Migration images guided high-resolution velocity modeling based on fully convolutional neural network

Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.

Migration velocity modeling based on common reflection surface gather

The common-reflection-surface (CRS) stacking is a new seismic imaging method, which only depends on seismic three parameters and near-surface velocity instead of macro-velocity model. According to optimized three parameters obtained by CRS stacking, we derived an analytical relationship between three parameters and migration velocity field, and put forward CRS gather migration velocity modeling method, which realize velocity estimation by optimizing three parameters in CRS gather. The test of a sag model proved that this method is more effective and adaptable for velocity modeling of a complex geological body, and the accuracy of velocity analysis depends on the precision of optimized three parameters.

Structural similarity of lithospheric velocity models of Chinese mainland

Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.

Velocity and Structural Modeling of Mesozoic Chiltan Limestone and Goru Formation for Hydrocarbon Evaluation in the Bitrisim Area, Lower Indus Basin, Pakistan

The present study focuses on building a workflow for structural interpretation and velocity modeling and implementing to Jurassic-Cretaceous succession （Chiltan Limestone and Massive sand of the Lower Goru Formation）. 2D-Migrated seismic sections of the area are used as data set and in order to confirm the presence of hydrocarbons in the study area, P and S-wave seismic velocities are estimated from single-component seismic data. Some specific issues in the use of seismic data for modeling and hydrocarbon evaluation need to deal with including distinguishing the reservoir and cap rocks, and the effects of faults, folds and presence of hydrocarbons on these rocks. This study has carried out the structural interpretation and modeling of the seismic data for the identification of traps. The results demonstrate existence of appropriate structural traps in the form of horst and grabens in the area. 2D and 3D velocity modeling of the horizons indicates the presence of high velocity zones in the eastern half of the study while relatively low velocity zones are encountered in the western half of the area. Two wells were drilled in the study area （i.e. Fateh-01 and Ichhri-01） and both are dry. Immature hydrocarbons migration is considered as a failure reason for Fateh-01 and Ichhri-01 well.

Velocity Modeling and Inversion Techniques for Locating Microseismic Events in Unconventional Reservoirs

A velocity model is an important factor influencing microseismic event locations. We re- view the velocity modeling and inversion techniques for locating microseismic events in exploration for unconventional oil and gas reservoirs. We first describe the geological and geophysical characteristics of reservoir formations related to hydraulic fracturing in heterogeneity, anisotropy, and variability, then discuss the influences of velocity estimation, anisotropy model, and their time-lapse changes on the accuracy in determining microseismic event locations, and then survey some typical methods for building velocity models in locating event locations. We conclude that the three tangled physical attributes of reservoirs make microseismic monitoring very challenging. The uncertainties in velocity model and ignoring its anisotropies and its variations in hydraulic fracturing can cause systematic mislocations of microseismie events which are unacceptable in microseismic monitoring. So, we propose some potential ways for building accurate velocity models.

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.

FeatureMatching Combining Variable Velocity Model with Reverse Optical Flow

The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion,which leads to a false matching,with an inaccurate pose estimation or failed tracking.To address the challenge above,a new method of feature point matching is proposed in this paper,which combines the variable velocity model with the reverse optical flow method.First,the constant velocity model is extended to a new variable velocity model,and the expanded variable velocity model is used to provide the initial pixel shifting for the reverse optical flow method.Then the search range of feature points is accurately determined according to the results of the reverse optical flow method,thereby improving the accuracy and reliability of feature matching,with strengthened interframe tracking effects.Finally,we tested on TUM data set based on the RGB-D camera.Experimental results show that this method can reduce the probability of tracking failure and improve localization accuracy on SLAM(Simultaneous Localization and Mapping)systems.Compared with the traditional ORB-SLAM2,the test error of this method on each sequence in the TUM data set is significantly reduced,and the root mean square error is only 63.8%of the original system under the optimal condition.

Tomographic velocity inversion for ADCIGs in areas with a rugged surface

Pre-stack depth migration velocity analysis is one of the key techniques influencing image quality. As for areas with a rugged surface and complex subsurface, conventional prestack depth migration velocity analysis corrects the rugged surface to a known datum or designed surface velocity model on which to perform migration and update the velocity. We propose a rugged surface tomographic velocity inversion method based on angle-domain common image gathers by which the velocity field can be updated directly from the rugged surface without static correction for pre-stack data and improve inversion precision and efficiency. First, we introduce a method to acquire angle-domain common image gathers （ADCIGs） in rugged surface areas and then perform rugged surface tornographic velocity inversion. Tests with model and field data prove the method to be correct and effective.

