Geophysical Journal International最新文献

{"title":"Seafloor Rayleigh ellipticity, measured from unoriented data, and its significance for passive seismic imaging in the ocean","authors":"Sanxi Ai, Takeshi Akuhara, Lipeng He, Cheng Xiong, Zhiyong Yan, Yong Zheng","doi":"10.1093/gji/ggae250","DOIUrl":"https://doi.org/10.1093/gji/ggae250","url":null,"abstract":"Summary Observations of the seafloor Rayleigh ellipticity contribute to seismic imaging in the ocean. To extract such observables from the arbitrarily oriented ocean-bottom seismometer (OBS) data, we develop an orthogonal-regression based approach to measure the waveform amplitude ratios of the unoriented horizontal and vertical components. The amplitude ratios are then used to calculate the Rayleigh ellipticity (and the sensor orientation angle). The robustness of our method is verified by applications to both the unoriented OBS data and the well oriented on-land seismic data. As we propose to calculate the Rayleigh ellipticity directly from the unoriented three-component data, the measurement process avoids the complexity arising from the surface wave non-great circle effects and uncertainties of the OBS sensor orientation angles. Overall the Rayleigh ellipticity measurements from our method are systematically higher than those by conventional analysis and show less uncertainties. Our analyses suggest that the Rayleigh ellipticity curve (14-60 s), which could be retrieved from the raw broadband OBS data, is effective to constrain the oceanic lithosphere structure, and the accurate measurement of Rayleigh ellipticity curve is important. The potential of seafloor Rayleigh ellipticity for seismic imaging in the ocean is evidenced by a case study of the Japan Basin, the Sea of Japan. Considering the insufficient station coverage in the ocean, the single-station measurement of seafloor Rayleigh ellipticity is of significance for OBS community.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"41 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Error propagation and model update analysis in three-dimensional CSEM inversion","authors":"Rahul Dehiya","doi":"10.1093/gji/ggae251","DOIUrl":"https://doi.org/10.1093/gji/ggae251","url":null,"abstract":"Summary This study examines error propagation from data space to model space during three-dimensional inversion of controlled-source electromagnetic data using a Gauss-Newton based algorithm. An expression for model parameter correction is obtained using higher-order generalised singular value decomposition for various regularisation strategies. Inverse modelling is performed for different types of noise employing distinct regularisation schemes to investigate the impact of error. Data corrupted with random noise suggests that the random noise mainly propagates when regularisation parameters are small, owing to the high-frequency nature of random noise. Furthermore, the random noise predominantly causes artefacts in the shallower part of the inverted model. However, it has little impact on the estimation of major anomalies because the anomaly primarily depends on the smoothly varying parts of data. These observations are valid for both isotropic and anisotropic inversions. Resistive geological anomalies, like vertical dyke or vertical fractures, may pose a significant challenge for isotropic inversion in terms of convergence and data fit, even if the subsurface is isotropic. On the other hand, anisotropic inversion performs remarkably well in such cases, showing faster convergence and better data fit than isotropic inversion. Anisotropic inversion is indispensable in the case of an anisotropic host medium, as isotropic inversion produces significant artefacts and poorer data fit. Numerical experiments suggest that, in general, anisotropic inversion produces relatively better data fit and faster convergence, even in the case of isotropic subsurface. However, due to the varying degree of sensitivity of CSEM data on thin resistive bodies, caution is required in interpreting an anisotropy obtained using anisotropic inversion. An investigation of field data also supports the observations obtained using synthetic experiments.