The Karatau fault is one of the important strike-slip faults in central Asia,and the South Turgay Basin is located towards its northern end.Detailed seismic interpretation indicated that the strikeslip tectonism of th...The Karatau fault is one of the important strike-slip faults in central Asia,and the South Turgay Basin is located towards its northern end.Detailed seismic interpretation indicated that the strikeslip tectonism of the Karatau fault weakened gradually from west to east in the South Turgay Basin.Typical flower structures developed on the section,and strike-slip faults showed an echelon pattern on planar view.The Karatau strike-slip fault affected the South Turgay Basin in two periods：（1） The South Turgay strike-slip pull-apart rift basin formed as a result of regional extensive stress in the Early-Middle Jurassic,characterized by the juxtaposition of horsts and grabens.The formation of horsts provided favorable reservoir spaces for later hydrocarbon accumulation,and different filling stages of grabens controlled different reservoir-forming factors in grabens.（2） Two stages of tectonic inversion occurred in the Late Jurassic and Late Cretaceous and played a crucial role in the final shape of the structure in the South Turgay Basin.The oil and gas migrated to form reservoirs and mainly concentrated in the horsts,graben slopes and in both sides of the strike-slip fault zone.In the case of the degree of accumulation of petroleum,the factor explaining why horsts are better than grabens is the strike-slip pull-apart of the South Turgay Basin,and the structure inversion of the South Turgay Basin explains why the west graben is better than the east one.Overall,the Karatau strike-slip fault played a very important role in the formation of the South Turgay Basin and its hydrocarbon accumulations.展开更多
Full waveform inversion methods evaluate the properties of subsurface media by minimizing the misfit between synthetic and observed data.However,these methods omit measurement errors and physical assumptions in modeli...Full waveform inversion methods evaluate the properties of subsurface media by minimizing the misfit between synthetic and observed data.However,these methods omit measurement errors and physical assumptions in modeling,resulting in several problems in practical applications.In particular,full waveform inversion methods are very sensitive to erroneous observations(outliers)that violate the Gauss–Markov theorem.Herein,we propose a method for addressing spurious observations or outliers.Specifically,we remove outliers by inverting the synthetic data using the local convexity of the Gaussian distribution.To achieve this,we apply a waveform-like noise model based on a specific covariance matrix definition.Finally,we build an inversion problem based on the updated data,which is consistent with the wavefield reconstruction inversion method.Overall,we report an alternative optimization inversion problem for data containing outliers.The proposed method is robust because it uses uncertainties.This method enables accurate inversion,even when based on noisy models or a wrong wavelet.展开更多
Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
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 sy...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.展开更多
Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation ...Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.展开更多
BACKGROUND In laparoscopic proximal gastrectomy(LPG),the prolapse of the hepatic left lateral lobe near the lesser curvature and esophageal hiatus can obstruct the field of vision and operation.Therefore,it is necessa...BACKGROUND In laparoscopic proximal gastrectomy(LPG),the prolapse of the hepatic left lateral lobe near the lesser curvature and esophageal hiatus can obstruct the field of vision and operation.Therefore,it is necessary to retract or obstruct the hepatic left lateral lobe to ensure a clear field of vision.AIM To investigate the safety and clinical efficacy of the modified hepatic left lateral lobe inversion technique for LPG.METHODS A retrospective analysis was conducted on the clinical data of 13 consecutive patients with early-stage upper gastric adenocarcinoma or adenocarcinoma of the esophagogastric junction treated with LPG from January to December 2023 at the Department of Gastrointestinal Surgery,Second Affiliated Hospital of Fujian Medical University.The modified hepatic left lateral lobe inversion technique was used to expose the surgical field in all patients,and short-term outcomes were observed.RESULTS In all 13 patients,the modified hepatic left lateral lobe inversion technique was successful during surgery without the need for re-retraction or alteration of the liver traction method.There were no instances of esophageal hiatus occlusion,eliminating the need for forceps to assist in exposure.There was no occurrence of intraoperative hepatic hemorrhage,hepatic vein injury,or hepatic congestion.No postoperative digestive complications of Clavien-Dindo grade≥II occurred wi-thin 30 days after surgery,except for a single case of pulmonary infection.Some patients experienced increases in alanine aminotransferase and aspartate aminotransferase levels on the first day after surgery,which significantly decreased by the third day and returned to normal by the seventh day after surgery.CONCLUSION The modified hepatic left lateral lobe inversion technique has demonstrated satisfactory results,offering ad-vantages in terms of facilitating surgical procedures,reducing surgical trauma,and protecting the liver.展开更多
Hall effects have been the central paradigms in modern physics,materials science and practical applications,and have led to many exciting breakthroughs,including the discovery of topological Chern invariants and the r...Hall effects have been the central paradigms in modern physics,materials science and practical applications,and have led to many exciting breakthroughs,including the discovery of topological Chern invariants and the revolution of metrological resistance standard.To date,the Hall effects have mainly focused on a single degree of freedom(Do F),and most of them require the breaking of spatial-inversion and/or time-reversal symmetries.Here we demonstrate a new type of Hall effect,i.e.,layer-valley Hall effect,based on a combined layer-valley Do F characterized by the product of layer and valley indices.The layer-valley Hall effect has a quantum origin arising from the layer-valley contrasting Berry curvature,and can occur in nonmagnetic centrosymmetric crystals with both spatial-inversion and time-reversal symmetries,transcending the symmetry constraints of single Do F Hall effect based on the constituent layer or valley index.Moreover,the layer-valley Hall effect is highly tunable and shows a W-shaped pattern in response to the out-of-plane electric fields.Additionally,we discuss the potential detection approaches and material-specific design principles of layer-valley Hall effect.Our results demonstrate novel Hall physics and open up exotic paradigms for new research direction of layer-valleytronics that exploits the quantum nature of the coupled layer-valley DoF.展开更多
