Shear wave velocity prediction:A review of recent progress and future opportunities

Shear logs,also known as shear velocity logs,are used for various types of seismic analysis,such as determining the relationship between amplitude variation with offset(AVO)and interpreting multiple types of seismic data.This log is an important tool for analyzing the properties of rocks and interpreting seismic data to identify potential areas of oil and gas reserves.However,these logs are often not collected due to cost constraints or poor borehole conditions possibly leading to poor data quality,though there are various approaches in practice for estimating shear wave velocity.In this study,a detailed review of the recent advances in the various techniques used to measure shear wave(S-wave)velocity is carried out.These techniques include direct and indirect measurement,determination of empirical relationships between S-wave velocity and other parameters,machine learning,and rock physics models.Therefore,this study creates a collection of employed techniques,enhancing the existing knowledge of this significant topic and offering a progressive approach for practical implementation in the field.

Joint inversion of Rayleigh group and phase velocities for S-wave velocity structure of the 2021 M_(S)6.0 Luxian earthquake source area,China

On September 16,2021,a MS6.0 earthquake struck Luxian County,one of the shale gas blocks in the Southeastern Sichuan Basin,China.To understand the seismogenic environment and its mechanism,we inverted a fine three-dimensional S-wave velocity model from ambient noise tomography using data from a newly deployed dense seismic array around the epicenter,by extracting and jointly inverting the Rayleigh phase and group velocities in the period of 1.6–7.2 s.The results showed that the velocity model varied significantly beneath different geological units.The Yujiasi syncline is characterized by low velocity at depths of~3.0–4.0 km,corresponding to the stable sedimentary layer in the Sichuan Basin.The eastern and western branches of the Huayingshan fault belt generally exhibit high velocities in the NE-SW direction,with a few local low-velocity zones.The Luxian MS6.0 earthquake epicenter is located at the boundary between the high-and low-velocity zones,and the earthquake sequences expand eastward from the epicenter at depths of 3.0–5.0 km.Integrated with the velocity variations around the epicenter,distribution of aftershock sequences,and focal mechanism solution,it is speculated that the seismogenic mechanism of the main shock might be interpreted as the reactivation of pre-existing faults by hydraulic fracturing.

3D S-wave velocity structure of the Ningdu basin in Jiangxi province inferred from ambient noise tomography with dense array

The Ningdu basin,located in southern Jiangxi province of southwest China,is one of the Mesozoic basin groups which has exploration prospects for geothermal energy.A study on the detailed velocity structure of the Ningdu basin can provide important information for geothermal resource exploration.In this study,we deployed a dense seismic array in the Ningdu basin to investigate the 3D velocity structure and discuss implications for geothermal exploration and geological evolution.Based on the dense seismic array including 35 short-period(5 s-100 Hz)seismometers with an average interstation distance of~5 km,Rayleigh surface wave dispersion curves were extracted from the continuous ambient noise data for surface wave tomographic inversion.Group velocity tomography was conducted and the 3D S-wave velocity structure was inverted by the neighborhood algorithm.The results revealed obvious low-velocity anomalies in the center of the basin,consistent with the low-velocity Cretaceous sedimentary rocks.The basement and basin-controlling fault can also be depicted by the S-wave velocity anomalies.The obvious seismic interface is about 2 km depth in the basin center and decreases to 700 m depth near the basin boundary,suggesting spatial thickness variations of the Cretaceous sediment.The fault features of the S-wave velocity profile coincide with the geological cognition of the western boundary basincontrolling fault,which may provide possible upwelling channels for geothermal fluid.This study suggests that seismic tomography with a dense array is an effective method and can play an important role in the detailed investigations of sedimentary basins.

Rock critical porosity inversion and S-wave velocity prediction

A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.

