Density Inversion Research Articles

Improved Approaches for 3D Gravity and Gradient Imaging Based on Potential Field Separation: Application to the Magma Chamber in Wudalianchi Volcanic Field, Northeastern China

The gravity and gradient anomalies contain valuable information about the underground geological structures at various depths. Deep and shallow buried source bodies are able to be identified through multi-scale field separation processes, and visual comprehensions of geological structures can be obtained via 3D density inversion techniques. In this study, we propose an improved 3D imaging strategy based on gravitational field separation using the preferential continuation filter. This strategy incorporates the relationship between spectral features and buried depths of source bodies, allowing for a one-step transformation from planar gravity and full-tensor gradient field observations to a 3D density structure in the wave-number domain. Synthetic tests validate the effectiveness and robustness of the gravity and gradient imaging approaches, highlighting their advantages in high vertical resolution and low computational requirements. Nonetheless, it should be noted that the imaging effects of horizontal gradients Γxx and Γyy are unsatisfactory due to their weak noise resistance. Thus, they are not suitable for real data applications. The other imaging approaches are further applied to recover the subsurface 3D density structure beneath the Weishan cone in Wudalianchi Volcanic Field, Northeastern China. Our results provide insights into the possible location and shape of the low-density magma chamber. Also, the potential presence of partial melts is inferred and supported from a gravity perspective. The primary advantage of these approaches is their ability to generate a reasonable geological model in scenarios with limited prior information and physical property constraints. As a result, they have significant practical value in the field of applied geophysics, including mineral exploration and volcanology studies.

Soil salinization poses greater effects than soil moisture on field crop growth and yield in arid farming areas with intense irrigation

Soil moisture and salinization are key environmental factors affecting crop growth and yield in arid farming areas with intense irrigation. Quantifying their effects on crops is beneficial to understanding the principle of soil water-salt interactions. Due to the strong coupling relationship between them, the independent effect on field crops is hard to distinguish clearly. In this study, taking Yongji Sub-irrigation District (YJSID) in Inner Mongolia of China as case study, the sorting bins method and GeoDetector were employed to try to disentangle relative effects of soil moisture and salinization on crop development and yield during growing seasons in 2021–2022. The regional soil water content (SWC) and soil salt content (SSC) were firstly mapped and validated through the inverse density weighted method and random forest model. Separated effects of SWC and SSC on solar-induced chlorophyll fluorescence (SIF), gross primary productivity (GPP), and crop yield were then calculated and presented. Results showed that low SWC inhibited SIF and the ratio of GPP to SIF (GPP/SIF) in SSC bins, as their values declined among 52.989% and 71.801% of YJSID. In SWC bins, the increase of SIF and GPP/SIF covered 91.356% and 50.087% of the area, indicating that low SSC could bring out higher SIF and GPP/SIF for field crops. Relative importance assessment suggested that SSC posed greater impacts than SWC on SIF and GPP/SIF in YJSID with the area of 77.188% and 59.628%, respectively. To the SWC effects, it performed greater for the C3 crops (sunflower, wheat, interplant, others) than the C4 plant (maize) in SIF, while reversely in GPP/SIF. The q value calculated from GeoDetector also indicated that SSC had greater effects than SWC on crop yield. Increased SSC tended to reduce grain yield with linear relationships, and the severity was bigger for maize than sunflower. These results would contribute to further understanding of the key processes involved in soil water-salt interactions and dealing with them better in agricultural practice.

Study of Active Medium Length Effect on Characteristics of Passive QSwitching and Stokes with Anti-Stokes Pulse

Objective: To study the effect of active medium length on the characteristics of passive Q-switching pulses, Stokes pulses, and anti-Stokes pulses generated by laser-Raman medium interaction in optical systems, theoretically. Methods: The optical system consists of Nd+3:YVO4, PbWO4, and Cr+4:YAG as active mediums, Raman medium, and saturable absorber materials, respectively. The rate equations model has been used in the study, and the Rung-Kutta-Fehelberg numerical method was used to solve the rate equations. Finding: The result shows that, decreasing of the active medium length leads to emit high power pulses at advanced time. It also leads to increase in initial value and the maximum value of population inversion density, and leads to increase in the energy of passive Q-switching pulses, Stokes pulses, and anti-Stokes pulses. So the decreasing of the active medium length leads to decrease in the pulses duration and the final population inversion density. To increase the power of the three generated pulses, the length of the active medium used in the system must be decreased. Novelty: The characteristics of two pulses generated by Laser-Raman interaction (passive Q-switching pulse and Stokes pulse) have been of interest in some studies. This study investigates the effect of the active medium length on the characteristics of three pulses generated (anti-Stokes pulse with Stokes pulse as well as the passive Q-switching pulses) by the optical system rather than two pulses. Keywords: Laser; Nd+3 :YVO4; passive Q-­switching pulse; Stokes and anti-­Stokes pulses 1

