Iason Grigoratos

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Grigoratos

First Name

Iason

ORCID

0000-0002-1637-2007

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Publications1 - 10 of 15

Variability of Seismicity Rates and Maximum Magnitude for Adjacent Hydraulic Stimulations
Kwiatek, Grzegorz; Grigoratos, Iason; Wiemer, Stefan (2025)
Seismological Research Letters
We hindcasted the seismicity rates and the next largest earthquake magnitude using seismic and hydraulic data from two hydraulic stimulation campaigns carried out in adjacent (500 m apart) ultra‐deep wells in Finland. The two campaigns performed in 2018 and 2020 took place in the frame of the St1 Helsinki project producing stable, pressure‐controlled induced seismic activity with the maximum magnitudes of 1.7 and 1.2, respectively. The seismicity rates were modeled using simplified physics‐based approaches tailored to varying injection rates. This is the first time that this framework was applied to a cyclical injection protocol. The next largest earthquake magnitude was estimated using several existing models from the literature. Despite the close proximity of the two hydraulic stimulations and associated seismicity, we obtained strongly different parameterizations of the critical model components, questioning the usefulness of a priori seismic hazard modeling parameters for neighboring stimulation. The differences in parameterization were attributed to the contrasting hydraulic energy rates observed in each stimulation, small differences in the fracture network characteristics of the reservoir and resulting seismic injection efficiency, and potentially to variations in the injection protocol itself. As far as the seismicity rate model is concerned, despite a good performance during the 2018 campaign, the fit during the 2020 stimulation was suboptimal. Forecasting the next largest magnitude using different models led to a very wide range of outcomes. Moreover, their relative ranking across stimulations was inconsistent, including the situation when the best‐performing model in the 2018 stimulation turned out to be the worst one in the 2020 stimulation.
Thousands of Induced Earthquakes per Month in West Texas Detected Using EQCCT
Chen, Yangkang; Savvaidis, Alexandros; Saad, Omar M.; et al. (2024)
Geosciences
West Texas has been a seismically active region in the past decade due to the injection of industrial wastewater and hydrocarbon exploitation. The newly founded Texas seismological network has provided a catalog that characterizes the intense seismicity down to a magnitude of 1.5 Ml. However, there are numerous small-magnitude events (Ml < 1.0) occurring every day that are not analyzed and reported, due to the prohibitively high workload to manually verify the picks from automatic picking methods. We propose to apply an advanced deep learning method, the earthquake compact convolutional transformer (EQCCT), to unleash our power in analyzing hundreds of small earthquakes per day in West Texas. The EQCCT method is embedded in an integrated-detection-and-location framework to output a highly complete earthquake catalog, given a list of available seismic stations, in a seamless way. The EQCCT has enabled us to detect and locate 50-times more earthquakes (mostly smaller than magnitude 1) than we previously could. We applied the EQCCT-embedded detection and location workflow to the Culberson and Mentone earthquake zone (CMEZ) in West Texas and detected thousands of earthquakes per month for consecutively three months. Further relocation of the new catalog revealed an unprecedentedly high-resolution and precise depiction of shallow and deep basement-rooted faults. The highly complete catalog also offers significant insights into the seismo-tectonic status of the CMEZ. Association with nearby injection activities also revealed a strong correlation between the rate of injected fluid volume and the number of small earthquakes.
Building a probabilistic seismic hazard and risk model for EGS stimulations
Grigoratos, Iason; Papadopoulos, Athanasios N.; Ciardo, Federico; et al. (2022)
Seismological Research Letters
A hydraulic fracturing stimulation of around 650 m3 is to be conducted at the FORGE site in Utah in mid-April 2022, as part of a research study on Enhanced Geothermal Systems. In anticipation of this event, we built a site-specific probabilistic seismic hazard and risk model, in order to assess the potential effects of the upcoming stimulation around the site. The logic tree had more than 150 branches, with different branching levels for the seismicity rate model, the b-value, the maximum magnitude, and the ground shaking intensity model. The results presented here are magnitude exceedance probabilities, Modified Mercalli Intensity maps, and fatality risk for individuals in a hypothetical timber house 2 and 15 km away from the injection well. The estimated MMI values remain below 2 even at the site, while the individual risk at 2 km is above one in a million only if we assume a response similar to the average among 19 previous globally- sourced EGS stimulations.
A generic seismic risk protocol for energy production sites
Grigoratos, Iason; Schultz, Ryan; van Ginkel, Janneke; et al. (2025)
Bulletin of Earthquake Engineering