The bound weighted average method(BWAM)for predicting S-wave velocity

The shear-wave velocity is a very important parameter in oil and gas seismic exploration, and vital in prestack elastic-parameters inversion and seismic attribute analysis. However, sheafing-velocity logging is seldom carried out because it is expensive. This paper presents a simple method for predicting S-wave velocity which covers the basic factors that influence seismic wave propagation velocity in rocks. The elastic modulus of a rock is expressed here as a weighted arithmetic average between Voigt and Reuss bounds, where the weighting factor, w, is a measurement of the geometric details of the pore space and mineral grains. The S-wave velocity can be estimated from w, which is derived from the P-wave modulus. The method is applied to process well-logging data for a carbonate reservoir in Sichuan Basin, and shows the predicted S-wave velocities agree well with the measured S-wave velocities.

Estimation of Shallow S-Wave Velocity Structure of Two Practical Sites from Microtremors Array Observation in Tangshan Area

Microtremors array observation for estimating S-wave velocity structure from phase velocities of Rayleigh and Love wave on two practical sites in Tangshan area by a China-US joint group are researched.The phase velocities of Rayleigh wave are estimated from vertical component records and those of Love wave are estimated from three-component records of microtremors array using modified spatial auto-correlation method.Haskell matrix method is used in calculating Rayleigh and Love wave phase velocities,and the shallow S-wave velocity structure of two practical sites are estimated by means of a hybrid approach of Genetic Algorithm and Simplex.The results are compared with the PS logging data of the two sites,showing it is feasible to estimate the shallow S-wave velocity structure of practical site from the observation of microtremor array.

Estimation of S-wave Velocity for Gas Hydrate Reservoir in the Shenhu Area,North South China Sea

Estimation of S-wave velocity using logging data has mainly been performed for sandstone, mudstone and oil and gas strata, while its application to hydrate reservoirs has been largely overlooked. In this paper we present petxophysical methods to estimate the S-wave velocity of hydrate reservoirs with the P-wave velocity and the density as constraints. The three models used in this paper are an equivalent model （MBGL）, a three-phase model （TPBE）, and a thermo-elasticity model （TEM）. The MBGL model can effectively describe the internal relationship among the components of the rock, and the estimated P-wave velocities are in good agreement with the measured data （2.8% error）. However, in the TPBE model, the solid, liquid and gas phases axe considered to be independent of each other, and the estimation results are relatively low （46.6% error）. The TEM model is based on the sensitivity of the gas hydrate to temperature and pressure, and the accuracy of the estimation results is also high （3.6% error）. Before the estimation, the occurrence patterns of hydrates in the Shenhu area were examined, and occurrence state one （the hydrate is in solid form in the reservoir） was selected for analysis. By using the known P-wave velocity and density as constraints, a reasonable S-wave velocity value （ranging from 400 to 1100 m s 1 and for a hydrate layer of 1100 m s 1） can be obtained through multiple iterations. These methods and results provide new data and technical support for further research on hydrates and other geological features in the Shenhu area.

Mapping crustal S-wave velocity structure with SV-component receiver function method

In this article, we analyze the characters of SV-component receiver function of teleseismic body waves and its advantages in mapping the S-wave velocity structure of crust in detail. Similar to radial receiver function, SV-component receiver function can be obtained by directly deconvolving the P-component from the SV-component of teleseismic recordings. Our analyses indicate that the change of amplitude of SV-component receiver function against the change of epicentral distance is less than that of radial receiver function. Moreover, the waveform of SV-component receiver function is simpler than the radial receiver function and gives prominence to the PS converted phases that are the most sensitive to the shear wave velocity structure in the inversion. The synthetic tests show that the convergence of SV-component receiver function inversion is faster than that of the radial receiver function inversion. As an example, we investigate the S-wave velocity structure beneath HIA sta-tion by using the SV-component receiver function inversion method.