Seismic Attributes and Inverse Quantitative Static Density–Porosity–Constraint Reservoir Simulations of Naturally-Fractured Hydrocarbon-Bearing Lower Cretaceous Shallow-Marine Architectures, Onshore Indus, Pakistan

Seismic Attributes and Inverse Quantitative Static Density–Porosity–Constraint Reservoir Simulations of Naturally-Fractured Hydrocarbon-Bearing Lower Cretaceous Shallow-Marine Architectures, Onshore Indus, Pakistan

Unconventional Error Cancellation Explains the Success of Hartree-Fock Density Functional Theory for Barrier Heights.

Energy barriers, which control the rates of chemical reactions, are seriously underestimated by computationally efficient semilocal approximations for the exchange-correlation energy. The accuracy of a semilocal density functional approximation is strongly boosted for reaction barrier heights by evaluating that approximation non-self-consistently on Hartree-Fock electron densities, which has been known for ∼30 years. The conventional explanation is that the Hartree-Fock theory yields the more accurate density. This work presents a benchmark Kohn-Sham inversion of accurate coupled-cluster densities for the reaction H2 + F → HHF → H + HF and finds a strong, understandable cancellation between positive (excessively overcorrected) density-driven and large negative functional-driven errors (expected from stretched radical bonds in the transition state) within this Hartree-Fock density functional theory. This confirms earlier conclusions (Kaplan, A. D., et al. J. Chem. Theory Comput. 2023, 19, 532-543) based on 76 barrier heights and three less reliable, but less expensive, fully nonlocal density functional proxies for the exact density.

Inversion of the Electron Density in the Lower Ionosphere Using Artificial Intelligence

Inversion of the Electron Density in the Lower Ionosphere Using Artificial Intelligence

Asteroseismic modelling strategies in the PLATO era

Context. In the framework of the PLATO mission, to be launched in late 2026, seismic inversion techniques will play a key role in determining the mission precision requirements in terms of stellar mass, radius, and age. It is therefore relevant to discuss the challenges of the automation of seismic inversions, which were originally developed for individual modelling. Aims. We tested the performance of our newly developed quality assessment procedure of seismic inversions, which was designed for pipeline implementation. Methods. We applied our assessment procedure to a testing set composed of 26 reference models. We divided our testing set into two categories: calibrator targets whose inversion behaviour is well known from the literature and targets for which we assessed the quality of the inversion manually. We then compared the results of our assessment procedure with our expectations as a human modeller for three types of inversions: the mean density inversion, the acoustic radius inversion, and the central entropy inversion. Results. We find that our quality assessment procedure performs as well as a human modeller. The mean density inversion and the acoustic radius inversion are suited to large-scale applications, but not the central entropy inversion, at least in its current form. Conclusions. Our assessment procedure shows promising results for a pipeline implementation. It is based on the by-products of the inversion and therefore requires few numerical resources to quickly assess the quality of an inversion result.

DA-Net: Density-Aware 3D Object Detection Network for Point Clouds

3D object detection is an important but demanding task, which has become an active research topic in the field of multimedia. Much recent research has been devoted to exploiting end-to-end trainable object detection networks with point clouds. However, most state-of-the-art methods have bottlenecks in detecting occluded objects and small objects, because the sparseness of point clouds is exacerbated on these objects. In this paper, a Density-Aware 3D object detection network (DA-Net) is proposed to improve the perception performance for detecting occluded and small objects, which contains four components: a backbone module with an inverse density scoring module (IDM) and a point-wise attention module (PAM), a 3D intersection over union Estimation Module (3DEM), a Consistent Label Assignment (CLA) method and an Adaptive-Soft-NMS method. The proposed backbone module makes the network concentrate on low-density points of occluded objects, and suppresses outliers and background points. Then, the 3DEM is introduced to evaluate the localization quality of the prediction boxes. Furthermore, the proposed CLA method can more accurately select positive and negative samples for small objects. Finally, Adaptive-Soft-NMS is proposed in our method to reduce the number of false detections during inference and thereby improve detection performance substantially. Extensive experiments demonstrated that the proposed method achieves state-of-the-art performance on two large-scale datasets, SUN RGB-D (62.1% in terms of mAP@0.25) and ScanNetV2 (67.1% in terms of mAP@0.25), and in particular, the detection accuracy of small objects and occluded objects are extremely improved.

