Density Inversion Research Articles

A theoretical study of the output coupler reflectivity effect on the characteristics of Er+3 laser pulse at passively q-switching

The objective of this study deal the effect of the output coupler mirror reflectivity of laser system on behavior and characteristics (duration and energy) of erbium passive Q-switching laser pulse was studied theoretically. In the methods of the study, virtual passive Q-switching laser system consist of major elements such as erbium doped silica as an active medium, Cr+4: YAG crystal used as a saturable absorber, and the mirrors of resonator. Mathematical rate equations model has been used to describe the physical relationship between this element has been solved numerically by Rung - Kutta –Fehlberg method. The results showed regarding the pulse behavior, the increasing value of output coupler mirror reflectivity lead to decreasing of rising and falling time of pulse, so the emission of pulse occur in an advanced time. While regarding the pulse characteristics, the pulse was distinguishable by short duration and high energy, resulting high power of pulse when the output coupler mirror reflectivity increasing. Regarding of results discussion, the study attributes the results to a decrease of the initial and final population inversion density of active medium that results from the increasing value of output coupler mirror reflectivity. Therefore, it is possible to conclude in order to improve the characteristics of erbium passive Q-switching laser pulse; it is appropriate increase the value of output coupler mirror reflectivity within acceptable limits.

Deep learning-based inversion of soil and rock compaction density utilizing Falling Weight Deflectometer (FWD) and Surface Waves

Methods relying on a single dynamic parameter to estimate the material density for the compaction quality testing of earth-rock dams and roadbed projects, present certain limitations in terms of applicability, testing accuracy, and work efficiency. The theory of elastic wave propagation reveals that the compaction density of the medium results from the combined interaction of multiple material properties. This study proposes a method that utilizes the transient surface wave method and a vehicle-mounted Falling Weight Deflectometer (FWD) to jointly enhance the accuracy of soil and rock material compaction detection. The transient surface wave method is employed to extract surface wave velocity and compressional wave velocity. The analysis of the FWD signal involves extracting dynamic parameters closely related to material density, including stiffness coefficients, central frequencies, and stiffness impedances, from time-domain, frequency-domain, and mechanical impedance analyses. A fully connected deep neural network is introduced to intelligently estimate the compaction density. The deep learning model is optimized by selecting the optimal activation function and optimization algorithm, as well as additional tuning. Extensive testing shows that deep learning model produce results closely approximating the true compaction density values. The average relative errors for the wet density and the dry density are 2.9% and 2.85%, respectively, meeting the quality control requirements for density testing. The proposed approach enables rapid detection and control of the compaction quality of soil and rock materials, providing a new method for the in-situ rapid detection of compaction quality.

Prestack reservoir prediction method in ray parameter domain based on wide azimuth ocean bottom node seismic data

AbstractWide azimuth seismic data play an important role in deep reservoir prediction. According to the Paleogene clastic rock reservoir prediction, the high‐density and wide azimuth 3D seismic data acquisition of ocean bottom nodes was first carried out in a Chinese offshore oilfield in 2019. After high precision amplitude‐preserving processing, we obtained the high‐quality wide azimuth gathers. However, the research on anisotropy and reservoir prediction using wide azimuth seismic data mainly focuses on carbonate and bedrock intervals, which is not suitable for clastic rock reservoir prediction. Therefore, this paper innovatively proposes a clastic rock reservoir prediction method, which studies prestack reservoir prediction in the ray parameter domain based on wide azimuth ocean bottom node seismic data. Based on the azimuth gathers, we can obtain elastic parameters through prestack amplitude versus offset inversion, which is used to characterize the reservoir, so it is significant to obtain high precision elastic parameters in order to get highly reliable reservoir prediction results. In this paper, we develop an amplitude versus offset inversion method based on the Bayesian theory in ray parameter domain, the output of which is density, P‐wave impedance and Vp/Vs. These elastic parameters have high precision, and density data are valuable input for reservoir characterization because they are sensitive to the lithology of clastic rock reservoir at different orientations. In ray parameter domain inversion, the ray path of seismic wave propagation is considered polyline, which is more consistent with the actual situation; thus, extracted amplitudes of P gathers used in inversion are more accurate. In addition, the reflection coefficient formula in ray parameter domain has higher precision when the incident angle is large. The inversion based on the Bayesian theory can improve the stability of the inversion. Test on the actual data shows that the result of ray parameter domain inversion with a Bayesian scheme is more accurate, stable and reliable. Based on the above high precision density inversion results, an innovative wide azimuth data reservoir prediction technology based on elliptical short‐axis fitting was proposed. The actual prediction of the deep reservoir in the Bohai oilfield shows that sand thickness fitting prediction results in the short axis can best match the actual drilling sandstone thickness. The coincidence rate is 86% and the short‐axis fitting results are more in agreement with geological laws. Theoretical research and practical applications have shown that this method is feasible and effective, with high prediction accuracy, computational efficiency and strong application value.