Double-difference tomography of P- and S-wave velocity structure beneath the western part of Java, Indonesia

West Java in the western part of the Sunda Arc has a relatively high seismicity due to subduction activity and faults.In this study,double-difference tomography was used to obtain the 3D velocity tomograms of P and S waves beneath the western part of Java.To infer the geometry of the structure beneath the study area,precise earthquake hypo・center determination was first performed before tomographic imaging.For this,earthquake waveform data were extracted from the regional Meteorological,Climatological,Geophysical Agency(BMKG)network of Indonesia from South Sumatra to Central Java.The P and S arrival times for about 1,000 events in the period April 2009 to July 2016 were selected,the key features being events of magnitude>3,azimuthal gap<210°and number of phases>8.A nonlinear method using the oct-tree sampling algorithm from the NonLinLoc program was employed to determine the earthquake hypocenters.The hypocenter locations were then relocated using double-difference tomography(tomoDD).A significant reduction of travel-time(root mean square basis)and a better clustering of earthquakes were achieved which correlated well with the geological structure in West Java.Double-difference tomography was found to give a clear velocity structure,especially beneath the volcanic arc area,i.e.,under Mt Anak Krakatau,Mt Salak and the mountains complex in the southern part of West Java.Low velocity anomalies for the P and S waves as well as the vp/vs ratio below the volcanoes indicated possible partial melting of the upper mantle which ascended from the subducted slab beneath the volcanic arc.

S-wave velocity structure in Tangshan earthquake region and its adjacent areas from joint inversion of receiver functions and surface wave dispersion

Using the seismic records of 83 temporary and 17 permanent broadband seismic stations deployed in Tangshan earthquake region and its adjacent areas(39°N–41.5°N,115.5°E–119.5°E),we conducted a nonlinear joint inversion of receiver functions and surface wave dispersion.We obtained some detailed information about the Tangshan earthquake region and its adjacent areas,including sedimentary thickness,Moho depth,and crustal and upper mantle S-wave velocity.Meanwhile,we also obtained the vP/vS structure along two sections across the Tangshan region.The results show that:(1)the Moho depth ranges from 30 km to 38 km,and it becomes shallower from Yanshan uplift area to North China basin;(2)the thickness of sedimentary layer ranges from 0 km to 3 km,and it thickens from Yanshan uplift region to North China basin;(3)the S-wave velocity structure shows that the velocity distribution of the upper crust has obvious correlation with the surface geological structure,while the velocity characteristics of the middle and lower crust are opposite to that of the upper crust.Compared with the upper crust,the heterogeneity of the middle and lower crust is more obvious;(4)the discontinuity of Moho on the two sides of Tangshan fault suggests that Tangshan fault cut the whole crust,and the low vS and high vP/vS beneath the Tangshan earthquake region may reflect the invasion of mantle thermal material through Tangshan fault.

The shallow Longmenshan crustal S-velocity structure of the fault zone using ambient noise tomography of a seismic dense array

The Longmenshan fault zone(LMSF),characterized by complex structures and strong seismicity,is located at the junction between the eastern margin of the Tibetan Plateau and the north-western Sichuan basin.Since the Wenchuan earthquake on May 12,2008,abundant studies of the formation mechanism of earthquakes along the LMSF were performed.In this study,a short-period dense seismic array deployed across the LMSF was applied by ambient noise tomography.Fifty-two 3-D seismic instruments were used for data acquisition for 26 days.We calculated the empirical Green's functions(EGFs)between different station-pairs and extracted 776 Rayleigh-wave dispersion curves between 2 and 7 s.And then,we used the direct-inversion method to obtain the fine shallow crustal S-wave velocity structure within 6 km depth in the middle section of the Longmenshan fault zone and nearby areas.Our results show that the sedimentary layer(>5 km)exists in the northwest margin of Sichuan Basin with a low S-wave velocity(~1.5-2.5 km/s)which is much thicker than that beneath the Longmenshan fault zone and the Songpan-Garze block.The high-velocity structures with clear boundaries below the middle of Longmenshan fault zone(~2-4 km)and the Songpan-Garze block(~4.5-6 km)probably reveal the NW-SE distribution patterns of both the Pengguan complex and the high-density belt hidden in the northwest of the Pengguan complex.And the obviously high-velocity anomalies observed at the depth of^1-2 km in the southeastern margin of the Songpan-Garze block can be considered as the Laojungou granites.Our results provide a high-resolution shallow velocity structure for detailed studies of the Longmenshan fault zone.