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"43 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141744508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Refining tomography with generative neural networks trained from geodynamics","authors":"T Santos, T Bodin, F Soulez, Y Ricard, Y Capdeville","doi":"10.1093/gji/ggae240","DOIUrl":"https://doi.org/10.1093/gji/ggae240","url":null,"abstract":"Summary Inverse problems occur in many fields of geophysics, wherein surface observations are used to infer the internal structure of the Earth. Given the non-linearity and non-uniqueness inherent in these problems, a standard strategy is to incorporate a priori information regarding the unknown model. Sometimes a solution is obtained by imposing that the inverted model remains close to a reference model and with smooth lateral variations (e.g., a correlation length or a minimal wavelength are imposed). This approach forbids the presence of strong gradients or discontinuities in the recovered model. Admittedly, discontinuities, such as interfaces between layers, or shapes of geological provinces or of geological objects such as slabs can be a priori imposed or even suggested by the data themselves. This is however limited to a small set of possible constraints. For example, it would be very challenging and computationally expensive to perform a tomographic inversion where the subducting slabs would have possible top discontinuities with unknown shapes. The problem seems formidable because one cannot even imagine how to sample the prior space: is each specific slab continuous or broken into different portions having their own interfaces? No continuous set of parameters seems to describe all the possible interfaces that we could consider. To circumvent these questions, we propose to train a Generative Adversarial neural Network (GAN) to generate models from a geologically plausible prior distribution obtained from geodynamical simulations. In a Bayesian framework, a Markov chain Monte Carlo algorithm is used to sample the low-dimensional model space depicting the ensemble of potential geological models. This enables the integration of intricate a priori information, parametrized within a low-dimensional model space conducive to efficient sampling. The application of this approach is demonstrated in the context of a downscaling problem, where the objective is to infer small-scale geological structures from a smooth seismic tomographic image.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"70 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141744524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full waveform inversion of cross-hole radio frequency electromagnetic data","authors":"Polina Zheglova, Colin Farquharson, Alison Malcolm","doi":"10.1093/gji/ggae247","DOIUrl":"https://doi.org/10.1093/gji/ggae247","url":null,"abstract":"Summary We consider application of full waveform inversion (FWI) to radio-frequency electromagnetic (EM) data. Radio-frequency imaging (RIM) is a cross-borehole technique to image electromagnetic subsurface properties from measurements of transmitted radio-frequency waves. It is used in coal seam imaging, ore exploration and various engineering and civil engineering applications. RIM operates at frequencies from 50 kHz to several tens of MHz. It differs from other geophysical EM methods, because the frequency band includes the transition between the wave propagation and diffusion regimes. RIM data are acquired in two-dimensional cross-hole sections in a reciprocal manner. Traditionally, radio-frequency data are inverted by straight ray tomography because it is inexpensive and easy to implement. It is argued that due to attenuation, the sensitivity of the transmitted electric field is the strongest within the first Fresnel zone of the ray connecting the transmitter and receiver. While straight ray tomography is a simple to implement and fast method, the non-linearity in the relationship between model parameters and data is often strong enough to warrant non-linear inversion techniques. FWI is an iterative high resolution technique, in which the physical properties are updated to minimize the misfit between the measured and modelled wavefields. Full waveform techniques have been used and extensively studied for the inversion of seismic data, and more recently, they have been applied to the inversion of GPR data. Non-linear inversion methods for RIM data are less advanced. Their use has been hindered by the high cost of full wave modelling and the high conductivity contrasts of many RIM targets, and, to some extent, by the limitations of the measuring instruments. We present the first application of this methodology to simultaneous conductivity and permittivity inversion of RIM data. We implement the inversion in the frequency domain in two dimensions using L-BFGS optimization. We analyze the sensitivity of the data to the model parameters and the parameter trade-off and validate the proposed methodology on a synthetic example with moderate conductivity variations and localized highly conductive targets. We then apply the FWI methodology to a field data set from Sudbury, Canada. For the field data set, we determine the most appropriate preprocessing steps that take into account specific peculiarities of RIM: the insufficient prior information about the subsurface and the limitations of the measuring equipment. We show that FWI is applicable under the conditions of RIM and is robust to imperfect prior knowledge: we obtain satisfactory model recoveries starting