High-Efficiency Forward Modeling of Gravitational Fields in Spherical Harmonic Domain with Application to Lunar Topography Correction

Gravity forward modeling as a basic tool has been widely used for topography correction and 3D density inversion. The source region is usually discretized into tesseroids (i.e., spherical prisms) to consider the influence of the curvature of planets in global or large-scale problems. Traditional gravity forward modeling methods in spherical coordinates, including the Taylor expansion and Gaussian–Legendre quadrature, are all based on spatial domains, which mostly have low computational efficiency. This study proposes a high-efficiency forward modeling method of gravitational fields in the spherical harmonic domain, in which the gravity anomalies and gradient tensors can be expressed as spherical harmonic synthesis forms of spherical harmonic coefficients of 3D density distribution. A homogeneous spherical shell model is used to test its effectiveness compared with traditional spatial domain methods. It demonstrates that the computational efficiency of the proposed spherical harmonic domain method is improved by four orders of magnitude with a similar level of computational accuracy compared with the optimized 3D GLQ method. The test also shows that the computational time of the proposed method is not affected by the observation height. Finally, the proposed forward method is applied to the topography correction of the Moon. The results show that the gravity response of the topography obtained with our method is close to that of the optimized 3D GLQ method and is also consistent with previous results.

Calculation of Porosity and CO2 Content in CO2-Bearing Gas Formations Based on Density and Neutron Logging Forward and Inverse Methods.

When the gas reservoir contains CO2, the logging response tends to be complex. When calculating porosity with neutron and density curves, the accuracy of porosity calculation is reduced due to the uncertainty of fluid parameters, which in turn affects the evaluation of CO2 content. It increases the uncertainty of reserve evaluation. In this paper, a forward modeling model of density logging is established based on the equivalent volume model, and the method of neutron logging is formed by putting forward the nonlinear formula of the reciprocal of the comprehensive deceleration length. The key parameters and their variation rules of neutron logging and density logging forward modeling under different temperature and pressure conditions are obtained by experimental means and Monte Carlo method, respectively. The variation law of the influence of different CO2 content on neutron logging and density logging curves is simulated. The research shows that with the increase of CO2 content, the neutron logging value of gas reservoir decreases, while the density logging value increases, and the greater the porosity of gas reservoir, the more obvious this change trend is. Compared with CH4, CO2 has a more significant impact on the excavation effect of neutron logging. On this basis, combined with the conductivity model of the study area, the porosity and CO2 content of CO2 bearing gas reservoir are solved by the least-square method. The practice shows that the relative error of porosity calculation is within ±4% and the error of CO2 content calculation is within ±10%, which proves the reliability of this method.

TECTONIC AND NON-TECTONIC MESO-STRUCTURES IN THE LISAN FORMATION AND EQUIVALENT RECENT SEDIMENTS OF THE JORDAN RIFT VALLEY-CHARACTERIZATION AND FORMATION MECHANISMS

In this study, the structural elements portrayed in the recent sediments of the Dead Sea, which became exposed at its shores due to the drop in its level are described, and the mechanisms leading to their formation are elaborated. These structures include Plumes and density inversions, subaquatic gliding, seismites, undulations and wavy structures, flexures, and overpressure structures. The formation of these structures is found to be the result of different triggering factors such as Earthquakes, tectonic activity, instability of slopes, density inversion, pore fluids overpressure resulting from gas production by biochemical processes within the sediments (sulfur bacteria reduction of sulfates and oxidation of organic matter (petroleum residues)), submarine groundwater discharge, and volume changes associated with the transformation of gypsum to basinite and anhydrite, and the reversal of that transformation. Each of these triggering factors can produce more than one type of structure, depending on the prevailing composition of the sediments, its layering attitudes, grain-size distribution, porosities, and differential pressure situations within the sediment packages. The main finding of the study is the clarification of the role of gas production within the sediments as a result of sulfur bacteria activity and of the volume change processes associated with the transformation of gypsum to anhydrite and the reversal of that transformation in the formation of the mesostructures of the Dead Sea sediments.