Improvement of density inversion efficiency with projected gradient method: Application to FTG data

With the development of instruments for measuring Earth's gravity gradient tensor, full tensor gravity (FTG) data can be obtained validly and accurately. The highly precise performance of FTG data ensures that they can play an important role in many domains. Generally, FTG data can be acquired from airborne platform, and large-scale data can be obtained by long term observations. For this type of data, research methods for large data processing are very important. Three-dimensional data inversion is an effective and significant method for the quantitative interpretation of FTG data, which has received much attention. Large-scale data inversion is inevitable, and may consume large amounts of time with increase in the amount of data and model parameters. The main aim of this study is to improve the calculation efficiency of FTG data inversion compared with general conjugate gradient (CG) method. Accordingly, an improved gradient method with projections onto a convex set (the projected gradient method) was applied to accelerate the recovery rate of the sub-surface rock density, and a corresponding preconditioning factor was introduced to further improve the calculation efficiency of inversion. This new projected gradient method can improve the calculation efficiency of large amounts of FTG data, which is very necessary for practical application of FTG data. The application of synthetic FTG data with Gaussian noise and the real data demonstrated the feasibility and application value of the proposed inversion method.

Adaptive Space–Location-Weighting Function Method for High-Precision Density Inversion of Gravity Data

Underground 3D density variation can be obtained via the inversion of gravity data, which is a very important basis for structural division, oil and gas structure definition, and mineral resource evaluation. A depth-weighting function is usually introduced as a structural constraint in density inversion to solve the skin effect. We propose an adaptive space–location-weighting (ASW) function for gravity field data to improve the resolution of the inversion, which adds the position and depth information provided by the DEXP method to form a new weighting function. The weighting function is partitioned according to the horizontal distribution of the source and can effectively improve the resolution of field sources with different positions and different depths. The results of model tests have shown that the ASW function method can significantly improve the precision and resolution of density inversion results and has good noise immunity. The ASW method was applied to interpret the real gravity data of a mining area in Shandong, and we speculated potential mineralization based on the inversion results, which corresponded well with the logging results.

Expected spacing

The expected spacing, or average difference between consecutive order statistics, is known for uniform and exponential random variates. For other distributions, we can estimate it using the derivative of the inverse cumulative density (quantile) function, since passing a uniformly drawn value, whose spacing we know, through this function generates a random value from the distribution, and the difference between two such uniform values approximates the derivative. We calculate the spacing for two new distributions, the logistic and Gumbel, and show the estimator is exact for the first and approximate for the second. Comparing the estimators for six other distributions to numeric simulations shows they are also approximations, best in the middle of the order statistics with an error that goes inversely with the square of the sample size, but degrading in the tails.

Impact of Gaussian Traps on the Characteristics of L-shaped Tunnel Field-effect Transistor

Background: Internet of Things (IoT) applications require high-performance TFET devices that can be efficiently integrated with the cyber world and physical world. Objectives: The impact of introducing Gaussian traps in hetero-junction tunneling-field-effecttransistors (TFET) with an L-shaped gate is presented. Methods: The 2-D TCAD study of different characteristics, like input, output characteristics, and noise spectral density with trap and without trap, has been performed. Results: The simulation results showed that in L-shaped TFET (L_TFET), the high on-current of 1.93×10-5 A/μm, low off-current/leakage current of 1.09×10-13 A/μm, and steep sub-threshold slope (SS) of 24 mV/dec without traps and on-current of 8.46×10-6 A/μm, off-current of 2.86×10- 11 A/μm, and degraded SS with traps are observed. They also indicated that the presence of traps reduces gate-drain capacitance (Cgd), while gate-source capacitance (Cgs) remains unaffected. In addition, in L_TFET, the drain current noise spectral density (SID) of 7.63 E-21 (A2/Hz) at LF and 2.69 E-26 (A2/Hz) at HF while the noise voltage spectral density (SVG) of 7.33 E-4 (V2/Hz) at LF and 2.59 E-15 (V2/Hz) at HF without traps have been investigated in this study. The inverse dependence of drain current noise spectral density on frequency has been observed to lower the effect of noise at HF. Conclusion: It can be concluded that the proposed L_TFET device is free from ambipolarity conduction and can be well-suited for low-power applications.

