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ABSTRACT Characterization of a productive oil/gas well blowout through seismological methods is relatively uncommon. In this paper, we conduct an in-depth seismic evaluation of one of the

world’s most significant onshore oil well blowout incidents, which occurred in 2020 at the Baghjan oil field in Assam, northeast India. We show that the blowout and related on-site

activities generated distinct signals that can be distinguished by their spectral characteristics, temporal variation in geometric spreading, and sharp attenuation of daytime noise in

comparison to the nighttime. A micro-earthquake potentially triggered by the blowout was also detected. Furthermore, we show how seismic data can be used to reasonably estimate blowout gas

exit velocity and flame height. Our results demonstrate that a detailed characterization and spatiotemporal variation of blowout activity can be successfully captured through seismic

monitoring, opening new opportunities for hazard mitigation and cost-effective disaster management for such catastrophic events. SIMILAR CONTENT BEING VIEWED BY OTHERS SPATIOTEMPORAL

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March 2022 INTRODUCTION Oil well blowouts resulting in the uncontrolled release of natural gas or oil have been a well-known hazard of oil and gas exploration and production. Although the

largest known blowouts have occurred offshore1,2, the limited data available suggests that onshore wells are more prevalent and may experience higher failure rates3, possibly due to older

infrastructure and not as much oversight4. Davies et al. documented over 4 million onshore wells with failure rates from 2 to 75% across just nine nations with acceptably reliable data

(i.e., Australia, Austria, Bahrain, Brazil, Canada, the Netherlands, Poland, UK, USA), though these numbers likely underestimate true rates due to poor reporting3. Onshore wells are also at

higher risk than offshore wells of contaminating groundwater, surface water, and wetland ecosystems, and pose a higher direct hazard to human life4. As oil well infrastructure ages, the need

for enhanced remote monitoring strategies is growing. Here we report a novel case study documenting, to our knowledge, the first use of passive seismic monitoring to track the

characteristics of an active blowout event. On May 27, 2020, oil well no. 5 of the Baghjan oil field (operated by Oil India Limited (OIL)) in the Tinsukia district of Assam experienced one

of the most severe onshore blowouts in the world (see Fig. 1a, and Supplemental Material). The event ignited a catastrophic jet fire that raged at temperatures exceeding 1000 °C from June 9

to November 15, 2020, causing widespread evacuations and a few fatalities, with an estimated USD 3.2 billion of ecological damages5. The blowout had far-reaching consequences, not only on

the environment but also on noise pollution and ground vibrations, soil and water pollution, and thermal pollution that significantly impacted the lives of the nearby communities. The fire

at the blowout well, sourced by uninterrupted upwelling of natural gas and condensate at more than 4,000 psi, perpetually flamed with an average height of 108 m. The spontaneous noise

produced from the well, similar to that of the sound of a jet-engine, reached more than 100 dB within 100 m radius and more than 50 dB within 5 km radius. The flames of the blowout raised

the heat of both the air and water of the surrounding area by ~ 7 °C above the ambient temperature, amounting to thermal pollution. In the aftermath of this event, it has also resulted in

the loss of an estimated 55 per cent of the biodiversity in the affected Dibru-Saikhowa National Park. As many as 1,632 hectares of wetland, 523 ha of grassland, 172 ha of area covering

rivers and streams, and 213 ha of forest were damaged to varying degrees based on the proximity of the ecosystem to the blowout6. Experts say it may take more than 10 years for even a

partial recovery of the destruction caused to the landscape7. To the best of our knowledge, this event is one of the worst onshore blowout-fueled jet fires that has been documented in

history6 and therefore warrants multidisciplinary studies which can help in prevention and mitigation of such accidents in the future. Here, we investigate characteristics of seismo-acoustic

noise, in particular “air-ground-coupled-air” waves (AGCA)8,9,10 generated by the blowout, as well as related activities, captured on a temporary broadband seismic network. Our results