Tomographic inversion of OBS converted shear waves:case study of profile EW6 in the Dongsha area

Studies of converted S-wave data recorded on the ocean bottom seismometer(OBS)allow for the estimation of crustal S-wave velocity,from which is further derived the Vp/Vs ratio to constrain the crustal lithology and geophysical properties.Constructing a precise S-wave velocity model is important for deep structural research,and inversion of converted S-waves provides a potential solution.However,the inversion of the converted S-wave remains a weakness because of the complexity of the seismic ray path and the inconsistent conversion interface.In this study,we introduced two travel time correction methods for the S-wave velocity inversion and imaged different S-wave velocity structures in accordance with the corresponding corrected S-wave phases using seismic data of profile EW6 in the northeastern South China Sea(SCS).The two inversion models show a similar trend in velocities,and the velocity difference is<0.15 km/s(mostly in the range of 0–0.1 km/s),indicating the accuracy of the two travel time correction methods and the reliability of the inversion results.According to simulations of seismic ray tracing based on different models,the velocity of sediments is the primary influencing factor in ray tracing for S-wave phases.If the sedimentary layer has high velocities,the near offset crustal S-wave refractions cannot be traced.In contrast,the ray tracing of Moho S-wave reflections was not significantly impacted by the velocity of the sediments.The two travel time correction methods have their own advantages,and the application of different approaches is based on additional requirements.These works provide an important reference for future improvements in converted S-wave research.

Seismogenic model of the 2023 M_(W)5.5 Pingyuan earthquake in North China Plain and its tectonic implications

The 6 August 2023 M_(W)5.5 Pingyuan earthquake is the largest earthquake in the central North China Plain(NCP)over the past two decades.Due to the thick sedimentary cover,no corresponding active faults have been reported yet in the epicenter area.Thus,this earthquake presents a unique opportunity to delve into the buried active faults beneath the NCP.By integrating strong ground motion records,high-precision aftershock sequence relocation,and focal mechanism solutions,we gain insights into the seismotectonics of the Pingyuan earthquake.The aftershocks are clustered at depths ranging from 15 to 20 km and delineate a NE-SW trend,consistent with the distribution of ground motion records.A NE-SW nodal plane(226°)of the focal mechanism solutions is also derived from regional waveform inversion,suggesting that the mainshock was dominated by strike-slip motion with minor normal faulting component.Integrating regional geological data,we propose that an unrecognized fault between the NE-SW trending Gaotang and Lingxian-Yangxin faults is the seismogenic fault of this event.Based on the S-wave velocity structure beneath the NCP,this fault probably extends into the lower crust with a high angle.Considering the tectonic regime and stress state,we speculate that the interplay of shear strain between the Amurian and South China blocks and the hot upwelling magma from the subducted paleo Pacific flat slab significantly contributed to the generation of the Pingyuan earthquake.

Interpretation of S-Wave Data from Fanshi-Taipusiqi DSS Profile and Analysis of Correlation between Deep Structural Characteristics and Seismicity

By processing S-wave data from the Fanshi-Huai’an-Taipusiqi DSS profile,which is a three-component,wide-angle reflection/refraction profile,and in the light of the results from P-wave interpretation,two-dimensional(2-D)structures of the crust and upper mantle are presented,including S-wave velocity Vs and the physical parameter of medium-Poisson’s ratio a.Taking other geological and geophysical information into account,and with reference to the results from petrophysical experiments at home and abroad,we carried out interpretation and inference with respect to deep crustal structure,tectonics,and lithologic characters.It has been concluded that in the upper and middle crust,a values are mostly not greater than 0.25,and rocks,which generally assume brittle,are mainly composed of granite; the rocks in the lower layer of the upper crust between Yangyuan-Huai’an containing inorganic CO2 itself releases carbon; for the rocks in the lower crust and crust-mantle transitional zone,which are comparatively

S-wave velocity and Poisson's ratio structure of crust in Yunnan and its implication