Activities related to energy production have been linked with felt (and in some cases damaging) earthquakes. Notable examples include hydraulic fracturing, wastewater disposal, geothermal systems, coal mining, carbon storage and hydropower dams. As the demand for energy continues to grow, new frontiers in energy exploration will emerge - some with the potential for induced seismicity. Thus, there is a clear need for a source-agnostic seismic risk protocol that can be applied to any activity or region. This study outlines one such implementation that uses scenario earthquakes to produce a priori risk thresholds that can be referenced against current seismicity levels on an ongoing basis. Our framework is designed to inform regulatory decisions by considering the consequences of earthquake scenarios on the population and the built environment, together with simplified forecasts of the next largest magnitude. The proposed framework can tackle both the screening process needed for permitting purposes and serve as a risk management plan during operations.
The spatial distribution of causal factors behind the seismicity in the Delaware basin
Grigoratos, Iason; Savvaidis, Alexandros; Rathje, Ellen (2022)
Our analysis hindcasts seismicity rates of magnitude (M) ≥ 1.5 in the Delaware Basin (West Texas) from 2017 through 2019 on a 5km grid using either HF or SWD data as input, and compares them against the null hypothesis of solely tectonic loading. Each block is assigned a p-value, indicating the statistical confidence of its causal link with either HF, shallow SWD or deep SWD injection operations. To do that we expanded the framework of Grigoratos et al. (2020) to daily hydraulic fracturing (HF) operations and pressure-driven modeling of wastewater disposal (SWD). Our results indicate that 60% of the earthquakes occurred in blocks with p ≤ 0.05 (95% confidence interval) for at least one examined causal factor, and are thus triggered by oil and gas activities. This percentage increases to 68% for p ≤ 0.10 (90% confidence interval). Overall, more events than previously identified are associated with HF, especially within Reeves county. That said, shallow SWD is linked to more earthquakes, likely reactivating parallel faults of significant length. The seismicity around Pecos city seems to be affected by more than one injection activity, with higher frequency operational data and better depth resolution needed to fully decouple causality. Finally, within Culberson county, the only area where the earthquakes occur predominantly within the basement, the identified triggering mechanism is far-field SWD from deep wells.
Seven Thousand Felt Earthquakes in Oklahoma and Kansas Can Be Confidently Traced Back to Oil and Gas Activities
Grigoratos, Iason; Savvaidis, Alexandros; Wiemer, Stefan (2025)
GeoHazards
The seismicity levels in Oklahoma and southern Kansas have increased dramatically over the last 15 years. Past studies have identified the massive disposal of wastewater co-produced during oil and gas extraction as the driving force behind some earthquake clusters, with a small number of events directly linked to hydraulic fracturing (HF) stimulations. The present investigation is the first one to examine the role both of these activities played throughout the two states, under the same framework. Our findings confirm that wastewater disposal is the main causal factor, while also identifying several previously undocumented clusters of seismicity that were triggered by HF. We were able to identify areas where both causal factors spatially coincide, even though they act at distinct depth intervals. Overall, oil and gas operations are probabilistically linked at high confidence levels with more than 7000 felt earthquakes (M ≥ 2.5), including 46 events with M ≥ 4.0 and 4 events with M ≥ 5. Our analysis utilized newly compiled regional earthquake catalogs and established physics-based principles. It first hindcasts the seismicity rates after 2012 on a spatial grid using either real or randomized HF and wastewater data as the input, and then compares them against the null hypothesis of purely tectonic loading. In the end, each block is assigned a p-value, reflecting the statistical confidence in its causal association with either HF stimulations or wastewater disposal.
Rapid identification of induced seismicity using deep learning in West Texas
Chen , Yangkang; Grigoratos, Iason; Yang , Liuqing; et al. (2025)
Geophysical Journal International
Timely identification of the triggering mechanism behind the observed seismicity in areas with multiple overlapping human activities is an important research topic that can facilitate effective measures to mitigate the seismic hazard. This task is particularly challenging when dealing with delayed operational data, uncertain focal depths or uneven seismic monitoring coverage. Here, we propose a deep learning (DL) framework to identify which human activity triggered a certain earthquake in near real-time using only seismic waveforms as input. We use an advanced architecture, the compact convolutional transformer (CCT), to extract high-level abstract features from the three-component seismograms and then use an advanced capsule neural network to link the induced seismicity in West Texas with three potential causal factors, that is, hydraulic fracturing (HF), shallow saltwater disposal (SWDsh) or deep saltwater disposal (SWDdp). The training data was prepared based on an established probabilistic approach that combined physics-based principles with both real and reshuffled injection data to hindcast past seismicity rates. In the end, each activity was assigned a confidence level for association at the 5 km spatial scale. Even though the training data include only 981 events, we obtain over 90 per cent accuracy for all three causal factors for both the single- and multistation versions of the model.