provide new insights into blowout conditions and highlight the potential advantages of employing seismo-acoustic monitoring for remote detection and management of blowout events and related

activities. A literature review on similar events, such as explosions and gas pipeline bursts, highlights the distinctive advantages of using seismic data in studying these occurrences,

offering insights that few other methods can provide. Koper et al.11 discuss seismic recordings of a natural gas pipeline explosion in Carlsbad, New Mexico, on August 19, 2000. Their study

analyzed the recorded seismic signals during which they identified three impulsive events and two extended seismic events related to the explosion and continuous emanation of the flaming

gases, respectively. Their study provided insights into the nature and timing of the pipeline explosion event. The seismic analysis was valuable for law enforcement agencies investigating

this incident and for litigation processes. A related study by Stahler et al.12 investigated recorded seismic events linked to the Nordstream pipeline subsea explosions in the Baltic Sea.

They located two significant seismic events near the observed methane plumes by analyzing the polarization of seismic signals from multiple stations. This study is an example of the

application of seismology in locating the explosions and thus establishing the cause of the pipeline burst, which is useful for mitigating the harmful effects of such explosions. The Barros

et al.13 study of the 2020 Beirut explosion, one of the largest non-nuclear explosions in history, employed seismic and infrasound data for their investigation. Their study estimated the

explosion’s epicenter, magnitudes, and explosive yield highlighting the joint analysis of seismo-acoustic signals to better understand and quantify large-scale explosions. Another study

which follows a similar methodology, Evers et al.14 investigates a gas pipeline explosion near Ghislenghien, Belgium, using seismo-acoustic methods. Their analysis used array-processing

techniques and atmospheric models to determine the explosion’s origin time and location and yield using data from several seismic and infrasound stations. A similar study by Schneider et

al.15 investigates the Baumgarten gas explosion in Austria using seismo-acoustic methods. The study describes the explosion’s characteristics by analyzing data from seismic and infrasound

stations and modeling ray paths in the atmosphere. These studies highlight the effectiveness of seismic and acoustic methods in forensic investigations of analyzing non-tectonic seismic

events such as explosions, which is important to people and society. Seismological studies of explosions, therefore provide insights for future mitigation and response strategies along with

the scientific characterization of the events. The information that these studies provide, such as the precise location and timing of explosions, is useful for law enforcement and

investigative agencies. These studies also help us understand the dynamics of explosions, which can help formulate safety protocols and standards customized for a specific operation or area.

Therefore, integrating seismological monitoring program into safety and planning frameworks is an important component of explosion risk management. The preliminary report on the Baghjan gas

blowout by the Central Pollution Control Board, Government of India (2020) also highlights concerns regarding the seismic vulnerability of the region in the wake of the gas blowout, which

motivated the seismic monitoring that forms the basis of this study. The northeastern state of Assam, India, where the gas blowout took place, is a region prone to seismic activity, having

recorded many earthquakes in the past16,17,18,19. The continuous gas blowouts and further drilling attempts to bring it under control could also have potentially generated induced

seismicity, so monitoring with local seismic stations was necessary. Fluvial floodplains and wetlands characterize the local landscape of the region, which would also have amplified ground

motion in the case of any induced seismicity, making this area particularly susceptible to damage from seismic activity. The same report also highlights that constant tremor related to the

gas blowout caused significant damage to the area’s infrastructure, roads, and homes. These vibrations had adversely affected the local community, causing physical and mental stress,

disrupting education and livelihood, and impacting the health of residents. After the blowout was subdued, seismological monitoring provided data on the intensity and frequency of these

tremors that can be used for remedial and compensatory relief measures. The impact of this gas blowout was severe enough to warrant other studies using remote sensing data to study the

environmental impact (Arandhara et al.20). Our seismological study of the event enhances the damage assessment by showcasing the extent of ground vibrations and its variations in space and

