Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

Face stability is an essential issue in tunnel design and construction.Layered rock masses are typical and ubiquitous;uncertainties in rock properties always exist.In view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit analysis.An efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty effects.Ten input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random variables.The effects of these parameter uncertainties on the failure probability and sensitivity indices are discussed.In addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,respectively.The results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom layer.The efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

Quantitative estimation of bubble volume fraction of submarine seep plumes by modeling seismic oceanography data

Submarine seep plumes are a natural phenomenon in which different types of gases migrate through deep or shallow subsurface sediments and leak into seawater in pressure gradient.When detected using acoustic data,the leaked gases frequently exhibit a flame-like structure.We numerically modelled the relationship between the seismic response characteristic and bubble volume fraction to establish the bubble volume fraction in the submarine seep plume.Results show that our models are able to invert and predict the bubble volume fraction from field seismic oceanography data,by which synthetic seismic sections in different dominant frequencies could be numerically simulated,seismic attribute sections(e.g.,instantaneous amplitude,instantaneous frequency,and instantaneous phase)extracted,and the correlation between the seismic attributes and bubble volume fraction be quantitatively determined with functional equations.The instantaneous amplitude is positively correlated with bubble volume fraction,while the instantaneous frequency and bubble volume fraction are negatively correlated.In addition,information entropy is introduced as a proxy to quantify the relationship between the instantaneous phase and bubble volume fraction.As the bubble volume fraction increases,the information entropy of the instantaneous phase increases rapidly at the beginning,followed by a slight upward trend,and finally stabilizes.Therefore,under optimal noise conditions,the bubble volume fraction of submarine seep plumes can be inverted and predicted based on seismic response characteristics in terms of seismic attributes.

Time-domain dynamic constitutive model suitable for mucky soil site seismic response

Soil nonlinear behavior displays noticeable effects on the site seismic response.This study proposes a new functional expression of the skeleton curve to replace the hyperbolic skeleton curve.By integrating shear modulus and combining the dynamic skeleton curve and the damping degradation coefficient,the constitutive equation of the logarithmic dynamic skeleton can be obtained,which considers the damping effect in a soil dynamics problem.Based on the finite difference method and the multi-transmitting boundary condition,a 1D site seismic response analysis program called Soilresp1D has been developed herein and used to analyze the time-domain seismic response in three types of sites.At the same time,this study also provides numerical simulation results based on the hyperbolic constitutive model and the equivalent linear method.The results verify the rationality of the new soil dynamic constitutive model.It can analyze the mucky soil site nonlinear seismic response,reflecting the deformation characteristics and damping effect of the silty soil.The hysteresis loop area is more extensive,and the residual strain is evident.

Introduction to a recently released dataset entitled CSNCD:A Comprehensive Dataset of Chinese Seismic Network

China and its adjacent regions are heavily affected by earthquake disasters,which has led to strong demand and vigorous development of the Chinese Seismic Network(CSN).Since 2004,China Earthquake Networks Center(CENC)has been authorized by China Earthquake Administration(CEA)to take charge of CSN management,mainly observing product output and quality control.

A reweighted damped singular spectrum analysis method for robust seismic noise suppression

(Multichannel)Singular spectrum analysis is considered as one of the most effective methods for seismic incoherent noise suppression.It utilizes the low-rank feature of seismic signal and regards the noise suppression as a low-rank reconstruction problem.However,in some cases the seismic geophones receive some erratic disturbances and the amplitudes are dramatically larger than other receivers.The presence of this kind of noise,called erratic noise,makes singular spectrum analysis(SSA)reconstruction unstable and has undesirable effects on the final results.We robustify the low-rank reconstruction of seismic data by a reweighted damped SSA(RD-SSA)method.It incorporates the damped SSA,an improved version of SSA,into a reweighted framework.The damping operator is used to weaken the artificial disturbance introduced by the low-rank projection of both erratic and random noise.The central idea of the RD-SSA method is to iteratively approximate the observed data with the quadratic norm for the first iteration and the Tukeys bisquare norm for the rest iterations.The RD-SSA method can suppress seismic incoherent noise and keep the reconstruction process robust to the erratic disturbance.The feasibility of RD-SSA is validated via both synthetic and field data examples.