Seismic fluid identification method based on the joint PP‐ and SH–SH‐wave stochastic inversion

AbstractPre‐stack seismic inversion is an effective method for elastic parameter inversion using seismic data, which facilitates seismic fluid identification. However, pure PP‐wave inversion has issues of strong multi‐solution and limited prediction accuracy. Therefore, we propose a seismic fluid identification approach based on the joint PP‐ and SH–SH‐wave stochastic inversion. First, the linearized SH–SH‐wave amplitude variation with offset approximation parameterized by shear modulus and density is derived. Numerical simulations demonstrate that the SH–SH‐wave amplitude variation with offset approximation has a good accuracy. Reflection coefficient contribution analysis indicates that the new formulation has better parameter sensitivity to shear modulus and density than the PP wave amplitude variation with offset approximation derived by Russell, which helps one to improve the inversion of shear modulus and density. On this basis, we construct a joint inversion equation of PP and SH–SH waves for a Russell fluid indicator, a shear modulus and density and present a novel joint stochastic inversion method based on the ensemble smoother with multiple data assimilation. Stanford VI‐E model tests reveal that the Russell fluid indicator factor, shear modulus and density obtained from the joint PP‐ and SH–SH‐wave inversion have higher identification accuracy and smaller relative errors than those from pure PP‐wave inversion. Furthermore, field data tests indicate that this method has practical applicability in seismic fluid identification.

Subsoil density field reconstruction through 3-D FWI: a systematic comparison between vertical- and horizontal-force seismic sources

SUMMARY Bulk-density (ρ) of soil is an important indicator of soil compaction and type. A knowledge of the spatial variability of in situ soil density is important in geotechnical engineering, hydrology and agriculture. Surface geophysical methods have so far shown limited success in providing an accurate and high-resolution image of 3-D soil-density distribution. In this pursuit, 3-D seismic full-waveform inversion (FWI) is promising, provided the robustness and accuracy of density inversion via this approach can be established in the near-surface scale. However, simultaneous reconstruction of ρ and seismic wave velocities through multiparameter FWI remains a challenging task. Near-surface seismic data are commonly dominated by dispersive surface waves whose velocities are controlled by the value and distribution of shear-wave velocity (VS). One major difficulty in estimating reliably ρ from near-surface seismic data is due to the relatively low sensitivity of the seismic wavefield to ρ compared to seismic velocities. Additionally, the accuracy of the estimated ρ decreases due to error in VS—an issue known as parameter coupling. Parameter coupling makes it difficult to estimate accurately ρ within the framework of conventional gradient-based FWI. More sophisticated optimization approaches (e.g. truncated Newton) can reduce the effect of parameter coupling, but these approaches are commonly not affordable in near-surface applications due to heavy computational burden. In this research, we have investigated how choosing correctly the force direction of the seismic source can contribute to a higher accuracy of ρ estimates through 3-D FWI. Using scattered wavefields, the Hessian, and inversion tests, an in-depth and systematic investigation of data sets corresponding to different force directions has been carried out. A comparison of the scattered wavefields due to a point-localized ρ perturbation for different force directions shows the robustness of the horizontal-force data set to noise compared to the vertical-force data set. Furthermore, for a point-scatterer model, an analysis of the gradients of the misfit function using the Hessian shows that utilizing a horizontal-force source enables one to reconstruct the high-resolution gradient with relatively small parameter coupling. Finally, inversion tests for two different subsoil models demonstrate that 3-D FWI on a horizontal-force-source seismic data set is capable of providing a more accurate 3-D ρ distribution in soil compared to a vertical-force-source data set. Our results show that the use of a horizontal-force source might allow avoiding computationally demanding, costly optimization approaches in 3-D FWI.