time, that can affect nearby structures and ecosystems. In this case, seismological studies complement conventional environmental assessment techniques and taken together offer a more

comprehensive understanding of the blowout’s impact on the surrounding sensitive ecosystem. FIRST DETECTION OF AN ONSHORE BLOWOUT-TRIGGERED EARTHQUAKE? Earthquakes induced by oil and gas

extraction activities are a known phenomenon21,22,23. Here we investigate whether earthquakes might have been induced by the Baghjan blowout. Our data showcases the first reported

micro-earthquake associated with a blowout event, at a distance of about 5 km south of the well and at a depth of ~ 1.9 km (Mc 0.5, Fig. 1a). Based on a global compilation of injection

well-induced earthquakes, Goebel and Brodsky24 showed that many such earthquakes occur at distances from the well ranging from 10 m to over 10 km. The triggering mechanism of induced

earthquakes are, however, not yet fully understood, and exceptions exist such as the Bakken Shale Formation in North Dakota, which has experienced little to no induced seismicity despite

thousands of injection wells being in operation there25,26. Thus, given that we do not yet have a fully-developed understanding of a possible blowout inducing mechanism as in the injection

well induced case, we can only speculate that this earthquake at ~ 5 km distance from the blowout might be what we refer to here as a “blowout quake.” If the blowout did indeed trigger this

earthquake, this might represent the first recorded earthquake directly linked to a well blowout. The earthquake’s shallow depth further suggests it could be an induced phenomenon.

Identifying the exact cause of this “blowout quake” remains challenging, though rapid changes in subsurface pore pressure resulting from the blowout are a plausible explanation.

Additionally, the shutdown of nearby wells during the blowout could have forced fluids to migrate, potentially altering the pore pressure conditions. TYPE OF NOISE Frequency-domain analysis

of the seismic data recorded in this study reveals the presence of high-energy monochromatic signals, which we interpret as stemming from human activity, such as the use of electric

generators and water pumps during fire-fighting efforts. Conversely, the broad pulses detected could likely be linked to mini-explosion—sudden fluctuations in the gas jet flux emanating from

the blowout well. The estimated maximum Peak Particle Velocity (PPV) was 0.22 mm/s at the nearest station (BJN5) and the minimum was 0.095 mm/s at a farther station (BJN3). We observe a

clear daily variation in seismic amplitude (Fig. 1b–d), with high noise levels lasting ~ 8 h per day during typical daytime working hours and lulls over nights and weekends, indicating that

high amplitudes correspond with human activities. Because most human activity in this area throughout the study involved fire suppression at the blowout site, the majority of this noise was

likely generated by a combination of fire suppression activities, continuous gas blowout and continuously operating machines such as water pumps. Evenings and weekends are typically

characterized by continuous lower levels of noise likely dominated by noise generated by uncontrolled release of gas, as well as water pumps that ran continuously throughout the study

period, creating a ‘water-umbrella’ to manage temperatures in the blowout site27. At several times throughout the study period, noise levels dropped dramatically for several minutes. Outside

of these quiet periods, clear amplitude peaks at 2–3 Hz and 5–8 Hz are observed at nearly all seismic stations (Fig. 1b), visible as prominent spectral stripes in a daylong spectrogram

(Fig. 1b). These bands disappear during periods of reduced noise, when energy is distributed relatively evenly over 1–10 Hz. We therefore interpret the 2–3 Hz and 5–8 Hz bands as

blowout-generated noise. During working hours, the noise level is elevated over broad frequency bands, typically 1–30 Hz, which we infer to be caused by people actively working and operating

machines at the blowout site. We also observe several distinct impulse signals throughout the study period. One of the clearest impulse signals was recorded on July 16, 2020 (Fig. 1b), at

the end of a period of reduced noise. Vertical and radial component seismograms of this pulse show relatively high energy with little energy on the transverse component (Fig. 2a). Particle

motion also shows elliptical motion in the vertical-radial plane (Fig. 2b) suggesting that the pulse is composed of Rayleigh waves. Spectral characteristics of the pulse match the 2–3 and