An updated parametric catalog of historical earthquakes around the Dead Sea Transform Fault Zone
Grigoratos, Iason; Poggi, Valerio; Danciu, Laurentiu; et al. (2020)
Journal of Seismology
In this study, we present the work done to review the existing historical earthquake information of the Dead Sea Transform Fault Zone (DSTFZ). Several studies from various sources have been collected and reassessed, with the ultimate goal of creating of new homogenized parametric earthquake catalog for the region. We analyze 244 earthquakes between 31 BC and 1900, which are associated with the geographical buffer extending from 27 N to 36 N and from 31 E to 39 E. Of these, 93 were considered real seismic events with moment magnitude (Mw) greater than 5 that indeed occurred within this zone. While we relied on past parametric data and did not assign new macroseismic intensities, magnitude values, or epicenters for several controversial events, we did however resort to the primary sources to obtain a more critical perspective for the various assigned macroseismic intensities. In order to validate the derived parametric information, we tried to associate the events present in the historical records, with any evidence coming from past field investigations, i.e., geological or archaeological studies. Acknowledging the uneven quality and quantity of data reporting each event, we provided each entry with an uncertainty range estimate. Our catalog lists 33 events of Mw ≥ 6 absent from the latest published compilation with compatible time span and areal coverage. The whole catalog is considered complete down to Mw 7 and in certain areas down to Mw 6 after the year 1000, with majority of the larger earthquakes located in the part of DSTFZ, which extends from the southeast part of Dead Sea lake till Antioch.
Revisiting the Seismicity in the Eagle Ford Shale: The Overlooked Role of Wastewater Disposal
Grigoratos, Iason; Savvaidis, Alexandros; Wiemer, Stefan (2025)
The Seismic Record
The seismicity in the Eagle Ford play has increased dramatically over the last decade. Past studies identified hydraulic fracturing (HF) as the only driving force in this area. We conclude that although HF is the dominant causal factor, wastewater disposal (SWD) was also a triggering mechanism in certain zones. Notably, in the center of the shale, there is a small area where both causal factors overlap. Furthermore, a cluster of earthquakes on the Mexican side of the national border is almost certainly triggered by SWD within Texas. To our knowledge, this is the first such documented case globally. Next, our analysis investigated the causal factors of the 2011 M$_w$ 4.8 Fashing earthquake and of two recent M$_w$ 3.9 events, while also confirming that HF was the key driving force behind the 2018 M$_w$ 4.0 rupture. We employed new earthquake catalogs, established physics-based principles, and a robust hypothesis testing framework.
Distinguishing the Causal Factors of Induced Seismicity in the Delaware Basin: Hydraulic Fracturing or Wastewater Disposal
Grigoratos, Iason; Savvaidis, Alexandros; Rathje, Ellen (2022)
Seismological Research Letters
Identifying the causal factors behind elevated seismicity rates in areas with multiple ongoing oil and gas activities has always been a challenging issue that is lacking a homogeneous response, hindering regulatory actions. A good example is the Delaware basin, inWest Texas and NewMexico, where the seismicity rates have been gradually increasing since 2009. To study the area, we expand the framework presented in Grigoratos et al. (2020a) to daily hydraulic fracturing (HF) operations and pressure-driven modeling of wastewater disposal (SWD). Our analysis hindcasts seismicity rates of magnitude (M) 1.5 events after 2017 on a 5 km grid using either HF or SWD data as input and compares them against the null hypothesis of solely tectonic loading. In the end, each block is assigned a p-value, indicating the statistical confidence of its causal link with either HF, shallow SWD or deep SWD injection operations. Our results indicate that 68% of the earthquakes occurred in blocks with p 0.05 (95% confidence interval) for at least one examined causal factor and are thus triggered by oil and gas activities. This percentage increases to 81% for p 0.10 (90% confidence interval). Overall, more events than previously identified are associated with HF, especially within Reeves County. That said, shallow SWD is linked to many more earthquakes, likely reactivating parallel faults of significant length. We should note the seismicity around Pecos city seems to be affected by more than one injection activity, with higher frequency operational data and better depth resolution needed to fully decouple causality between HF and shallow SWD. Within Culberson County, and around the epicenter of the 2020 Mentone Mw 5.0 earthquake, the earthquakes occur predominantly within the basement, with the identified triggering mechanism being SWD from deep wells.

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Iason Grigoratos

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