Geophysical constraints on the deep structure beneath the Xiong'an New Area geothermal field, North China

The region known as the Xiong'an New Area serves as a testing and validation research laboratory for the development and utilization of geothermal energy in China. To better understand the lithospheric structure and associated geothermal features in the region, a comprehensive approach was employed, combining deep seismic reflection and an overlapping magnetotelluric sounding (MT) profile analysis. The analysis reveals arched reflections, coinciding with a relatively high-resistivity anomaly, demonstrating concentric patterns that indicate the presence of lithospheric gneiss domes beneath the Rongcheng and Niutuozhen structural highs. Additionally, the seismic image reveals a marked transparent zone characterised by low-resistivity beneath the Niubei slope. These dome-like features are interpreted as plutons and/or intrusive bodies that were formed by upwelling of the asthenosphere during the early Paleogene era. These relatively deep-rooted plutons are highly likely to be the primary heat sources in this geothermal region. Deep-seated faults beneath the Niubei slope act as channels, allowing the flow of fluids and the transfer of heat from the source to shallower levels. Isotope data supports that the notion that near-surface water flows through a shallow network of fractures, ultimately reaching the geothermal reservoir. The interpreted geometry suggests that the gneiss domes likely resulted from a Rayleigh-Taylor instability process. This process involves diapiric flow induced by density inversion, leading to an upwelling of the asthenosphere. These dynamics, superimposed onto a melted layered structure, generate the distinctive arcuate seismic reflectors found at the core of these domes. Surface geology analysis indicates that the initiation and final emplacement of these domes most likely occurred during the late Mesozoic period.

The morphology features, formation mechanism and elimination of channel segregation in industrial-scale Ti–Nb ingots produced by vacuum arc remelting

In this study, the morphology characteristics and formation mechanism of channel segregation in the industrial-sized Ti–Nb binary ingots produced by vacuum arc remelting (VAR) are researched based on experiments and calculations. The results show that the channel segregation is usually located at the 1/4–3/4 radius of the ingot and the morphology is closely related to the VAR process. The Ti-enriched channel segregation stripes tend to parallel to the ingot centerline and columnar dendrites in steady-state remelting region and hot-top region, respectively, while along the molten pool profile in residual molten pool region. For the first time, the Ti2O3 particles precipitated in the channel segregation were observed, following the orientation relationship of <001>β//<133>Ti2O3 and {11‾0}β//{011‾}Ti2O3 with β matrix in coherent boundary. First-principles calculations evident that the enrichment of Ti-solute tends to decrease the formation enthalpy, and hence makes for the precipitation of Ti2O3 particles. The numerical simulation and the experiment results manifest that the channel segregation originates from the convergence of interdendritic Ti-enriched liquid, resulting in the density inversion between the Ti-enriched initiation site and the surrounding liquid. The density gradient and the solidification rate dominate the growth direction and the radius distribution of the channel segregation. Based on the above, an optimized technique with helium cooling and the external stirring magnetic field was conducted and the channel segregation was eliminated successfully.

Nonlinear Optical Response of a Plasmonic Nanoantenna to Circularly Polarized Light: Rotation of Multipolar Charge Density and Near-Field Spin Angular Momentum Inversion.

The spin and orbital angular momentum carried by electromagnetic pulses open new perspectives to control nonlinear processes in light-matter interactions, with a wealth of potential applications. In this work, we use time-dependent density functional theory (TDDFT) to study the nonlinear optical response of a free-electron plasmonic nanowire to an intense, circularly polarized electromagnetic pulse. In contrast to the well-studied case of the linear polarization, we find that the nth harmonic optical response to circularly polarized light is determined by the multipole moment of order n of the induced nonlinear charge density that rotates around the nanowire axis at the fundamental frequency. As a consequence, the frequency conversion in the far field is suppressed, whereas electric near fields at all harmonic frequencies are induced in the proximity of the nanowire surface. These near fields are circularly polarized with handedness opposite to that of the incident pulse, thus producing an inversion of the spin angular momentum. An analytical approach based on general symmetry constraints nicely explains our numerical findings and allows for generalization of the TDDFT results. This work thus offers new insights into nonlinear optical processes in nanoscale plasmonic nanostructures that allow for the manipulation of the angular momentum of light at harmonic frequencies.

A Multi-Objective Geoacoustic Inversion of Modal-Dispersion and Waveform Envelope Data Based on Wasserstein Metric