Having been a seemingly unreachable ideal for decades,3-D full-waveform inversion applied to massive seismic datasets has become reality in recent years.Often achieving unprecedented resolution,it has provided new ins...Having been a seemingly unreachable ideal for decades,3-D full-waveform inversion applied to massive seismic datasets has become reality in recent years.Often achieving unprecedented resolution,it has provided new insight into the structure of the Earth,from the upper few metres of soil to the entire globe.Motivated by these successes,the technology is now being translated to medical ultrasound and non-destructive testing.Despite remarkable progress,the computational cost of fullwaveform inversion continues to be a major concern.It limits the amount of data that can be exploited,and it largely inhibits quantitative and comprehensive uncertainty analyses.These notes complement a presentation on recent developments in full-waveform inversion that are intended to reduce computational cost and assimilate more data,thereby improving tomographic resolution.The suite of strategies includes flexible and user-friendly spectral-element simulations,the design of wavefieldadapted meshes that harness prior information on wavefield geometry,dynamic mini-batch optimisation that naturally takes advantage of data redundancies,and collaborative multi-scale updating to jointly constrain crustal and mantle structure.展开更多
Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuit...Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuities.More specifically,seismic migration estimates the reflectivity function(stacked average reflectivity or pre-stack angle-dependent reflectivity)from seismic reflection data.On the other hand,seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations.Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters.Although there exist many differences,pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.Usually,seismic migration and inversion techniques assume an acoustic or isotropic elastic medium.Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property.We present a linearized waveform inversion(LWI)scheme for weakly anisotropic elastic media with vertical transversely isotropic(VTI)symmetry.It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations(ΔVp_(0)/Vp_(0)/Vs_(0)/Vs_(0)/,Δ∈,Δδ)from the long-wavelength reference model.Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration.We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method.The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images.We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters.Especially,the Thomsen parameter is the most difficult to resolve.We also analyze the multi-parameter crosstalk using scattering radiation patterns.The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.展开更多
Full-waveform inversion(FWI) uses the full information of seismic data to obtain a quantitative estimation of subsurface physical parameters. Anisotropic FWI has the potential to recover high-resolution velocity and a...Full-waveform inversion(FWI) uses the full information of seismic data to obtain a quantitative estimation of subsurface physical parameters. Anisotropic FWI has the potential to recover high-resolution velocity and anisotropy parameter models, which are critical for imaging the long-offset and wideazimuth data. We develop an acoustic anisotropic FWI method based on a simplified pure quasi P-wave(qP-wave) equation, which can be solved efficiently and is beneficial for the subsequent inversion.Using the inverse Hessian operator to precondition the functional gradients helps to reduce the parameter tradeoff in the multi-parameter inversion. To balance the accuracy and efficiency, we extend the truncated Gauss-Newton(TGN) method into FWI of pure qP-waves in vertical transverse isotropic(VTI) media. The inversion is performed in a nested way: a linear inner loop and a nonlinear outer loop.We derive the formulation of Hessian-vector products for pure qP-waves in VTI media based on the Lagrange multiplier method and compute the model update by solving a Gauss-Newton linear system via a matrix-free conjugate gradient method. A suitable preconditioner and the Eisenstat and Walker stopping criterion for the inner iterations are used to accelerate the convergence and avoid prohibitive computational cost. We test the proposed FWI method on several synthetic data sets. Inversion results reveal that the pure acoustic VTI FWI exhibits greater accuracy than the conventional pseudoacoustic VTI FWI. Additionally, the TGN method proves effective in mitigating the parameter crosstalk and increasing the accuracy of anisotropy parameters.展开更多
Landfill leaks pose a serious threat to environmental health,risking the contamination of both groundwater and soil resources.Accurate investigation of these sites is essential for implementing effective prevention an...Landfill leaks pose a serious threat to environmental health,risking the contamination of both groundwater and soil resources.Accurate investigation of these sites is essential for implementing effective prevention and control measures.The self-potential(SP)stands out for its sensitivity to contamination plumes,offering a solution for monitoring and detecting the movement and seepage of subsurface pollutants.However,traditional SP inversion techniques heavily rely on precise subsurface resistivity information.In this study,we propose the Attention U-Net deep learning network for rapid SP inversion.By incorporating an attention mechanism,this algorithm effectively learns the relationship between array-style SP data and the location and extent of subsurface contaminated sources.We designed a synthetic landfill model with a heterogeneous resistivity structure to assess the performance of Attention U-Net deep learning network.Additionally,we conducted further validation using a laboratory model to assess its practical applicability.The results demonstrate that the algorithm is not solely dependent on resistivity information,enabling effective locating of the source distribution,even in models with intricate subsurface structures.Our work provides a promising tool for SP data processing,enhancing the applicability of this method in the field of near-subsurface environmental monitoring.展开更多