Resilience-incorporated seismic risk assessment of precast concrete frames with“dry”connections

A resilience-incorporated risk assessment framework is proposed and demonstrated in this study to manifest the advantageous seismic resilience of precast concrete frame(PCF)structures with“dry”connections in terms of their low damage and rapid recovery.The framework integrates various uncertainties in the seismic hazard,fragility,capacity,demand,loss functions,and post-earthquake recovery.In this study,the PCF structures are distinguished from ordinary reinforced concrete frame(RCF)structures by characterizing multiple limit states for the PCF based on its unique damage mechanisms.Accordingly,probabilistic story-wise pushover analyses are performed to yield story-wise capacities for the predefined limit states.In the seismic resilience analysis,a step-wise recovery model is proposed to idealize the functionality recovery process,with separate considerations of the repair and non-repair events.The recovery model leverages the economic loss and downtime to delineate the stochastic post-earthquake recovery curves for the resilience loss estimation.As such,contingencies in the probabilistic post-earthquake repairs are incorporated and the empirical judgments on the recovery parameters are largely circumvented.The proposed framework is demonstrated through a comparative study between two“dry”connected PCFs and one RCF designed as alternative structural systems for a prototype building.The results from the risk quantification indicate that the PCFs show reduced loss hazards and lower expected losses relative to the RCF.Particularly,the PCF equipped with energy dissipation devices at the“dry”connections largely reduces the expected economic loss,downtime,and resilience loss by 29%,56%,and 60%,respectively,compared to the RCF.

The 2023 Turkey earthquake doublet: Earthquake relocation, seismic tomography, and stress field inversion

On February 6,2023,two earthquakes with magnitudes of M_(W) 7.8 and M_(W) 7.5 struck southeastern Turkey,causing significant casualties and economic losses.These seismic events occurred along the East Anatolian Fault Zone,a convergent boundary between the Arabian Plate and the Anatolian Subplate.In this study,we analyze the M_(W) 7.8 and M_(W) 7.5 earthquakes by comparing their aftershock relocations,tomographic images,and stress field inversions.The earthquakes were localized in the upper crust and exhibited steep dip angles.Furthermore,the aftershocks occurred either close to the boundaries of low and high P-wave velocity anomaly zones or within the low P-wave velocity anomaly zones.The East Anatolia Fault,associated with the M_(W) 7.8 earthquake,and the SürgüFault,related to the M_(W) 7.5 earthquake,predominantly experienced shear stress.However,their western sections experienced a combination of strike-slip and tensile stresses in addition to shear stress.The ruptures of the M_(W) 7.8 and M_(W) 7.5 earthquakes appear to have bridged a seismic gap that had seen sparse seismicity over the past 200 years prior to the 2023 Turkey earthquake sequence.

On electro-acoustic characteristics of a marine broadband sparker for seismic exploration

The construction of major marine infrastructure projects and the exploration and development of deep-sea mineral resources require fine imaging of seabed strata and structures.The highresolution marine seismic exploration based on a high broadband sparker source is an important approach to reveal seabed stratum and reservoir structure,and identify geohazard.To optimize the performance of sparker seismic source,we investigated the electro-acoustic characteristics of spark discharge under conditions of different charging voltages and electrode numbers.Results show that the sound source level increased with the increase of the charging voltage,whereas the main frequency decreased when the charging voltage increases.In addition,it was found that the charging capacitance had more obvious influence on the main frequency than the sound source level did.Although the load energy decreased with increasing electrode number,the sound source level still increased but the main frequency decreased.Meanwhile,the primary to bubble(P/B)ratio increased with the increase of the electrode number.To gain a deeper insight into the electro-acoustic characteristics,we investigate the relationship between sound source level and power peak,from which a good correlation was observed.A more practical statistical analysis on the rise rate of current was processed,and a perfect logarithmic function was derived.Furthermore,we found that the main frequency was most possibly subjected to the electrical energy,especially the charging energy per electrode.The results indicate that the charging energy per electrode less than 10 J could increase the main frequency to above 300 Hz.At last,the main frequency could be reduced to 20 Hz when the charging energy of a single-electrode discharge was enhanced to over 4 kJ.This study shall be helpful in developing a sparker seismic source and improving the performance for marine engineering exploration and geohazard assessment.