Near-surface velocity model construction based on a Monte-Carlo scheme

In tomographic statics seismic data processing, it 1s crucial to cletermme an optimum base for a near-surface model. In this paper, we consider near-surface model base determination as a global optimum problem. Given information from uphole shooting and the first-arrival times from a surface seismic survey, we present a near-surface velocity model construction method based on a Monte-Carlo sampling scheme using a layered equivalent medium assumption. Compared with traditional least-squares first-arrival tomography, this scheme can delineate a clearer, weathering-layer base, resulting in a better implementation of damming correction. Examples using synthetic and field data are used to demonstrate the effectiveness of the proposed scheme.

Assessing the effects of model parameter assumptions on surface-wave inversion results

Surface-wave inversion is a powerful tool for revealing the Earth's internal structure.However,aside from shear-wave velocity(v_(S)),other parameters can influence the inversion outcomes,yet these have not been systematically discussed.This study investigates the influence of various parameter assumptions on the results of surface-wave inversion,including the compressional and shear velocity ratio(v_(P)/v_(S)),shear-wave attenuation(Q_(S)),density(ρ),Moho interface,and sedimentary layer.We constructed synthetic models to generate dispersion data and compared the obtained results with different parameter assumptions with those of the true model.The results indicate that the v_(P)/v_(S) ratio,Q_(S),and density(ρ) have minimal effects on absolute velocity values and perturbation patterns in the inversion.Conversely,assumptions about the Moho interface and sedimentary layer significantly influenced absolute velocity values and perturbation patterns.Introducing an erroneous Mohointerface depth in the initial model of the inversion significantly affected the v_(S) model near that depth,while using a smooth initial model results in relatively minor deviations.The assumption on the sedimentary layer not only affects shallow structure results but also impacts the result at greater depths.Non-linear inversion methods outperform linear inversion methods,particularly for the assumptions of the Moho interface and sedimentary layer.Joint inversion with other data types,such as receiver functions or Rayleigh wave ellipticity,and using data from a broader period range or higher-mode surface waves,can mitigate these deviations.Furthermore,incorporating more accurate prior information can improve inversion results.

Velocity model and time-depth conversion for the northwestern South China Sea deepwater areas

There are rich natural gas resources in the northwestern South China Sea deepwater areas, with poor degree of exploration. Because of the unique tectonic, sedimentary background of the region, velocity model building and time-depth conversion have been an important and difficult problem for a long time. Recent researches in this direction have revealed three major problems for deepwater areas, i.e., the way to determine error correction for drilling velocity, the optimization of velocity modeling, and the understanding and analysis of velocity variations in the slope areas. The present contribution proposes technical solutions to the problems：（1） velocity correction version can be established by analyzing the geology, reservoir, water depths and velocity spectrum characteristics;（2） a unified method can be adopted to analyze the velocity variation patterns in drilled pale structural positions;and （3） across-layer velocity is analyzed to establish the velocity model individually for each of the layers. Such a solution is applicable, as shown in an example from the northwestern South China Sea deepwater areas, in which an improved prediction precision is obtained.

An improved multidirectional velocity model for micro-seismic monitoring in rock engineering

An improved multidirectional velocity model was proposed for more accurately locating micro-seismic events in rock engineering. It was assumed that the stress wave propagation velocities from a micro-seismic source to three nearest monitoring sensors in a sensor's array arrangement were the same. Since the defined objective function does not require pre-measurement of the stress wave propagation velocity in the field, errors from the velocity measurement can be avoided in comparison to three traditional velocity models. By analyzing 24 different cases, the proposed multidirectional velocity model iterated by the Simplex method is found to be the best option no matter the source is within the region of the sensor's array or not. The proposed model and the adopted iterative algorithm are verified by field data and it is concluded that it can significantly reduce the error of the estimated source location.

Improvements in seismic event locations in a deep western U.S. coal mine using tomographic velocity models and an evolutionary search algorithm

Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations.

Effect of Relative Velocity on the Optimal Velocity Model

In this letter, an improved optimal velocity model was proposed that assumes the effect of relative velocity deceases with the increment of gap between successive cars. Numerical simuation was carried out to test whether this model could depict the braking process correctly. The simuation results show good agreement with observed data.

Effect of multi-velocity-difference in traffic flow

Based on the optimal velocity models, an extended model is proposed, in which multi-veloclty-dllterence aheacl is taken into consideration. The damping effect of the multi-velocity-difference ahead has been investigated by means of analytical and numerical methods. Results indicate that the multi-velocity-difference leads to the enhancement of stability of traffic flow, suppression of the emergence of traffic jamming, and reduction of the energy consumption.