Wheat cultivar Zhongmai 895 was earlier found to carry YR86 in an 11.6 Mb recombination-suppressed region on chromosome 2AL when crossed with Yangmai 16.To fine-map the YR86 locus,we developed two large F2 populations...Wheat cultivar Zhongmai 895 was earlier found to carry YR86 in an 11.6 Mb recombination-suppressed region on chromosome 2AL when crossed with Yangmai 16.To fine-map the YR86 locus,we developed two large F2 populations from crosses Emai 580/Zhongmai 895 and Avocet S/Zhongmai 895.Remarkably,both populations exhibited suppressed recombination in the same 2AL region.Collinearity analysis across Chinese Spring,Aikang 58,and 10+wheat genomes revealed a 4.1 Mb chromosomal inversion spanning 708.5-712.6 Mb in the Chinese Spring reference genome.Molecular markers were developed in the breakpoint and were used to assess a wheat cultivar panel,revealing that Chinese Spring,Zhongmai 895,and Jimai 22 shared a common sequence named InvCS,whereas Aikang 58,Yangmai 16,Emai 580,and Avocet S shared the sequence named InvAK58.The inverted configuration explained the suppressed recombination observed in all three bi-parental populations.Normal recombination was observed in a Jimai 22/Zhongmai 895 F2 population,facilitating mapping of YR86 to a genetic interval of 0.15 cM corresponding to 710.27-712.56 Mb falling within the inverted region.Thirty-three high-confidence genes were annotated in the interval using the Chinese Spring reference genome,with six identified as potential candidates for YR86 based on genome and transcriptome analyses.These results will accelerate map-based cloning of YR86 and its deployment in wheat breeding.展开更多
Deterministic inversion based on deep learning has been widely utilized in model parameters estimation.Constrained by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learn...Deterministic inversion based on deep learning has been widely utilized in model parameters estimation.Constrained by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model parameters.However,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the solutions.The conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of inversion.In order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency impedance.In addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion results.To illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion method.Four synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed method.In addition,the robustness and generality of the proposed method are verified by the field seismic data.展开更多
Traditionally, simplification has been used in scientific modeling practices. However, recent advancements in deep learning techniques have provided a means to represent complex models. As a result, deep neural networ...Traditionally, simplification has been used in scientific modeling practices. However, recent advancements in deep learning techniques have provided a means to represent complex models. As a result, deep neural networks should be able to approximate the complex models, with a high degree of generalization. To achieve generalization, it is necessary to have a diverse range of examples in the training of the neural network, for example in data-driven FWI, training data should cover the expected subsurface models. To meet this requirement, we porposed a method to create geologically meaningful velocity models with complex structures and severe topography. However, it is important to note that generalization comes with its own set of challenges.Because of significant variation in topography of the generated velocity models, we need to include this information as an additional input data in training of the network. Therefore, we have transformed the seismic data to a fixed datum to incorporate geometric information. Additionally, we have enhanced the network's performance by introducing a term in the network loss function. Multiple metrics have been employed to evaluate the performance of the network. The results indicate that by providing the necessary information to the network and employing computational techniques to refine the model's accuracy, deep neural networks are capable of accurately estimating velocity models in complex environments characterized by extreme topography.展开更多
We apply stochastic seismic inversion and Bayesian facies classification for porosity modeling and igneous rock identification in the presalt interval of the Santos Basin. This integration of seismic and well-derived ...We apply stochastic seismic inversion and Bayesian facies classification for porosity modeling and igneous rock identification in the presalt interval of the Santos Basin. This integration of seismic and well-derived information enhances reservoir characterization. Stochastic inversion and Bayesian classification are powerful tools because they permit addressing the uncertainties in the model. We used the ES-MDA algorithm to achieve the realizations equivalent to the percentiles P10, P50, and P90 of acoustic impedance, a novel method for acoustic inversion in presalt. The facies were divided into five: reservoir 1,reservoir 2, tight carbonates, clayey rocks, and igneous rocks. To deal with the overlaps in acoustic impedance values of facies, we included geological information using a priori probability, indicating that structural highs are reservoir-dominated. To illustrate our approach, we conducted porosity modeling using facies-related rock-physics models for rock-physics inversion in an area with a well drilled in a coquina bank and evaluated the thickness and extension of an igneous intrusion near the carbonate-salt interface. The modeled porosity and the classified seismic facies are in good agreement with the ones observed in the wells. Notably, the coquinas bank presents an improvement in the porosity towards the top. The a priori probability model was crucial for limiting the clayey rocks to the structural lows. In Well B, the hit rate of the igneous rock in the three scenarios is higher than 60%, showing an excellent thickness-prediction capability.展开更多
Herein,a method of true-temperature inversion for a multi-wavelength pyrometer based on fractional-order particle-swarm optimization is proposed for difficult inversion problems with unknown emissivity.Fractional-order...Herein,a method of true-temperature inversion for a multi-wavelength pyrometer based on fractional-order particle-swarm optimization is proposed for difficult inversion problems with unknown emissivity.Fractional-order calculus has the inherent advantage of easily jumping out of local extreme values;here,it is introduced into the particle-swarm algorithm to invert the true temperature.An improved adaptive-adjustment mechanism is applied to automatically adjust the current velocity order of the particles and update their velocity and position values,increasing the accuracy of the true temperature values.The results of simulations using the proposed algorithm were compared with three algorithms using typical emissivity models:the internal penalty function algorithm,the optimization function(fmincon)algorithm,and the conventional particle-swarm optimization algorithm.The results show that the proposed algorithm has good accuracy for true-temperature inversion.Actual experimental results from a rocket-motor plume were used to demonstrate that the true-temperature inversion results of this algorithm are in good agreement with the theoretical true-temperature values.展开更多