Hcable for Time-Lapse Seismic Monitoring of Marine Carbon Capture and Storage

To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established techniques from various fields, and the seismic method proves to be the crucial one. This method is widely used to determine the CO_(2) distribution, image the plume development, and quantitatively estimate the concentration. Because both the CO_(2) distribution and the potential migration pathway can be spatially small scale, high resolution for seismic imaging is demanded. However, obtaining a high-resolution image of a subsurface structure in marine settings is difficult. Herein, we introduce the novel Hcable(Harrow-like cable system) technique, which may be applied to offshore CCS monitoring. This technique uses a highfrequency source(the dominant frequency>100 Hz) to generate seismic waves and a combination of a long cable and several short streamers to receive seismic waves. Ultrahigh-frequency seismic images are achieved through the processing of Hcable seismic data. Hcable is then applied in a case study to demonstrate its detailed characterization for small-scale structures. This work reveals that Hcable is a promising tool for timelapse seismic monitoring of oceanic CCS.

Detailed seismic zoning of the East Kazakhstan region in the Republic of Kazakhstan

Kazakhstan is currently drafting new construction regulations that comply with the major provisions of the Eurocodes.Such regulations are created on the basis of seismic zoning maps of various degrees of detail,developed by our Institute of Seismology using a new methodological approach for Kazakhstan.The article is about creating the first normative map of the Detailed Seismic Zoning on a probabilistic foundation for the Republic of Kazakhstan’s East Kazakhstan region.We carried out the probabilistic assessment of seismic hazard using a methodology consistent with the main provisions of Eurocode 8and updated compared with that used in developing maps of Kazakhstan’s General Seismic Zoning and seismic microzoning of Almaty.The most thorough and current data accessible for the area under consideration were combined with contemporary analytical techniques.Updates have been done to not only the databases being used but also the way seismic sources were shown,including active faults now.On a scale of 1:1000000,precise seismic zoning maps of the East Kazakhstan region were created for two probabilities of exceedance:10%and 2%in 50 years in terms of peak ground accelerations and macroseismic intensities.The obtained seismic hazard distribution is generally consistent with the General Seismic Zoning of Kazakhstan’s previous findings.However,because active faults were included and a thoroughly revised catalog was used,there are more pronounced zones of increased danger along the fault in the western part of the region.In the west of the territory,acceleration values also increased due to a more accurate consideration of seismotectonic conditions.Zoning maps are the basis for developing new state building regulations of the Republic of Kazakhstan.

Application of 9-component S-wave 3D seismic data to study sedimentary facies and reservoirs in a biogasbearing area:A case study on the Pleistocene Qigequan Formation in Taidong area,Sanhu Depression,Qaidam Basin,NW China

To solve the problems in restoring sedimentary facies and predicting reservoirs in loose gas-bearing sediment,based on seismic sedimentologic analysis of the first 9-component S-wave 3D seismic dataset of China,a fourth-order isochronous stratigraphic framework was set up and then sedimentary facies and reservoirs in the Pleistocene Qigequan Formation in Taidong area of Qaidam Basin were studied by seismic geomorphology and seismic lithology.The study method and thought are as following.Firstly,techniques of phase rotation,frequency decomposition and fusion,and stratal slicing were applied to the 9-component S-wave seismic data to restore sedimentary facies of major marker beds based on sedimentary models reflected by satellite images.Then,techniques of seismic attribute extraction,principal component analysis,and random fitting were applied to calculate the reservoir thickness and physical parameters of a key sandbody,and the results are satisfactory and confirmed by blind testing wells.Study results reveal that the dominant sedimentary facies in the Qigequan Formation within the study area are delta front and shallow lake.The RGB fused slices indicate that there are two cycles with three sets of underwater distributary channel systems in one period.Among them,sandstones in the distributary channels of middle-low Qigequan Formation are thick and broad with superior physical properties,which are favorable reservoirs.The reservoir permeability is also affected by diagenesis.Distributary channel sandstone reservoirs extend further to the west of Sebei-1 gas field,which provides a basis to expand exploration to the western peripheral area.