5–8 Hz bands found during times of active gas blowout, suggesting that the noise produced by the gas blowout is also dominated by Rayleigh waves (Fig. 2c). We use this impulsive

mini-explosion signal as a template and apply a match filter technique to identify similar pulses during the 17-day study period. Such impulse signals typically occur in clusters and are

observed sporadically throughout the duration studied here, both at day and night times, suggesting they are likely smaller explosions producing weak pulses of AGCA Rayleigh waves. It is

important to note that the frequency bands can vary depending on the individual characteristics of the blowout event and the surrounding geological environment. In this case, the blowout

site is located at soft alluvium where the predominant frequency of the site is lower, thus the appearance of prominent spectral stripes at lower frequencies. Had it been a rocky site, the

predominant frequency of the site could have been higher, thus influencing the prominent spectral stripes. A more comprehensive analysis, including additional data (e.g., recording of

background seismic noise after controlling the blowout at the same locations where recording was done during blowout) and modeling, would be necessary to provide a definitive explanation for

the observed frequency bands. NOISE ATTENUATION We use the blowout as the assumed source of noise and determine its seismic attenuation, which we attribute to be mostly geometrical

spreading, and its diurnal variation. Near the source, geometrical spreading is the dominant factor that determines how ground shaking decays with distance28. Ground shaking is controlled by

the source, path, and near-surface site conditions. During the study period, path and site conditions remain nearly unchanged. Thus, geometrical spreading is an important element of

modeling predicted ground motion in an area29,30. It is typically determined by analyzing natural earthquakes data18,19,20. In this case, however, we took a novel approach of determining

geometrical spreading from a coherent, near-continuous and strong noise source. Time also provides an additional dimension in this study, as the noise characteristics change throughout the

day. As discussed earlier in detail, there are three types of noise recorded here. Here, we determine geometrical spreading separately using different types of noise occurring in different

time periods and compare them. Surprisingly, geometrical spreading appears to vary over time in the study area, which as described below can be explained by different types of waves (body

waves and surface waves) mixed in different proportions dominating the ground motion at different times (Fig. 2d; Table 1). Amplitudes of seismic surface and body waves theoretically decay

at R−0.5 and R−1, respectively, where R is distance from the source. Noise in this study is dominated by the blowout, which is by far the strongest continuous source of noise in the study

area. Generally, we find that the amplitude of noise in the study area decays at a rate close to R−0.5 indicating that the wavefield is dominated by surface waves (Fig. 2d) as suggested by

previous analyses of the impulse signal. Surface waves from the blowout are the main source of noise during nighttime periods (R−0.46). Daytime amplitude decay consistently shows steeper

slopes(R−0.61) compared to nighttime even though the amplitude is higher compared to nighttime (Fig. 2d). We can conceive of no mechanistic reason for surface wave amplitudes to decay faster

with distance during the day, and therefore infer that the apparent increase in decay rate results from the near-field signal being a combination of body waves produced by human activities

during the day superposed on surface waves from the blowout. The impulse signal detected on July 16, 2020 occurred during daytime at around 16:00 h (IST) and decays at a rate of R−0.581,

suggesting that higher amplitude surface waves from the impulse are reducing the relative dominance of daytime anthropogenic body waves. This observation supports our conclusion that the

impulse is likely a result of small explosion during blowout. We have performed this analysis over various frequency ranges spanning 1 to 30 Hz. The highest concentration of energy is

observed below 10 Hz, although considerable energy can be seen up to 30 Hz as well. Increasing frequency from 10 Hz to 30 Hz, however, does not change the decay slope significantly, implying

that even at higher frequencies surface waves dominate the wavefield (Fig. 2d). This is because inelastic attenuation is nonlinear and higher frequencies decay with distance at a faster