Robust estimation of loss‐based measures of model performance under covariate shift

AbstractWe present methods for estimating loss‐based measures of the performance of a prediction model in a target population that differs from the source population in which the model was developed, in settings where outcome and covariate data are available from the source population but only covariate data are available on a simple random sample from the target population. Prior work adjusting for differences between the two populations has used various weighting estimators with inverse odds or density ratio weights. Here, we develop more robust estimators for the target population risk (expected loss) that can be used with data‐adaptive (e.g., machine learning‐based) estimation of nuisance parameters. We examine the large‐sample properties of the estimators and evaluate finite‐sample performance in simulations. Last, we apply the methods to data from lung cancer screening using nationally representative data from the National Health and Nutrition Examination Survey (NHANES) and extend our methods to account for the complex survey design of the NHANES.

Temperature upper bound of an ideal gas

We study thermodynamics of a heat-conducting ideal gas system. The study is based on i) the first law of thermodynamics from action formulation which expects heat-dependence of energy density and ii) the existence condition of a (local) Lorentz boost between an Eckart observer and a Landau-Lifshitz observer–a condition that extends the stability criterion of thermal equilibrium. The implications of these conditions include: i) Heat contributes to the energy density through the combination q/nΘ2 where q, n, and Θ represent heat, the number density, and the temperature, respectively. ii) The energy density has a unique minimum at q=0. iii) The temperature upper bound suppresses the heat dependence of the energy density inverse quadratically. This result explains why the expected heat dependence is difficult to observe in ordinary situation thermodynamics.

Rock-physics modeling and pre-stack seismic inversion for the Cambrian superdeep dolomite reservoirs in Tarim Basin, Northwest China

The Cambrian superdeep dolomite in Tarim Basin has great resource potentialities. However, the superdeep dolomite reservoirs have the seismogeological characteristics of deep burial, low porosity and permeability, complex fracture networks and low signal-to-noise, which cannot support the efficient exploration and development of superdeep dolomite reservoir due to restricting the precision of fracture prediction. The fractures and pores compose the main storage spaces of superdeep dolomite reservoir. To better characterize the superior reservoir of superdeep dolomite with complex fracture, we first describe the properties of dolomite using core data, which illustrates that the low-porosity and low-permeability dolomite reservoirs have three tendencies: relatively higher porosity and lower permeability, relatively lower porosity and lower permeability, and relatively lower porosity and higher permeability. The development of porosity is decided by the size of dolomite particle, and when the porosity is greater, the pore type controls the permeability of the reservoir. It is difficult to effectively characterize dolomite with multiple types fractures and pores with the traditional rock physical analysis. Considering the influence of complex pore structures on the elastic parameters of superdeep dolomites, we propose a fracture characterization indicator (FCI) based on Biot theory. We test the FCI using cores and well-logging data, which can quantitatively describe the change of pores in dolomite reservoirs, much better than conventional rock-physics modeling. Meanwhile, the pre-stack seismic gather optimization process is established to employ the combination of denoising and flattening. The density indicator (DI) is proposed due to the poor result of density inversion. The priority distributions of superdeep dolomite reservoirs are revealed through the FCI and DI applied to 3D pre-stack seismic inversions. The results are consistent with those by actual drilling, which confirms that the proposed method can serve as a new way to predict superdeep dolomite reservoirs.

Zircon U[sbnd]Pb geochronology and geochemistry of hot subduction volcanic suite in the deep bore-hole well-core KBH-5: Evidence of Neoarchean Shimoga greenstone belt beneath the Cretaceous Deccan Traps, India