Receiver function of body wave under the 23 stations in Yunnan was extracted from 3-component broadband digital recording of teleseismic event. Thus, the S-wave velocity structure and distribution characteristics of Poisson's ratio in crust of Yunnan are obtained by inversion. The results show that the crustal thickness is gradually thinned from north to south. The crustal thickness in Zhongdian of northwest reaches as many as 62.0 km and the one in Jinghong of further south end is only 30.2 km. What should be especially noted is that there exists a Moho upheaval running in NS in the Chuxiong region and a Moho concave is generally parallel to it in Dongchuan. In addition, there exists an obvious transversal inhomogeneity for the S-wave velocity structure in upper mantle and crust in the Yunnan region. The low velocity layer exists not only in 10.0-15.0 km in upper crust in some regions, but also in 30.0-40.0 km in lower crust. Generally, the Poisson's ratio is on the high side, however it has a better corresponding relation to the crustal velocity structure. An obvious block distribution feature is still shown on such a high background of Poisson's ratio. It is discovered by synthetically analyzing the velocity structure and Poisson's ratio distribution that there are high Poisson's ratio and complicated crust-mantle velocity structure feature in the Sichuan-Yunnan Diamond Block with Xiaojiang fault to be the east boundary and Yulong Snow Mountain fault to be the west boundary besides the frequent seismicity. This feature differs obviously from that of surrounding areas, which would provide geophysical evidence to deeply study the eastwardly flowage of lithospheric substances in the Qinghai-Tibet Plateau.

3D S-Wave Velocity Structure of the Crust and Upper Mantle

In this paper, 238 Rayleigh wave path data are selected and processed by the matched-filtering frequency-time analysis technique and the grid dispersion inversion method to obtain the 3D S-wave velocity structure of China mainland and its adjacent sea regions. The results show that the velocity structure relates to geotectonic division, Bouguer gravity anomaly is basically controlled by the relief of Moho discontinuity, the buried depth of LVL in upper mantle concerns the surface heat flow deeply. In this paper, authors indicate the main characteristics of the velocity structure in tectonic active and stable regions.

Determination of the crustal structure and seismicity of the Linfen rift with S-wave velocity mapping

The Linfen rift is a Cenozoic extensional rift with significant seismicity and seismic hazards.Studies of this rift shed light on deep dynamic processes and seismogenic mechanisms relevant to crustal structure and seismic activity.We first conducted a joint inversion of receiver functions and surface wave dispersion on waveform data collected from 27 broadband seismic stations to image the crustal S-wave velocity in the Linfen rift and its surroundings.We then relocated the source parameters for 10 earthquake events with depths>20 km and studied the relationship between crustal S-wave velocity and seismicity.The results show that low-velocity zones of different scales exist in the middle-lower crust,and that the depth of the seismogenic layer gradually increases from^25 km in the south to^34 km in the north,roughly corresponding to the bottom of the low-velocity zone.We found that most of the relocated earthquakes occurred in the low-velocity zone at depths of 18 km to 34 km,with the deepest at 32 km.Two of the greatest historic earthquakes,Linfen(Ms 7.75)in 1695 and Hongtong(Ms 8.0)in 1303,occurred at the bottom of the high-velocity zone at depths of 12 km to 18 km.Our results,combined with previous studies,suggest that the upwelling mantle material below the rift did not remarkably affect the velocity structure from the bottom of the seismogenic layer down to the uppermost mantle nor heat the crust.It is likely that neither crustal-scale faults nor mantle earthquakes exist in the Linfen rift.