from homogeneous initial models in all of our examples. Just as other methods, FWI underestimates large conductivity contrasts due to the loss of sensitivity of the transmitted electric field to the conductivity variations as the conductivity increases above a certain level. The permittivity in","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"114 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141744591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Pn magnitude scale mb(Pn) for earthquakes along the equatorial Mid-Atlantic Ridge","authors":"Won-Young Kim, Guilherme W S de Melo, Marcelo Assumpcao","doi":"10.1093/gji/ggae242","DOIUrl":"https://doi.org/10.1093/gji/ggae242","url":null,"abstract":"Summary We developed a short-period Pn magnitude scale mb(Pn) for earthquakes along the equatorial Mid-Atlantic Ridge. Due to low signal-to-noise ratios, teleseismic body wave magnitude and long-period surface wave magnitude cannot be confidently determined for small earthquakes of mb < 4. Local magnitude scales are also not useful for these events because the oceanic environment does not allow the propagation of crustal phases. However, regional high-frequency Pn waves from these small- to moderate-size (mb 3–6) earthquakes are well recorded in the equatorial Atlantic region and can be used to assign magnitudes. We measured over 2 041 Pn peak amplitudes on vertical records from about 20 stations in northeastern Brazil and 11 stations in western Africa in the distance range of 700–3,700 km. We analyzed data from 189 events from the global centroid moment tensor catalog to tie our mb(Pn) scale to MW so that seismic moments can be readily estimated. Pn arrivals show apparent group velocity between 7.9 km/s at short ranges (∼1,000 km) and up to 9.1 km/s at 3,500 km. The measured peak amplitudes have a frequency between 0.8 and 3 Hz at 1 000–1,800 km, but at greater distances, 1 800–3,700 km, they show a remarkably consistent frequency of about 0.8 Hz. The peak amplitude attenuates at a higher rate at short distances (∼0.65 magnitude units between 700–2,000 km) but attenuates at a lower rate at long distances (∼0.35 magnitude units between 2 000 and 3,700 km). The low rate of amplitude decay with distance and nearly constant frequency content of the peak amplitudes suggest that Pn waves propagate efficiently in the lower part of the upper mantle in the equatorial Atlantic Ocean basins. These are important attributes of oceanic Pn waves that can be used to assign magnitude for small- to moderate-size earthquakes in the equatorial mid-Atlantic region. The estimated station corrections correlate well with upper mantle low-velocity anomalies, especially in Brazil.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"7 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multivariate variational mode decomposition to extract the stripe noise in GRACE harmonic coefficients","authors":"Guangyu Jian, Fang Zou, Chuang Xu, Zhengwen Yan","doi":"10.1093/gji/ggae241","DOIUrl":"https://doi.org/10.1093/gji/ggae241","url":null,"abstract":"Summary In this work, a novel method has been developed to remove the north-south stripe noise in the Level-2 spherical harmonic coefficient products collected by the Gravity Recovery and Climate Experiment (GRACE) mission. The proposed method extracts the stripe noise from the Equivalent Water Height (EWH) map via the Multivariate Variational Mode Decomposition algorithm. The idea behind our method is to extract the co-frequency mode in multiple-channel series in the longitude direction. The parameters of our method are empirically determined. The investigation in a closed-loop simulation proves the improvement of our methods compared with the Singular Spectrum Analysis Spatial (SSAS) filter. Subsequently, the spatial-domain and spectral-domain investigations are conducted by using real GRACE data. Our method only suppresses stripe noise at low latitudes (30°S∼30°N) and imposes an order-dependent impact on spherical harmonic coefficients but with potential over-smoothing. Meanwhile, the well-documented water level proves that our method further reduces outliers in a time series of localized mass variations compared with the SSAS filter. More importantly, users are allowed to reduce the filtering strength of our method to preserve small-scale strong signals while suppressing stripe noise. Moreover, noise levels over the ocean at low latitudes are evaluated as well. The noise level of our method using empirical parameters is 32.48 mm of EWH, with 31.54 and 53.52 mm for SSAS and DDK6, respectively. Our work introduces a novel method to address the issue of north-south stripe noise in the spatial domain.