (YM = 55 ± 5 GPa) and Poisson's ratio (PR = 0.25 ± 0.02) are derived from the available velocity logging data of nearby wells (Ronald et al, 2019).…”

Section: Determination Of Hydraulic and Geomechanical Properties Andmentioning

confidence: 99%

“…According to the above stress tensors and the focal depth of the induced events, the Mohr diagram is plotted to depict the initial stress state of the source mechanisms prior to fracturing stimulations ( Figure 5). The calculation of the effective normal stress and shear stress is well documented in prior works (Hui et al, 2021). A value of 0.6 for the friction coefficient is adopted under the assumption of a critically stressed state of the inferred fault.…”

Section: 1029/2020gc009563 4 Of 13mentioning

confidence: 99%

“…Statistically, 6% of HF operations targeting the Duvernay Formation are related to the induced seismicity with moment magnitude M L > 3 in WCSB (Ghofrani & Atkinson, 2020). The occurrence of some large magnitude HF‐induced seismicity in WCSB has been linked to site‐specific geological, geomechanical, and operational factors, including the proximity to basement and carbonate reef margins, formation overpressure, shale content and total organic content (TOC), critical stress state of seismogenic faults, the hydraulic connection between preexisting faults and stimulated wells (Eaton & Schultz, 2018; Eyre et al., 2019; Hui et al., 2021; Pawley et al., 2018; Schultz et al., 2017; Zhang et al., 2019). It is noted that the operational factors are aiming to be proxies for whether there are likely to be the necessary conditions present (e.g., specifically, the presence of a critically stressed fault).…”

Section: Introductionmentioning

confidence: 99%

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Insights on Controlling Factors of Hydraulically Induced Seismicity in the Duvernay East Shale Basin

Hui

Chen

et al. 2021

Geochem Geophys Geosyst

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Historically, the Duvernay East Shale Basin had been regarded as a seismicity‐quiescent region. However, an ML 4.18‐magnitude earthquake on 04/03/2019 was triggered due to hydraulic fracturing of two horizontal wells. The physical mechanism and controlling factors of this large‐magnitude earthquake are not well understood. In this work, the coupled modeling of the ML 4.18 case is conducted to quantify the poroelastic effects during fluid injection and to reveal the triggering mechanism of this earthquake cluster. Additional simulations of tested cases with different hydraulic, geomechanical, and operational parameters are also conducted to quantify the effects of these factors on hydraulically induced seismicity. It is found that the hydraulic fractures of two wells propagated within the Duvernay formation and connected with the inferred fault. The increase in pore pressure reduced the shear stress of the fault and caused the fault slip. The hydraulically induced seismicity is susceptible to the low permeable injection layer and high‐permeable fault, less rigid fault with low‐Biot's coefficient, large fluid injection, and proximity of hydraulic fracturing‐fault distance. Enlarging the distance between the stimulated well and seismogenic fault is the first‐order choice to mitigate seismic risks. Under the proximity of well‐fault distance, reducing the fracturing size job would be an effective approach to reduce the expected magnitude of hydraulically induced seismicity.

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Section: Characterization Of the Inferred Fault And Hydraulic Fractursupporting

confidence: 68%

Section: Discussionmentioning

confidence: 99%

Section: Determination Of Hydraulic and Geomechanical Properties Andmentioning

confidence: 99%

Section: 1029/2020gc009563 4 Of 13mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Insights on Controlling Factors of Hydraulically Induced Seismicity in the Duvernay East Shale Basin

Hui

Chen

et al. 2021

Geochem Geophys Geosyst

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Integrated microseismic and geomechanical analysis of hydraulic fracturing induced fault reactivation: a case study in Sichuan Basin, Southwest China

Feng¹,

Luo²,

Chen³

et al. 2023

Geomech. Geophys. Geo-energ. Geo-resour.

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Because of the special geographical location adjacent to the Tibetan Plateau, the geological setting of the Sichuan Basin is very complex, which brings a great challenge to shale gas development. In this study, we conducted an integrated microseismic and geomechanical analysis on a refracturing well in the Sichuan Basin. We observed that casing deformation occurred in the area of fault reactivation. However, the reactivation of pre-existing faults does not always cause casing deformation. In addition, a cluster of high-magnitude microseismic events will be triggered during the fault reactivation, which is also helpful to recognize the reactivated faults. Furthermore, according to the definition of b-value in the Gutenberg–Richter law, a group of high-magnitude microseismic events usually shows a low b-value and vice versa. Based on the analysis of treatment data and microseismicity, we found that there is a positive relationship between b-value and instantaneous shut-in pressure (ISIP): lower b-value represents lower ISIP. The investigation of the stress shadow effect based on the theoretical solution of a plane strain fracture is also convincing to prove the relationship between b-value and ISIP. Therefore, a significant relationship between hydraulic fracturing, microseismicity, and fault reactivation is established. Importantly, some useful implications of this relationship could be utilized for early warning of fault reactivation (probably casing deformation) and optimization of refracturing design for unconventional shale plays.

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Spatial correlation-based machine learning framework for evaluating shale gas production potential: A case study in southern Sichuan Basin, China

Yi,

Qi,

et al. 2024

Applied Energy

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An integrated approach to characterize hydraulic fracturing-induced seismicity in shale reservoirs

Cited by 31 publications

References 89 publications

Insights on Controlling Factors of Hydraulically Induced Seismicity in the Duvernay East Shale Basin

Insights on Controlling Factors of Hydraulically Induced Seismicity in the Duvernay East Shale Basin

Integrated microseismic and geomechanical analysis of hydraulic fracturing induced fault reactivation: a case study in Sichuan Basin, Southwest China

Spatial correlation-based machine learning framework for evaluating shale gas production potential: A case study in southern Sichuan Basin, China

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