The inversion of acoustic field data to estimate geoacoustic parameters has been a prominent research focus in the field of underwater acoustics for several decades. Modal-dispersion curves have been used to inverse seabed sound speed and density profiles, but such techniques do not account for attenuation inversion. In this study, a new approach where modal-dispersion and waveform envelope data are simultaneously inversed under a multi-objective framework is proposed. The inversion is performed using the Multi-Objective Bayesian Optimization (MOBO) method. The posterior probability densities (PPD) of the estimation results are obtained by resampling from the exploited state space using the Gibbs Sampler. In this study, the implemented MOBO approach is compared with individual inversions both from modal-dispersion curves and the waveform data. In addition, the effective use of the Wasserstein metric from optimal transport theory is explored. Then the MOBO performance is tested against two different cost functions based on the L2 norm and the Wasserstein metric, respectively. Numerical experiments are employed to evaluate the effect of different cost functions on inversion performance. It is found that the MOBO approach may have more profound advantages when applied to Wasserstein metrics. Results obtained from our study reveal that the MOBO approach exhibits reduced uncertainty in the inverse results when compared to individual inversion methods, such as modal-dispersion inversion or waveform inversion. However, it is important to note that this enhanced uncertainty reduction comes at the cost of sacrificing accuracy in certain parameters other than the sediment sound speed and attenuation.

Case Analysis of Heavy Air Pollution Process in Xi'an Using Multi-source Data

Air pollution continues to be a serious problem in Xi'an. A heavy pollution process and formation mechanism were investigated in Xi'an in January 2019 using multi-source methods (such as material balance and sulfur/nitrogen oxidation rate (SOR/NOR)). The multi-source data included the concentrations of PM2.5, PM10, SO2, NO2, CO, and O3; the chemical components of PM2.5; the meteorological records of ground and vertical observations; the atmospheric reanalysis data. Three phases were obtained including the accumulation phase (P1), maintenance phase (P2), and dispersion phase (P3) during the pollution period. The pollution event was primarily attributed to the superposition of adverse weather conditions and feedback effects. During the periods of P1 and P2, the area of Xi'an was affected by blocking and zonal westerly airflow at 500 hPa (with flat westerly airflow) and uniform-distribution pressure at sea level with a limited pressure gradient and stable weather conditions, and the easterly wind was dominant at 925 hPa; not all of these factors were conducive to the pollutant diffusion. An interaction feedback mechanism between meteorological conditions and heavy pollution could be studied using the ground-based microwave radiometer. The correlations between PM2.5 and inversions of water vapor density, relative humidity, air temperature, and temperature inversion were significant with coefficients of 0.86, 0.62, 0.53, and 0.38, respectively. The feedback mechanism was primarily manifested as follows:with the pollutant accumulation, the radiative cooling effect could lead to or strengthen the occurrence and intensity of temperature inversion, decrease the mixed layer height, and cause moisture accumulation. High humidity could further maintain the pollution by accelerating the secondary formation and promoting the hygroscopic growth of aerosol particles. Therefore, the dominant chemical components to PM2.5were secondary inorganic ions (SO42-+NO3-+NH4+, SNA) and "other" components during the period of P2, with contributions of 43.2% and 23.1%, respectively. In addition, the peak values of PM2.5, SOR, NOR, and the light extinction coefficients all occurred on the same days (January 3 and 6), indicating that the effect of secondary formation was important for both heavy pollution events and visibility. The total contribution of NH4NO3, organic matter (OM), (NH4)2SO4, and EC to the light extinction coefficient was more than 85%. Limited variations in the proportion for components were observed in three phases. During the period of P3, the strong cold air in the mid-lower atmosphere was conducive to the dry and clean air sinking and the pressure gradient at sea level increasing. These were beneficial to the diffusion of air pollutants and water vapor.

Seismic Elastic Parameter Inversion via a FCRN and GRU Hybrid Network with Multi-Task Learning

Seismic elastic parameter inversion translates seismic data into subsurface structures and physical properties of formations. Traditional model-based inversion methods have limitations in retrieving complex geological structures. In recent years, deep learning methods have emerged as preferable alternatives. Nevertheless, inverting multiple elastic parameters using neural networks individually is computationally intensive and can lead to overfitting due to a shortage of labeled data in field applications. Multi-task learning can be employed to invert elastic parameters simultaneously. In this work, a hybrid network that leverages the fully convolutional residual network (FCRN) and the gated recurrent unit network (GRU) is designed for the simultaneous inversion of P-wave velocity and density from post-stack seismic data. The FCRN efficiently extracts local information from seismic data, while the GRU captures global dependency over time. To further improve the horizontal continuity and inversion stability, we use a multi-trace to single-trace (M2S) inversion strategy. Consequently, we name our proposed method the M2S multi-task FCRN and GRU hybrid network (M2S-MFCRGRU). Through anti-noise experiments and blind well tests, M2S-MFCRGRU exhibits superior anti-noise performance and generalization ability. Comprehensive experimental inversion results also showcase the excellent lateral continuity, vertical resolution, and stability of the M2S-MFCRGRU inversion results.