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"59 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lateral and vertical variations of seismic anisotropy in the lithosphere-asthenosphere system underneath Central Europe from long-term splitting measurements","authors":"Yvonne Fröhlich, Michael Grund, Joachim R R Ritter","doi":"10.1093/gji/ggae245","DOIUrl":"https://doi.org/10.1093/gji/ggae245","url":null,"abstract":"Summary Backazimuthal variations in the shear wave splitting of core-refracted shear waves (SKS, SKKS, and PKS phases, jointly referred to as XKS) at the Black Forest Observatory (BFO, Southwest Germany) indicate small-scale lateral and partly vertical variations of the seismic anisotropy. However, existing anisotropy studies and models for the nearby Upper Rhine Graben (URG) area in the northern Alpine foreland are mostly based on short-term recordings and by this suffer from a limited backazimuthal coverage and averaging over a wide or the whole backazimuth range. To identify and delimit laterally confined anisotropy regimes in this region, we carry out XKS splitting measurements at six neighbouring (semi-)permanent broadband seismological recording stations (inter-station distance 10-80 km). We manually analyse long-term (partly > 20 yr) recordings to achieve a sufficient backazimuthal coverage to resolve complex anisotropy. The splitting parameters (fast polarization direction $phi $, delay time $delta t$) are determined in a single- and multi-event analysis. We test structural anisotropy models with one layer with horizontal or tilted symmetry axis and with two layers with horizontal symmetry axes (transverse isotropy). To account for lateral variations around a single recording site, modelling is compared for the whole and for limited backazimuth ranges. Based on this, we provide a 3-D block model with spatial variation of anisotropic properties. Based on delay times > 0.3 s and missing discrepancies between SKS and SKKS phases, which do not support lower mantle anisotropy, the found anisotropy is placed in the lithosphere and asthenosphere. The spatial distribution as well as the lateral and backazimuthal variations of the splitting parameters confirm lateral and partly vertical variations in anisotropy. On the east side of the URG, we suggest two anisotropic layers in the Moldanubian Zone (south) and one anisotropic layer in the Saxothuringian Zone (north). In the Moldanubian Zone, a change of the fast polarization directions is observed between the east and the west side of the URG, indicating different textures. At the boundary between the two terranes, an inclined anisotropy is modelled which may be related with deformation during Variscan subduction. Regarding the observation of numerous null measurements and inconsistent splitting parameters, especially (southwest of BFO) in the southern URG, different hypothesis are tested: scattering of the seismic wavefield due to small-scale lateral heterogeneities, a vertical a-axis due to a vertical mantle flow related to the Kaiserstuhl Volcanic Complex, as well as a different preferred orientation of the olivine crystals (not A-type, but C-type) due to specific ambient conditions (high temperature, water content).","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"40 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-guided deep learning-based inversion for airborne electromagnetic data","authors":"Sihong Wu, Qinghua Huang, Li Zhao","doi":"10.1093/gji/ggae244","DOIUrl":"https://doi.org/10.1093/gji/ggae244","url":null,"abstract":"Summary The Earth's subsurface structure provides critical insights into sustainable resource management and geologic evolution. The airborne electromagnetic (AEM) method is an efficient data acquisition technique and can be used to image the underground resistivity structure with high spatial resolution. However, inversion of the increasingly huge volume of AEM data poses a heavy computational burden. In this study, we develop a hybrid deep learning-based approach by employing the physics-guided neural network (PGNN) which incorporates the governing physical laws into the loss function to solve the AEM inverse problem. The PGNN integrates the strength of data-driven method for representation learning with electromagnetic laws and allows for the underlying physical constraints to be strictly satisfied. We validate the effectiveness of our approach using both synthetic and field datasets. Compared with the classic Gauss-Newton method, our PGNN inversion system shows strong robustness against multiple noise sources and reduces the risk of being trapped in local extrema. Moreover, the PGNN-inverted results are physically more consistent with the AEM observations compared to the purely data-driven approach. Application to the field AEM data from Northern Australia demonstrates that the PGNN-based inversion framework effectively estimates the subsurface electrical properties with considerable lateral continuity and significantly higher efficiency, completing the inversion of more than 2734000 AEM soundings taking only minutes on a common PC. Our proposed PGNN-based method shows great promise for large-scale underground resistivity imaging, and the well-identified subsurface resistivity structure can effectively improve our understanding of resource distributions and geological hazards.