The deflection of the vertical(DOV)is the key information in the study of ocean gravity field.However,in most areas,the precision of the prime component of DoV is significantly lower than that of the meridian componen...The deflection of the vertical(DOV)is the key information in the study of ocean gravity field.However,in most areas,the precision of the prime component of DoV is significantly lower than that of the meridian component.To obtain higher accuracy and resolution of ocean gravity information,researchers have proposed a novel altimeter called the wide-swath altimeter.This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height(SSH).In this paper,the Surface Water and Ocean Topography(SWOT)mission with a wide-swath altimeter on board is selected for research.One cycle of swoT sea surface height data is simulated to inverse the DOV in the Arabian Sea(45°E—80°E,0°-30°N),and the inversion results are compared with those of conventional altimeter data.The results demonstrate that the difference between the meridian and prime components derived from the inversion of swoT wide-swath data is minimal,significantly outperforming the inversion results of conventional nadir altimeter data.The advantage of swoT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions.To investigate the impact of this advantage on inversion precision,this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DoV components.The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DoV component is analyzed.It is found that the accuracy of DoV inversion has significantly improved with the increase of geodetic gradient calculation direction.In addition,the effects of various errors and grid spacing in SwoT wide sea surface height data on the precision of Dov inversion are also analyzed.展开更多
The low-wavenumber components in the gradient of full waveform inversion(FWI)play a vital role in the stability of the inversion.However,when FWI is implemented in some high frequencies and current models are not far ...The low-wavenumber components in the gradient of full waveform inversion(FWI)play a vital role in the stability of the inversion.However,when FWI is implemented in some high frequencies and current models are not far away from the real velocity model,an excessive number of low-wavenumber components in the gradient will also reduce the convergence rate and inversion accuracy.To solve this problem,this paper firstly derives a formula of scattering angle weighted gradient in FWI,then proposes a hybrid gradient.The hybrid gradient combines the conventional gradient of FWI with the scattering angle weighted gradient in each inversion frequency band based on an empirical formula derived herein.Using weighted hybrid mode,we can retain some low-wavenumber components in the initial lowfrequency inversion to ensure the stability of the inversion,and use more high-wavenumber components in the high-frequency inversion to improve the convergence rate.The results of synthetic data experiment demonstrate that compared to the conventional FWI,the FWI based on the proposed hybrid gradient can effectively reduce the low-wavenumber components in the gradient under the premise of ensuring inversion stability.It also greatly enhances the convergence rate and inversion accuracy,especially in the deep part of the model.And the field marine seismic data experiment also illustrates that the FWI based on hybrid gradient(HGFWI)has good stability and adaptability.展开更多
Surface wave inversion is a key step in the application of surface waves to soil velocity profiling.Currently,a common practice for the process of inversion is that the number of soil layers is assumed to be known bef...Surface wave inversion is a key step in the application of surface waves to soil velocity profiling.Currently,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization variable.However,an improper selection of the number of layers may lead to an incorrect shear wave velocity profile.In this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil layers.First,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer number.Then,the shear-wave velocity profile is determined by a genetic algorithm with the known layer number.By applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.展开更多
Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and e...Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.展开更多
基金supported by the Major National Science and Technology Projects of China (No. 2008ZX05029-002)CNPC Research Topics of China (No.07B60101)
文摘The Karatau fault is one of the important strike-slip faults in central Asia,and the South Turgay Basin is located towards its northern end.Detailed seismic interpretation indicated that the strikeslip tectonism of the Karatau fault weakened gradually from west to east in the South Turgay Basin.Typical flower structures developed on the section,and strike-slip faults showed an echelon pattern on planar view.The Karatau strike-slip fault affected the South Turgay Basin in two periods：（1） The South Turgay strike-slip pull-apart rift basin formed as a result of regional extensive stress in the Early-Middle Jurassic,characterized by the juxtaposition of horsts and grabens.The formation of horsts provided favorable reservoir spaces for later hydrocarbon accumulation,and different filling stages of grabens controlled different reservoir-forming factors in grabens.（2） Two stages of tectonic inversion occurred in the Late Jurassic and Late Cretaceous and played a crucial role in the final shape of the structure in the South Turgay Basin.The oil and gas migrated to form reservoirs and mainly concentrated in the horsts,graben slopes and in both sides of the strike-slip fault zone.In the case of the degree of accumulation of petroleum,the factor explaining why horsts are better than grabens is the strike-slip pull-apart of the South Turgay Basin,and the structure inversion of the South Turgay Basin explains why the west graben is better than the east one.Overall,the Karatau strike-slip fault played a very important role in the formation of the South Turgay Basin and its hydrocarbon accumulations.