S-wave velocity inversion and prediction using a deep hybrid neural network

The S-wave velocity is a critical petrophysical parameter in reservoir description,prestack seismic inversion,and geomechanical analysis.However,obtaining the S-wave velocity from field measurements is difficult.When no measured Swave data are available,petrophysical modelling provides the most accurate S-wave velocity prediction.However,because of the complexity of underground geological structures and diversity of rock minerals,the prediction results of petrophysical modelling are easily affected by factors such as the cognition and experience of the modeller.Therefore,the development of novel robust and simple S-wave velocity inversion and prediction methods independent of the modeller is critical.Inspired by ensemble learning and based on the geologic sedimentation law of reservoirs and their characteristics in logging response,an Swave velocity inversion and prediction method based on deep hybrid neural network was developed by combining the classical convolution neural network(CNN)with the long short-term memory(LSTM)network.Considering the conventional logging data such as acoustic and density as the input in the proposed method,the CNN was used to establish the nonlinear mapping relationship between the input data and S-wave velocity,and the LSTM network was used to integrate the vertical variation trend of the stratum.Thus,intelligent data-driven inversion and prediction of the S-wave velocity were realised.The experimental results revealed that the proposed method exhibited a strong generalisation ability and could obtain prediction results comparable to those of petrophysical modelling with a single-well data set for training.Thus,a novel methodology for robust and convenient S-wave velocity prediction was devised.The proposed method has considerable academic and application implications.

Shear wave velocity structure of the crust and upper mantle underneath the Tianshan orogenic belt

From April, 2003 to September, 2004, a passive broadband seismic array consisting of 60 stations was deployed over the Tianshan orogenic belt by State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration. Among them, 51 stations make up an about 500-km-long profile across the Tianshan Mountains from Kuytun to Kuqa. The receiver function profile and S-wave velocity structure of the crust and upper mantle down to 100 km deep are obtained by using the re-ceiver function method (Liu et al. 1996, 2000). The main results can be summarized as follows: (1) A clear mountain root does not exist beneath the Tianshan Mountains, and the crust-mantle boundaries underneath the stations mostly have transitional structures. This implies that the material differentia-tion between the crust and mantle is not yet accomplished and the orogenic process is still going on. (2) The crust beneath the Tianshan Mountains has laterally blocked structures in direction perpendicular to the mountain strike, and the crust-mantle boundary has a clear dislocation structure. Both of them correspond to each other. (3) The offsets of the Moho discontinuity are highly correlated to the tectonic borders on the surface and that corresponding to the frontal southern Tianshan fault reaches to 14 km. This manifests that large vertical divergent movement took place between different blocks. This sup-ports the discontinuous model of the Tianshan orogeny, and the Tarim block subduction is restricted only to the southern side of the South Tianshan. (4) Inside the upper and middle crust of the Tianshan Mountains exist several low-velocity bodies correlated with high seismicity located on the moun-tain-basin jointures on both sides of the mountain and between different blocks, and the low-velocity bodies on the mountain-basin jointures are inclined obviously to the mountain. This implies that the low-velocity bodies may be correlated closely to the thrust and subduction of the basins on both sides of the mountain, the splicing of adjacent blocks and the fast uplift of the Tianshan Mountains.

A new method to constrain shallow crustal S-wave velocities based on direct P-wave amplitudes in receiver functions and its application in northeastern Tibet

A new method is developed to constrain S-wave velocity structures of the shallow crust based on frequencydependent amplitudes of direct P-waves in P-wave receiver functions(P-RFs). This method involves the following two steps:first, the high-frequency approximate amplitude formula of direct P-waves in P-RFs of individual stations is used to fit the observed amplitude distribution against the ray parameters at different frequencies, and second, the S-wave velocity depth profile beneath each station is constrained according to an empirical correlation between frequency and depth. Unlike traditional inversion techniques, the newly developed method is not dependent on initial velocity models, and the lateral and vertical resolutions of the results are controlled by the interstation distance and the data frequency, respectively. The effectiveness of the method is verified by synthetic tests on various models. The method is then applied to teleseismic P-RF data from a NW-SEtrending linear seismic array extending from the northeastern Tibetan Plateau to the central Sichuan Basin to construct an S-wave velocity image of the shallow crust along the array. The imaged velocity structure is further analysed and compared with the regional geology. In particular, the structural differences of sedimentary basins in the cratonic area of the stable Sichuan Basin and tectonically active belts in northeastern Tibet are investigated. By combining our results with previous observations, the relationship between the surficial geology and deep processes in the study region is also discussed.