rate. We thus conclude that, geometrical spreading is likely the controlling factor for amplitude decay at this distance. Notably, the decay rate during one of the short periods of reduced

noise is almost flat suggesting no strong coherent source of noise active in the area during this calm period. This suggests that more localized noise dominates the wavefield around each

seismometer during these times, supporting our conclusion that the calm periods reflect short pauses or significant reductions of the blowout. This is a reasonable interpretation considering

that crews were trying to plug the blowout during this time. SOURCE CHARACTERIZATION The arrival times of the pulse that occurred on July 16, 2020 could be precisely picked at different

stations of the network (Fig. 3a). Joint inversion of these arrival times for source location and propagation velocity indicates acoustic waves that originated from a source located at the

blowout site. (Fig. 3b,c). The continuous background noise exhibits the largest coherence over the 1–3 Hz frequency band (Fig. 4a), which corresponds to the stationary vibrations also

observed in the daylong spectrograms of Fig. 1b. Coherency analysis is utilized to derive accurate estimates of differential travel times between stations. The inversion of these times

reveals a stationary source location, which coincides with the blowout site. The amplitude of the signal exhibits a characteristic daily pattern, likely reflecting the disturbances generated

by the fire extinguishing operations (Fig. 4b), as described in previous sections in detail. The composite location map shown in Fig. 4c exhibits a pronounced peak at the blowout site, with

average discrepancies of approximately 50 m and 150 m along the east-west (EW) and north-south (NS) directions, respectively. These discrepancies arise due to deviations from the

assumptions of constant sound velocity and a static atmosphere, which we initially adopted for predicting travel times. ESTIMATING JET CHARACTERISTICS Our analyses suggest that the blowout

generated AGCA Rayleigh waves which are acoustic waves that impinge on the Earth’s surface and generate (i.e., couple to the ground as) seismic surface waves31,32,33. Similar signals are

frequently produced by volcanic eruptions so acoustic infrasound recordings have been extensively utilized in monitoring and surveillance of active volcanoes to detect eruptions in remote

locations, measure eruptive parameters, and infer eruption source processes34,35. The acoustic power radiated during gaseous volcanic eruptions has been shown to correlate positively with

gas exit velocity, in turn exhibiting a positive correlation with ash plume height. We apply this theory described for volcanic jet aeroacoustics36 to the gas explosion of the Baghjan

blowout. Assuming that the ground motion is linked to AGCA waves, we use seismic recordings from each station to estimate the infrasonic acoustic pressure at the source. As a result, we

obtain estimates for the gas exit velocity, which is approximately 1260 m/s, and the flame height, which is approximately 97 m. (See _Methods_, in _Supplementary Material_ for a complete

description of this analysis.). Despite the use of several simplifying assumptions in this approach (Methods), these model results are remarkably consistent with field-reported values of ~ 

1000 m/s and ~ 100 m, respectively (Table 2 in Supplementary Material)6. CONCLUSIONS In this study, we analyzed continuous recordings of seismic noise collected by a temporary seismic

network installed within a 10 km radius of the Baghjan well blowout site for a total duration of 17 days. Our analysis documents details of the characteristics of seismic data recorded in

the vicinity of the blowout, and also documents what we conclude to be the first known case of a blowout microearthquake. This documentation contributes to a growing database and

understanding of how seismological analysis elucidates the phenomenon of oil and gas well blowout accidents. Further investigation of past and future seismic data recorded in the vicinity of

blowouts will help determine whether such events are common, and could contribute to our growing knowledge of the mechanics and mitigation strategies for these types of oil and gas well

explosion accidents, as well as for other environmental hazards associated with oil and natural gas producing facilities, such as the well-known conundrum of injection-induced earthquakes.