基金National Natural Science Foundation of China under Grant 42276055National Key Research and Development Program under Grant 2022YFC2803503Fundamental Research Funds for the Central Universities under Grant 202262008.
文摘Full waveform inversion methods evaluate the properties of subsurface media by minimizing the misfit between synthetic and observed data.However,these methods omit measurement errors and physical assumptions in modeling,resulting in several problems in practical applications.In particular,full waveform inversion methods are very sensitive to erroneous observations(outliers)that violate the Gauss–Markov theorem.Herein,we propose a method for addressing spurious observations or outliers.Specifically,we remove outliers by inverting the synthetic data using the local convexity of the Gaussian distribution.To achieve this,we apply a waveform-like noise model based on a specific covariance matrix definition.Finally,we build an inversion problem based on the updated data,which is consistent with the wavefield reconstruction inversion method.Overall,we report an alternative optimization inversion problem for data containing outliers.The proposed method is robust because it uses uncertainties.This method enables accurate inversion,even when based on noisy models or a wrong wavelet.
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
基金supported by the Special Fund of the Institute of Geophysics, China Earthquake Administration (No. DQJB21B32)the National Key R&D Program of China (No. 2022YFF0800601)。
文摘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.
文摘Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.
基金Key Clinical Specialty Discipline Construction Program of Fujian,Fujian Health Medicine and Politics,No.[2022]884.
文摘BACKGROUND In laparoscopic proximal gastrectomy(LPG),the prolapse of the hepatic left lateral lobe near the lesser curvature and esophageal hiatus can obstruct the field of vision and operation.Therefore,it is necessary to retract or obstruct the hepatic left lateral lobe to ensure a clear field of vision.AIM To investigate the safety and clinical efficacy of the modified hepatic left lateral lobe inversion technique for LPG.METHODS A retrospective analysis was conducted on the clinical data of 13 consecutive patients with early-stage upper gastric adenocarcinoma or adenocarcinoma of the esophagogastric junction treated with LPG from January to December 2023 at the Department of Gastrointestinal Surgery,Second Affiliated Hospital of Fujian Medical University.The modified hepatic left lateral lobe inversion technique was used to expose the surgical field in all patients,and short-term outcomes were observed.RESULTS In all 13 patients,the modified hepatic left lateral lobe inversion technique was successful during surgery without the need for re-retraction or alteration of the liver traction method.There were no instances of esophageal hiatus occlusion,eliminating the need for forceps to assist in exposure.There was no occurrence of intraoperative hepatic hemorrhage,hepatic vein injury,or hepatic congestion.No postoperative digestive complications of Clavien-Dindo grade≥II occurred wi-thin 30 days after surgery,except for a single case of pulmonary infection.Some patients experienced increases in alanine aminotransferase and aspartate aminotransferase levels on the first day after surgery,which significantly decreased by the third day and returned to normal by the seventh day after surgery.CONCLUSION The modified hepatic left lateral lobe inversion technique has demonstrated satisfactory results,offering ad-vantages in terms of facilitating surgical procedures,reducing surgical trauma,and protecting the liver.
基金supported by the National Natural Science Foundation of China(Grant Nos.61888102 and 12274447)the National Key Research and Development Program of China(Grant Nos.2021YFA1202900 and 2023YFA1407000)+2 种基金the KeyArea Research and Development Program of Guangdong Province,China(Grant No.2020B0101340001)the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030002)the Strategic Priority Research Program of Chinese Academy of Sciences(CAS)(Grant No.XDB0470101)。
文摘Hall effects have been the central paradigms in modern physics,materials science and practical applications,and have led to many exciting breakthroughs,including the discovery of topological Chern invariants and the revolution of metrological resistance standard.To date,the Hall effects have mainly focused on a single degree of freedom(Do F),and most of them require the breaking of spatial-inversion and/or time-reversal symmetries.Here we demonstrate a new type of Hall effect,i.e.,layer-valley Hall effect,based on a combined layer-valley Do F characterized by the product of layer and valley indices.The layer-valley Hall effect has a quantum origin arising from the layer-valley contrasting Berry curvature,and can occur in nonmagnetic centrosymmetric crystals with both spatial-inversion and time-reversal symmetries,transcending the symmetry constraints of single Do F Hall effect based on the constituent layer or valley index.Moreover,the layer-valley Hall effect is highly tunable and shows a W-shaped pattern in response to the out-of-plane electric fields.Additionally,we discuss the potential detection approaches and material-specific design principles of layer-valley Hall effect.Our results demonstrate novel Hall physics and open up exotic paradigms for new research direction of layer-valleytronics that exploits the quantum nature of the coupled layer-valley DoF.