A model for predicting bubble rise velocity in a pulsed gas solid fluidized bed

Bed stability, and especially the bed density distribution, is affected by the behavior of bubbles in a gas solid fluidized bed. Bubble rise velocity in a pulsed gas-solid fluidized bed was studied using photographic and computational fluid dynamics methods. The variation in bubble rise velocity was investigated as a function of the periodic pulsed air flow. A predictive model of bubble rise velocity was derived: ub=ψ(Ut+Up-Umf)+kp(gdb)(1/2). The software of Origin was used to fit the empirical coefficients to give ψ = 0.4807 and kp = 0.1305. Experimental verification of the simulations shows that the regular change in bubble rise velocity is accurately described by the model. The correlation coefficient was 0.9905 for the simulations and 0.9706 for the experiments.

A multi-scale 3-D crust velocity model in the Hefei-Chao Lake area around the southern segment of Tanlu Fault Zone

Regional high-precision velocity models of the crust are an important foundation for examining seismic activity,seismogenic environments,and disaster distribution characteristics.The Hefei-Chao Lake area contains the main geological units of Hefei Basin,with thick sediments and the Chao Lake depression.Several major concealed faults of the southern NNE-trending Tanlu Fault Zone cross this area.To further explore the underground distribution characteristics of the faults and their tectonic evolutionary relationship with adjacent tectonic units,this study used ambient noise data recorded by a seismic array deployed in Hefei City and Chao Lake,constructing a 3-D velocity model at the depth of 1–8 km.Then a multi-scale high-resolution 3-D velocity model of this area was constructed by this new upper crustal velocity model with the previous middle and lower crustal model.The new model reveals that a high-velocity belt is highly consistent with the strike of the Tanlu Fault Zone,and a low-velocity sedimentary characteristic is consistent with the Hefei Basin and Chao Lake depression.The distribution morphology of high and low velocity bodies shows that the sedimentary pattern of Hefei-Chao Lake area is closely related to the tectonic evolution of the Tanlu Fault Zone since the Mesozoic.This study also identifies multiple low-velocity anomalies in the southeastern Hefei City.We speculate that strong ground motion during the 2009 Feidong earthquake(magnitude of 3.5)was related to amplification by the thick sediments in the Hefei Basin.We also discuss further applications of multi-scale high-resolution models of the shallow layer to strong ground motion simulations in cities and for earthquake disaster assessments.

Velocity anticipation in the optimal velocity model

In this paper, the velocity anticipation in the optimal velocity model （OVM） is investigated. The driver adjusts the velocity of his vehicle by the desired headway, which depends on both instantaneous headway and relative velocity. The effect of relative velocity is measured by a sensitivity function. A specific form of the sensitivity function is supposed and the involved parameters are determined by the both numerical simulation and empirical data. It is shown that inclusion of velocity anticipation enhances the stability of traffic flow. Numerical simulations show a good agreement with empirical data. This model provides a better description of real traffic, including the acceleration process from standing states and the deceleration process approaching a stopped car.

Gas-kinetic numerical method for solving mesoscopic velocity distribution function equation

A gas-kinetic numerical method for directly solving the mesoscopic velocity distribution function equation is presented and applied to the study of three-dimensional complex flows and micro-channel flows covering various flow regimes. The unified velocity distribution function equation describing gas transport phenomena from rarefied transition to continuum flow regimes can be presented on the basis of the kinetic Boltzmann-Shakhov model equation. The gas-kinetic finite-difference schemes for the velocity distribution function are constructed by developing a discrete velocity ordinate method of gas kinetic theory and an unsteady time-splitting technique from computational fluid dynamics. Gas-kinetic boundary conditions and numerical modeling can be established by directly manipulating on the mesoscopic velocity distribution function. A new Gauss-type discrete velocity numerical integra- tion method can be developed and adopted to attack complex flows with different Mach numbers. HPF paral- lel strategy suitable for the gas-kinetic numerical method is investigated and adopted to solve three-dimensional complex problems. High Mach number flows around three-dimensional bodies are computed preliminarilywith massive scale parallel. It is noteworthy and of practical importance that the HPF parallel algorithm for solving three-dimensional complex problems can be effectively developed to cover various flow regimes. On the other hand, the gas-kinetic numerical method is extended and used to study micro-channel gas flows including the classical Couette flow, the Poiseuillechannel flow and pressure-driven gas flows in twodimensional short micro-channels. The numerical experience shows that the gas-kinetic algorithm may be a powerful tool in the numerical simulation of microscale gas flows occuring in the Micro-Electro-Mechanical System （MEMS）.

Detailed string stability analysis for bi-directional optimal velocity model

The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.