The precise source locations and detailed source property characteristics obtained in this study indicate that densely distributed permanent or temporary seismic networks can effectively

supplement existing, but sparsely located, infrasound arrays. This approach provides valuable information for identifying and locating infrasonic blowout sources at both local and regional

scales. Several lines of evidence suggest that sustained ground vibrations observed in the 2–3 Hz and 5–8 Hz bands are likely associated with the propagation of blowout-generated acoustic

waves dynamically coupled to the ground as Rayleigh waves. Our estimates of gas jet velocity and flame height obtained from acoustic power suggest that seismic instruments could provide a

real-time tool to inform emergency response personnel regarding pragmatic intervention through quantitative monitoring of such events. Our detection of explosion clustering also suggests the

potential for future development of seismic early warning systems to improve safety measures for disaster response crews. To the best of our knowledge, no studies have previously documented

seismic signals during an active and continuous blowout of an oil/gas well. However, dense seismic arrays are currently used in several oil producing countries for monitoring the activity

of producing oil and gas wells37,38, providing a convenient pathway to adapt existing resources for emergency monitoring. This work thus paves the way to a vast array of seismological

applications for the rapid assessment and ongoing monitoring of hazardous phenomena. DATA AVAILABILITY The raw seismic Data can be provided with a request to the Director, CSIR-NEIST Jorhat

at [email protected] via Gmail Drive. The link of the Gmail drive is https://drive.google.com/drive/folders/1c8n1ckVUbcbzp7FHM68BqJFNDxyu7BHy in main manuscript. REFERENCES *

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Implications for tensile fracture development. _Geophys. Res. Lett._ 44, 4814–4819 (2017). Article  ADS  Google Scholar  Download references ACKNOWLEDGEMENTS We thank Government of Assam for

help rendered during execution of the project. CSIR, Govt. of India is also thankfully acknowledge for their help and necessary permission. Oil India Limited (OIL), Duliajan, Assam, India

provided financial support via Ref No. OIL/CONT/LOA/G/134/2020-21; date: 24/06/2020. Thanks to all the project members for executing the project during CoVID-19 pandemic period. Special

thanks to Dr. Saurabh Baruah, Chief Scientist, CSIR-NEIST Jorhat and Mr. I. Baruah, OIL, Duliajan, Assam, India for their help in executing the project. We thank the anonymous reviewers and

Editor for their constructive comments in improving the paper. Thanks to Dr. V. M. Tiwari, Director, CSIR-NEIST, Jorhat, Assam, India for his permission to publish this article. AUTHOR

INFORMATION AUTHORS AND AFFILIATIONS * CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India Santanu Baruah, Manoj K. Phukan, G. Narahari Sastry, Sausthov M.

Bhattacharyya, Chandan Dey, Kimlina Gogoi, Timangshu Chetia & Prachurjya Borthakur * Academy of Scientific and Innovative Research, Ghaziabad, Uttar Pradesh, 201 002, India Santanu

Baruah, Kimlina Gogoi & Prachurjya Borthakur * Department of Earth and Planetary Sciences, University of California, Riverside, USA Shankho Niyogi & Abhijit Ghosh * Istituto

Nazionale di Geofisica e Vulcanologia - Sezione di Pisa, Via C. Battisti, Pisa, Italy Davide Piccinini & Gilberto Saccorotti * Department of Earth and Environmental Sciences, Boston

College, Chestnut Hill, MA, 02467, USA Alan L. Kafka * Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, USA Danica Roth *

Environment and Forest Department, Government of Assam, Guwahati, India Mahendra Kumar Yadava * Department of Biotechnology, Indian Institute of Technology-Hyderabad, Kandi, Telangana,

502285, India G. Narahari Sastry * Geohazards Research Centre, King Abdulaziz University, Jeddah, Saudi Arabia Mohamed F. Abdelwahed * Formerly at Geological Survey of India, Kolkata, India

J. R. Kayal * National Institute of Technology-Agartala, Agartala, Tripura, 799046, India J. R. Kayal * Department of Geosciences, University of Malta, Msida, MSD, 2080, Malta Sebastiano