基金support from the European Union’s Horizon 2020 research and innovation program through the ERC Starting Grant,entitled“The Collaborative Seismic Earth Model”(Grant No.714069)provided by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No.955515(SPIN ITN)+1 种基金the ChEESE project(Folch et al.,2023)which secured funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No.823844。
文摘Having been a seemingly unreachable ideal for decades,3-D full-waveform inversion applied to massive seismic datasets has become reality in recent years.Often achieving unprecedented resolution,it has provided new insight into the structure of the Earth,from the upper few metres of soil to the entire globe.Motivated by these successes,the technology is now being translated to medical ultrasound and non-destructive testing.Despite remarkable progress,the computational cost of fullwaveform inversion continues to be a major concern.It limits the amount of data that can be exploited,and it largely inhibits quantitative and comprehensive uncertainty analyses.These notes complement a presentation on recent developments in full-waveform inversion that are intended to reduce computational cost and assimilate more data,thereby improving tomographic resolution.The suite of strategies includes flexible and user-friendly spectral-element simulations,the design of wavefieldadapted meshes that harness prior information on wavefield geometry,dynamic mini-batch optimisation that naturally takes advantage of data redundancies,and collaborative multi-scale updating to jointly constrain crustal and mantle structure.
文摘Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuities.More specifically,seismic migration estimates the reflectivity function(stacked average reflectivity or pre-stack angle-dependent reflectivity)from seismic reflection data.On the other hand,seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations.Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters.Although there exist many differences,pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.Usually,seismic migration and inversion techniques assume an acoustic or isotropic elastic medium.Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property.We present a linearized waveform inversion(LWI)scheme for weakly anisotropic elastic media with vertical transversely isotropic(VTI)symmetry.It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations(ΔVp_(0)/Vp_(0)/Vs_(0)/Vs_(0)/,Δ∈,Δδ)from the long-wavelength reference model.Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration.We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method.The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images.We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters.Especially,the Thomsen parameter is the most difficult to resolve.We also analyze the multi-parameter crosstalk using scattering radiation patterns.The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.
基金supported by the National Natural Science Foundation of China (grant No. 42174156)the Young Science and Technology Star Project of Shaanxi Province (grant No. 2023KJXX-021)the Fundamental Research Funds for the Central Universities, CHD (grant Nos. 300102263401 and 300102264204)。
文摘Full-waveform inversion(FWI) uses the full information of seismic data to obtain a quantitative estimation of subsurface physical parameters. Anisotropic FWI has the potential to recover high-resolution velocity and anisotropy parameter models, which are critical for imaging the long-offset and wideazimuth data. We develop an acoustic anisotropic FWI method based on a simplified pure quasi P-wave(qP-wave) equation, which can be solved efficiently and is beneficial for the subsequent inversion.Using the inverse Hessian operator to precondition the functional gradients helps to reduce the parameter tradeoff in the multi-parameter inversion. To balance the accuracy and efficiency, we extend the truncated Gauss-Newton(TGN) method into FWI of pure qP-waves in vertical transverse isotropic(VTI) media. The inversion is performed in a nested way: a linear inner loop and a nonlinear outer loop.We derive the formulation of Hessian-vector products for pure qP-waves in VTI media based on the Lagrange multiplier method and compute the model update by solving a Gauss-Newton linear system via a matrix-free conjugate gradient method. A suitable preconditioner and the Eisenstat and Walker stopping criterion for the inner iterations are used to accelerate the convergence and avoid prohibitive computational cost. We test the proposed FWI method on several synthetic data sets. Inversion results reveal that the pure acoustic VTI FWI exhibits greater accuracy than the conventional pseudoacoustic VTI FWI. Additionally, the TGN method proves effective in mitigating the parameter crosstalk and increasing the accuracy of anisotropy parameters.