Potential of the Arkhangelsk seismic network for European Arctic monitoring

The Arkhangelsk Seismic Network(ASN)of the N.Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences,founded in 2003,includes 10 permanent seismic stations located on the coasts of the White,Barents,and Kara Seas and on the Arctic archipelagos of Novaya Zemlya,Franz Josef Land,and Severnaya Zemlya.The network is registered with the International Federation of Digital Seismograph Networks and the International Seismological Center.We used not only ASN data to process earthquakes but also the waveforms of various international seismic stations.The 13,000 seismic events were registered using ASN data for 2012-2022,and for 5,500 of them,we determined the parameters of the earthquake epicenters from the European Arctic.The spatial distribution of epicenters shows that the ASN monitors not only the main seismically active zones but also weak seismicity on the shelf of the Barents and Kara Seas.The representative magnitude of ASN was ML,rep=3.5.The level of microseismic noise has seasonal variations that affect the registration capabilities of each station included in the ASN and the overall sensitivity of the network as a whole.In summer,the sensitivity of the ASN decreased owing to the increasing microseismic and ambient noises,whereas in winter,the sensitivity of the ASN increased significantly because of the decrease.

A regression approach for seismic first-break picking

The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)technology.However,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-noise ratio(SNR)situations.To address this issue,we propose a regression approach to pick FBs based on bidirectional long short-term memory(Bi LSTM)neural network by learning the implicit Eikonal equation of 3D inhomogeneous media with rugged topography in the target region.We employ a regressive model that represents the relationships among the elevation of shots,offset and the elevation of receivers with their seismic traveltime to predict the unknown FBs,from common-shot gathers with sparsely distributed traces.Different from image segmentation methods which automatically extract image features and classify FBs from seismic data,the proposed method can learn the inner relationship between field geometry and FBs.In addition,the predicted results by the regressive model are continuous values of FBs rather than the discrete ones of the binary distribution.The picking results of synthetic data shows that the proposed method has low dependence on label data,and can obtain reliable and similar predicted results using two types of label data with large differences.The picking results of9380 shots for 3D seismic data generated by vibroseis indicate that the proposed method can still accurately predict FBs in low SNR data.The subsequent stacked profiles further illustrate the reliability and effectiveness of the proposed method.The results of model data and field seismic data demonstrate that the proposed regression method is a robust first-break picker with high potential for field application.

Equivalent linear model for seismic damage evaluation of single-degree-of-freedom systems representing reinforced concrete structures considering cyclic degradation behavior

In this study,a novel equivalent damping ratio model that is suitable for reinforced concrete(RC)structures considering cyclic degradation behavior is developed,and a new equivalent linearization analysis method for implementing the proposed equivalent damping ratio model for use in seismic damage evaluation is presented.To this end,Ibarra’s peak-oriented model,which incorporates an energy-based degradation rule,is selected for representing hysteretic behavior of RC structure,and the optimized equivalent damping for predicting the maximum displacement response is presented by using the empirical method,in which the effect of cyclic degradation is considered.Moreover,the relationship between the hysteretic energy dissipation of the inelastic system and the elastic strain energy of the equivalent linear system is established so that the proposed equivalent linear system can be directly integrated with the Park-Ang seismic model to implement seismic damage evaluation.Due to the simplicity of the equivalent linearization method,the proposed method provides an efficient and reliable way of obtaining comprehensive insight into the seismic performance of RC structures.The verification demonstrates the validity of the proposed method.

Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

Viscoelastic stress change from the 1931 M_(w)7.8 Fuyun earthquake and its impacts on seismic activity around the Altai mountains

The 1931 M_(w)7.8 Fuyun earthquake occurred around the Altai mountains, an intracontinental deformation belt with limited active strain-rate accumulation. To explore whether seismic activity in this deformation belt was affected by stress interaction among different active faults, we calculate the Coulomb failure stress change(ΔCFS) induced by the Fuyun earthquake due to coseismic deformation of the elastic crust and postseismic viscoelastic relaxation of the lower crust and upper mantle. Numerical results show that the total ΔCFS at a 10-km depth produced by the Fuyun earthquake attains approximately 0.015-0.134 bar near the epicenter, and just before the occurrence of the 2003 M_(w)7.2 Chuya earthquake, which distances about 400 km away from the Fuyun earthquake. Among the increased ΔCFS,viscoelastic relaxation from 1931 to 2003 contributes to approximately 0.014-0.131 bar, accounting for>90% of the total ΔCFS. More importantly, we find that for the recorded seismicity in the region with a radius of about 270 km to the Fuyun earthquake from 1970 to 2018, the percentage of earthquakes that fall in positive lobes of ΔCFS resolved on the NNW-SSE Fuyun strike-slip fault, on the NWW-SEE Irtysh strike-slip fault, and on the NW-SE Kurti reverse fault is up to 67.22%-91.36%. Therefore, the predictedΔCFS suggests that the impact of the 1931 M_(w)7.8 Fuyun earthquake on seismic activity around the Altai mountains is still significant as to hasten occurrence of the 2003 M_(w)7.2 Chuya earthquake at a relatively far distance and to trigger its aftershocks in the near-field even after several decades of the mainshock.