D’Amico * Assam State Disaster Management Authority (ASDMA), Assam Secretariate, Government of Assam, Dispur, Guwahati, Assam, 781005, India Nandita Dutta * Institute of Seismological

Research, Government of Gujarat, Gandhinagar, Gujarat, 382009, India Sowrav Saikia Authors * Santanu Baruah View author publications You can also search for this author inPubMed Google

Scholar * Shankho Niyogi View author publications You can also search for this author inPubMed Google Scholar * Abhijit Ghosh View author publications You can also search for this author

inPubMed Google Scholar * Davide Piccinini View author publications You can also search for this author inPubMed Google Scholar * Gilberto Saccorotti View author publications You can also

search for this author inPubMed Google Scholar * Alan L. Kafka View author publications You can also search for this author inPubMed Google Scholar * Danica Roth View author publications You

can also search for this author inPubMed Google Scholar * Mahendra Kumar Yadava View author publications You can also search for this author inPubMed Google Scholar * Manoj K. Phukan View

author publications You can also search for this author inPubMed Google Scholar * G. Narahari Sastry View author publications You can also search for this author inPubMed Google Scholar *

Mohamed F. Abdelwahed View author publications You can also search for this author inPubMed Google Scholar * J. R. Kayal View author publications You can also search for this author inPubMed

 Google Scholar * Sausthov M. Bhattacharyya View author publications You can also search for this author inPubMed Google Scholar * Chandan Dey View author publications You can also search

for this author inPubMed Google Scholar * Kimlina Gogoi View author publications You can also search for this author inPubMed Google Scholar * Timangshu Chetia View author publications You

can also search for this author inPubMed Google Scholar * Prachurjya Borthakur View author publications You can also search for this author inPubMed Google Scholar * Sebastiano D’Amico View

author publications You can also search for this author inPubMed Google Scholar * Nandita Dutta View author publications You can also search for this author inPubMed Google Scholar * Sowrav

Saikia View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS S.B. conceptualized the work. S.B., A.G., D.P., G.S. J.R.K., C.D. wrote the original

manuscript. S.B., A.L.K., D.R., S.M.B., M.F.A., S.D.A. performed the seismic analysis. S.B., A.G., S.N. and S.M.B. performed the noise analysis. D.P., G.S. performed the infrasound

analysis. S.B., M.K.P., S.M.B., and C.D. performed the field surveys including data generation and collection. M.K.Y. performed various survey related to study of the flame, pollution,

impact assessment and other. S.B., M.K.P., G.N.S. assisted with the project management and field work coordination. Thorough check-up of the results obtained are performed by: S.B., A.G.,

D.P., G.S., A.L.K., D.R., M.F.A., S.D.A. The manuscript was reviewed by S.B., A.L.K., D.R., J.R.K. and G.N.S. The manuscript has been formatted and figures have been comprehensively detailed

by S.B., K.G., T.C., P.B., N.D., and S.S. All authors interpreted and discussed the final results, and edited, reviewed and approved the final manuscript. CORRESPONDING AUTHORS

Correspondence to Santanu Baruah, Abhijit Ghosh or Gilberto Saccorotti. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S

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ABOUT THIS ARTICLE CITE THIS ARTICLE Baruah, S., Niyogi, S., Ghosh, A. _et al._ Seismic monitoring of 2020 Baghjan oil-well blowout incident in Assam, India. _Sci Rep_ 14, 24108 (2024).

https://doi.org/10.1038/s41598-024-74428-y Download citation * Received: 30 November 2023 * Accepted: 26 September 2024 * Published: 15 October 2024 * DOI:

https://doi.org/10.1038/s41598-024-74428-y SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * Baghjan oil-blowout * Blowout quake * Rayleigh waves *

Air-ground-coupled air waves (AGCA)