基金Projects(42174170,41874145,72088101)supported by the National Natural Science Foundation of ChinaProject(CX20200228)supported by the Hunan Provincial Innovation Foundation for Postgraduate,China。
文摘Landfill leaks pose a serious threat to environmental health,risking the contamination of both groundwater and soil resources.Accurate investigation of these sites is essential for implementing effective prevention and control measures.The self-potential(SP)stands out for its sensitivity to contamination plumes,offering a solution for monitoring and detecting the movement and seepage of subsurface pollutants.However,traditional SP inversion techniques heavily rely on precise subsurface resistivity information.In this study,we propose the Attention U-Net deep learning network for rapid SP inversion.By incorporating an attention mechanism,this algorithm effectively learns the relationship between array-style SP data and the location and extent of subsurface contaminated sources.We designed a synthetic landfill model with a heterogeneous resistivity structure to assess the performance of Attention U-Net deep learning network.Additionally,we conducted further validation using a laboratory model to assess its practical applicability.The results demonstrate that the algorithm is not solely dependent on resistivity information,enabling effective locating of the source distribution,even in models with intricate subsurface structures.Our work provides a promising tool for SP data processing,enhancing the applicability of this method in the field of near-subsurface environmental monitoring.
基金financially supported by the National Key Research and Development Program of China (2022YFD1200900 and 2022YFD1200904)the Agricultural Science and Technology Innovation Program+1 种基金Fundamental Research Funds for Central NonProfit of Institute of Crop Sciences, CAASShijiazhuang S&T Project (232490022A and 232490432A)
文摘Wheat cultivar Zhongmai 895 was earlier found to carry YR86 in an 11.6 Mb recombination-suppressed region on chromosome 2AL when crossed with Yangmai 16.To fine-map the YR86 locus,we developed two large F2 populations from crosses Emai 580/Zhongmai 895 and Avocet S/Zhongmai 895.Remarkably,both populations exhibited suppressed recombination in the same 2AL region.Collinearity analysis across Chinese Spring,Aikang 58,and 10+wheat genomes revealed a 4.1 Mb chromosomal inversion spanning 708.5-712.6 Mb in the Chinese Spring reference genome.Molecular markers were developed in the breakpoint and were used to assess a wheat cultivar panel,revealing that Chinese Spring,Zhongmai 895,and Jimai 22 shared a common sequence named InvCS,whereas Aikang 58,Yangmai 16,Emai 580,and Avocet S shared the sequence named InvAK58.The inverted configuration explained the suppressed recombination observed in all three bi-parental populations.Normal recombination was observed in a Jimai 22/Zhongmai 895 F2 population,facilitating mapping of YR86 to a genetic interval of 0.15 cM corresponding to 710.27-712.56 Mb falling within the inverted region.Thirty-three high-confidence genes were annotated in the interval using the Chinese Spring reference genome,with six identified as potential candidates for YR86 based on genome and transcriptome analyses.These results will accelerate map-based cloning of YR86 and its deployment in wheat breeding.
基金the sponsorship of Shandong Province Foundation for Laoshan National Laboratory of Science and Technology Foundation(LSKJ202203400)National Natural Science Foundation of China(42174139,42030103)Science Foundation from Innovation and Technology Support Program for Young Scientists in Colleges of Shandong Province and Ministry of Science and Technology of China(2019RA2136)。
文摘Deterministic inversion based on deep learning has been widely utilized in model parameters estimation.Constrained by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model parameters.However,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the solutions.The conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of inversion.In order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency impedance.In addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion results.To illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion method.Four synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed method.In addition,the robustness and generality of the proposed method are verified by the field seismic data.
文摘Traditionally, simplification has been used in scientific modeling practices. However, recent advancements in deep learning techniques have provided a means to represent complex models. As a result, deep neural networks should be able to approximate the complex models, with a high degree of generalization. To achieve generalization, it is necessary to have a diverse range of examples in the training of the neural network, for example in data-driven FWI, training data should cover the expected subsurface models. To meet this requirement, we porposed a method to create geologically meaningful velocity models with complex structures and severe topography. However, it is important to note that generalization comes with its own set of challenges.Because of significant variation in topography of the generated velocity models, we need to include this information as an additional input data in training of the network. Therefore, we have transformed the seismic data to a fixed datum to incorporate geometric information. Additionally, we have enhanced the network's performance by introducing a term in the network loss function. Multiple metrics have been employed to evaluate the performance of the network. The results indicate that by providing the necessary information to the network and employing computational techniques to refine the model's accuracy, deep neural networks are capable of accurately estimating velocity models in complex environments characterized by extreme topography.
基金Equinor for financing the R&D projectthe Institute of Science and Technology of Petroleum Geophysics of Brazil for supporting this research。
文摘We apply stochastic seismic inversion and Bayesian facies classification for porosity modeling and igneous rock identification in the presalt interval of the Santos Basin. This integration of seismic and well-derived information enhances reservoir characterization. Stochastic inversion and Bayesian classification are powerful tools because they permit addressing the uncertainties in the model. We used the ES-MDA algorithm to achieve the realizations equivalent to the percentiles P10, P50, and P90 of acoustic impedance, a novel method for acoustic inversion in presalt. The facies were divided into five: reservoir 1,reservoir 2, tight carbonates, clayey rocks, and igneous rocks. To deal with the overlaps in acoustic impedance values of facies, we included geological information using a priori probability, indicating that structural highs are reservoir-dominated. To illustrate our approach, we conducted porosity modeling using facies-related rock-physics models for rock-physics inversion in an area with a well drilled in a coquina bank and evaluated the thickness and extension of an igneous intrusion near the carbonate-salt interface. The modeled porosity and the classified seismic facies are in good agreement with the ones observed in the wells. Notably, the coquinas bank presents an improvement in the porosity towards the top. The a priori probability model was crucial for limiting the clayey rocks to the structural lows. In Well B, the hit rate of the igneous rock in the three scenarios is higher than 60%, showing an excellent thickness-prediction capability.