Seismic fragility analysis of three-tower cable-stayed bridges with different connection configurations

Seismic fragility analysis of three-tower cable-stayed bridges with three different structural systems,including rigid system(RS),floating system(FS),and passive energy dissipation system(PEDS),is conducted to study the effects of connection configurations on seismic responses and fragilities.Finite element models of bridges are established using OpenSees.A new ground motion screening method based on the statistical characteristic of the predominant period is proposed to avoid irregular behavior in the selection process of ground motions,and incremental dynamic analysis(IDA)is performed to develop components and systems fragility curves.The effects of damper failure on calculated results for PEDS are examined in terms of seismic response and fragility analysis.The results show that the bridge tower is the most affected component by different structural systems.For RS,the fragility of the middle tower is significantly higher than other components,and the bridge failure starts from the middle tower,exhibiting a characteristic of local failure.For FS and PEDS,the fragility of the edge tower is higher than the middle tower.The system fragility of RS is higher than FS and PEDS.Taking the failure of dampers into account is necessary to obtain reliable seismic capacity of cable-stayed bridges.

Study on the tunnel shape and soil-lining interaction influencing the lining behavior under seismic loading

The response of tunnels subjected to seismic loading is a complex mechanism and depends not only on the seismic nature but also on tunnel structure and surrounding soil properties.The individual behavior of circular,rectangular,and sub-rectangular tunnels subjected to seismic loadings has already been studied in the literature.In the present research,two case scenarios of circular,rectangular tunnels and four sub-rectangular shaped tunnels,with similar cross-section areas,were adopted to perform a comprehensive numerical investigation.The purpose of the study was to determine the mechanical behavior of tunnels of different shapes,depending upon seismic conditions.Analyses were performed by considering the influence of soil-lining interaction,soil parameters,and lining thickness,as well as lining rigidity.Computations were performed for no-slip and full-slip conditions.The results indicate that the tunnel shape design is of great importance when regarding the mechanical behavior of the surrounding soil.This concerns no-slip as well as full-slip soil-lining interaction,especially when the lining is subjected to seismic loading.Moreover,it is shown that changes in incremental bending moments for circular,rectangular and sub-rectangular tunnels that depend upon the soil-lining interaction conditions differ significantly.

Quantifying the Effects of Near-Surface Viscosity on Seismic Acquisition Geometry: A case study from Chepaizi Exploration Area, Junggar Basin (NW China)

The Chepaizi Exploration Area,Junggar Basin(NW China)holds substantial importance for seismic exploration endeavors,yet it poses notable challenges due to the intricate nature of its subsurface and near-surface conditions.To address these challenges,we introduce a novel and comprehensive workflow tailored to evaluate and optimize seismic acquisition geometries while considering the impacts of near-surface viscosity.By integrating geological knowledge,historical seismic data,and subsurface modeling,we conduct simulations employing the visco-acoustic wave equation and reverse-time migration to produce detailed subsurface images.The quality of these images is quantitatively evaluated using a local similarity metric,a pivotal tool for evaluating the accuracy of seismic imaging.The culmination of this workflow results in an automated optimization strategy for acquisition geometries that enhances subsurface exploration.Our proposed methodology underscores the importance of incorporating near-surface viscosity effects in seismic imaging,offering a robust framework for improving the accuracy of subsurface imaging.Herein,we aim to contribute to the advancement of seismic imaging methodologies by providing valuable insights for achieving high-quality seismic exploration outcomes in regions characterized by complex subsurface and near-surface conditions.