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"32 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic structure of the Balmuccia Peridotite from a high-resolution refraction and reflection survey","authors":"Damian Pasiecznik, Andrew Greenwood, Florian Bleibinhaus, György Hetényi","doi":"10.1093/gji/ggae239","DOIUrl":"https://doi.org/10.1093/gji/ggae239","url":null,"abstract":"Summary In anticipation of a forthcoming scientific deep drilling initiative within the Western Alps near Balmuccia, Italy, a high-resolution seismic survey is performed at the proposed drill site. This site is situated within the Ivrea Verbano Zone (IVZ), characterized by lower-crustal materials and fragments of upper mantle rocks exposed adjacent to the Insubric Line. The 2-km-long seismic survey crosses an isolated km-scale outcrop of peridotite near the town of Balmuccia. Applying P-wave traveltime tomography, a substantial contrast in seismic velocities is identified, with velocities in the range of 1–8 km s−1. The peridotite displays velocities ranging from 6 to 8 km s−1. The higher velocities near 8 km s−1 are consistent with laboratory measurements on small-scale samples, while the low velocity areas within the peridotite body reflect the influence of fractures and faults. The mean velocity derived for the peridotite body is ca. 7 km s−1. The reflection seismic analysis reveals subvertical reflectors positioned at the peridotite boundaries mapped at the surface, converging at a depth of ca. 0.175 km b.s.l. which images a lens-like structure for the peridotite body. However, the area beneath the imaged lens and the deeper Ivrea Geophysical Body (IGB) suggested by earlier studies is not well imaged, which leaves room for other interpretations regarding the relationship of these two bodies. Prior geophysical investigations provide only approximate depth estimates for the top of the IGB, spanning between 1–3 km depth b.s.l. Although the reflection data does not exhibit a series of continuous reflectors beneath the peridotite, a prominent reflection at ca. 1.3 km depth may indicate the top of the IGB.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"53 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging the ETAS model to forecast mining microseismicity","authors":"Mohammadamin Sedghizadeh, Matthew van den Berghe, Robert Shcherbakov","doi":"10.1093/gji/ggae236","DOIUrl":"https://doi.org/10.1093/gji/ggae236","url":null,"abstract":"Mining operations result in changes of the subsurface stress field that can lead to the occurrence of microseismic events. The development of strategies for forecasting and avoidance of significant events is crucial for safe and efficient operations of mines. One such example, discussed here is the observed induced microseismicity in soft rock potash mines. It is primarily driven by the rock excavations but can also be triggered by preceding events or can result from the delayed effects of plastic creep of soft rocks. Therefore, it is important from seismic hazard assessment and risk mitigation points of view to understand the statistical aspects of microseismicity in potash or other types of mines. In this study, the temporal evolution of the induced microseismicity from a potash mine in Saskatchewan is analyzed and modeled. Specifically, the epidemic type aftershock sequence (ETAS) model is used to approximate the occurrence rate of the induced mining microseismicity. The estimated parameters signify that the microseismicity displays swarm-type characteristics with limited inter-event triggering. Moreover, the Bayesian predictive framework is used to compute the probabilities of the occurrences of the largest expected events above a certain magnitude for prescribed forecasting time intervals during the evolution of the sequence. This approach for computing the probabilities allows one to incorporate fully the uncertainties of the model parameters. The Markov Chain Monte Carlo (MCMC) sampling of the posterior distribution are used to generate parameter chains to quantify their variability. Furthermore, several statistical tests are conducted to assess the credibility of the obtained retrospective forecasts compared to the observed microseismicity. The obtained results show that the developed approach can accurately forecast the number of events and intensity of the sequence. It also provides a framework for computing the probabilities for the largest expected events.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":"43 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}