基金supported by the National Natural Science Foundation of China(Grant No.62205280)the Graduate Innovation Foundation of Yantai University(Grant No.GGIFYTU2348).
文摘Herein,a method of true-temperature inversion for a multi-wavelength pyrometer based on fractional-order particle-swarm optimization is proposed for difficult inversion problems with unknown emissivity.Fractional-order calculus has the inherent advantage of easily jumping out of local extreme values;here,it is introduced into the particle-swarm algorithm to invert the true temperature.An improved adaptive-adjustment mechanism is applied to automatically adjust the current velocity order of the particles and update their velocity and position values,increasing the accuracy of the true temperature values.The results of simulations using the proposed algorithm were compared with three algorithms using typical emissivity models:the internal penalty function algorithm,the optimization function(fmincon)algorithm,and the conventional particle-swarm optimization algorithm.The results show that the proposed algorithm has good accuracy for true-temperature inversion.Actual experimental results from a rocket-motor plume were used to demonstrate that the true-temperature inversion results of this algorithm are in good agreement with the theoretical true-temperature values.
基金support from the National Natural Science Foundation of China(No.42274006,42192535,42242015).
文摘The deflection of the vertical(DOV)is the key information in the study of ocean gravity field.However,in most areas,the precision of the prime component of DoV is significantly lower than that of the meridian component.To obtain higher accuracy and resolution of ocean gravity information,researchers have proposed a novel altimeter called the wide-swath altimeter.This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height(SSH).In this paper,the Surface Water and Ocean Topography(SWOT)mission with a wide-swath altimeter on board is selected for research.One cycle of swoT sea surface height data is simulated to inverse the DOV in the Arabian Sea(45°E—80°E,0°-30°N),and the inversion results are compared with those of conventional altimeter data.The results demonstrate that the difference between the meridian and prime components derived from the inversion of swoT wide-swath data is minimal,significantly outperforming the inversion results of conventional nadir altimeter data.The advantage of swoT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions.To investigate the impact of this advantage on inversion precision,this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DoV components.The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DoV component is analyzed.It is found that the accuracy of DoV inversion has significantly improved with the increase of geodetic gradient calculation direction.In addition,the effects of various errors and grid spacing in SwoT wide sea surface height data on the precision of Dov inversion are also analyzed.
基金jointly supported by Young Scientists Cultivation Fund Project of Harbin Engineering University(79000013/003)the Mount Taishan Industrial Leading Talent Project+1 种基金the Great and Special Project under Grant KJGG-2022-0104 of CNOOC Limitedthe National Natural Science Foundation of China(42006064,42106070,42074138)。
文摘The low-wavenumber components in the gradient of full waveform inversion(FWI)play a vital role in the stability of the inversion.However,when FWI is implemented in some high frequencies and current models are not far away from the real velocity model,an excessive number of low-wavenumber components in the gradient will also reduce the convergence rate and inversion accuracy.To solve this problem,this paper firstly derives a formula of scattering angle weighted gradient in FWI,then proposes a hybrid gradient.The hybrid gradient combines the conventional gradient of FWI with the scattering angle weighted gradient in each inversion frequency band based on an empirical formula derived herein.Using weighted hybrid mode,we can retain some low-wavenumber components in the initial lowfrequency inversion to ensure the stability of the inversion,and use more high-wavenumber components in the high-frequency inversion to improve the convergence rate.The results of synthetic data experiment demonstrate that compared to the conventional FWI,the FWI based on the proposed hybrid gradient can effectively reduce the low-wavenumber components in the gradient under the premise of ensuring inversion stability.It also greatly enhances the convergence rate and inversion accuracy,especially in the deep part of the model.And the field marine seismic data experiment also illustrates that the FWI based on hybrid gradient(HGFWI)has good stability and adaptability.
基金provided through research grant No.0035/2019/A1 from the Science and Technology Development Fund,Macao SARthe assistantship from the Faculty of Science and Technology,University of Macao。
文摘Surface wave inversion is a key step in the application of surface waves to soil velocity profiling.Currently,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization variable.However,an improper selection of the number of layers may lead to an incorrect shear wave velocity profile.In this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil layers.First,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer number.Then,the shear-wave velocity profile is determined by a genetic algorithm with the known layer number.By applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.
基金supported by the Fundamental Research Funds for the Central Universities(No.202262012)the National Natural Science Foundation of China(No.42076224)the National Key R&D Program of China(No.2021YFC2801200).
文摘Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.