The continents across Earth have grown through accretion and amalgamation of plume-generated oceanic plateaux and subduction-originated magmatic arcs. The evidence of such evolutionary processes is well preserved in the greenstone belts of Canada, South Africa, China, Australia and India. Unlike accretion that leads to lateral growth of the continents, flood basalt volcanism results in the superposition of large volumes of dense mafic material above relatively less dense sialic upper continental crust. The resulting density inversion is liable to generate tectonic stresses resulting in faulting of under burden along weak planes. The nature of the crust obscured beneath flood basalt provinces that have accumulated over the past 500 My in Large Igneous Provinces (LIPs) has remained enigmatic, largely because of the voluminous lava pile that deters access to the concealed basement, unless otherwise retrieved through deep continental drilling. Here, we present in situ zircon UPb geochronology and bulk-rock geochemistry of a volcanic sequence discovered at −400 m m.s.l in the deep bore-hole well-core KBH-5 of the southwestern Deccan Traps, India. The ∼300 m thick metavolcanic succession includes a basalt – Nb-enriched basalt – andesite – Mg-andesite – dacite – adakite suite. The zircons yielded a 2.58 Ga U-Pb age for the suite, which also incorporates entrained zircon xenocrysts of 2.7 Ga age from a preexisting juvenile material during its emplacement. The bore-hole KBH-5 is located on an NNW-SSE trending normal fault, paralleling a series of major faults west of the Western Ghat Escarpment. Although the crustal block plummeted ∼1000 m downward along the fault plane, the geochemical attributes of the metavolcanic rocks are thoroughly comparable to those reported in the Medur Formation of the Shimoga greenstone belt, ∼300 km south of KBH-5 in the western Dharwar craton. Our study provides the first physical evidence of Dharwar greenstone belt(s) extending further beneath the Deccan Traps, which was previously only speculative based on short-wavelength gravity highs. The metavolcanic sequence evolved in a subduction-related back-arc tectonic regime and accreted to the active continental margin of India in the Neoarchean. Unveiling of potentially similar scenarios in cratons elsewhere entrapped beneath the vast canopy of continental flood basalts, would reveal new crustal growth events during the Archean -Proterozoic transition across the Earth.

Simulation of atmospheric density detection by spaceborne Rayleigh lidar

Atmospheric density is one of the most important elements of the atmospheric environment. The accurate acquisition of atmospheric density in the near space plays a vital role in understanding atmospheric environment changes and aerospace operations. Spaceborne lidar, as an active observation method, has the advantages of high precision and all-time detection and is a unique payload for obtaining global atmospheric density. To promote the development of a spaceborne Rayleigh lidar payload, the key parameters of the payload need to be designed and optimized, and the detection performance needs to be simulated. In this paper, based on the atmospheric model, lidar equation, and load design parameters, the performance of spaceborne Rayleigh lidar for atmospheric density detection is simulated, and the atmospheric density of the global reference altitude obtained from ERA-5 reanalysis data to conduct simulation analysis of the atmospheric density of the global near space. The results show that the detection height ranges of night and day are 30–70 km and 30–40 km, respectively, and the detection accuracy is better than 10 %. Moreover, the distribution characteristics of the atmospheric density in the global near space with the change of altitude, season, latitude, and longitude are given. Finally, the feasibility of the proposed algorithm was verified by comparing it with the atmospheric density of TIMED/SABER and NRLMSIS-00 models. It provides a reference for the development of spaceborne Rayleigh lidar and global atmospheric density inversion.

Accurate in situ rock density measurement with cosmic ray muon radiography

Muon radiography, which relies on measuring the absorption and attenuation of muons as they pass through matters, offers a new imaging technique capable of revealing the internal structure of large objects. Recent technological advancement allows for the application or testing of muon radiography in various fields, including mining, civil engineering, security check, etc. This study investigates the factors that influence muon radiography, which is used in density inversion, through simulations and experiments. The materials considered for density inversion include water, standard rock, and iron. Our simulation studies show that the number of events detected and selected has an impact on the reconstruction results, and several factors, such as multiple Coulomb scattering processes, recording time, and spatial resolution, which influence the number of muons, must be taken into account when measuring the rock density. We design and conduct a laboratory scale experiment based on the simulation results. We filter the 220 h of recording signals through time coincidence and straight-line fitting to obtain the selected events. Our results reveal that the statistical error of muons survival ratio in recording time significantly impacts the inversion result and decreases the error can improve accuracy greatly. In the experiment, the deviation between the inversion mean value and the expected value can be reduced to 2.4%–2.9% for iron, 7% for water, and 1.5% for standard rock. This density inversion approach provides insight into future density detection of underground structures.

Numerical and experimental investigation of temperature dependence vs. mobility degradation on I–V characteristics in N-LDMOS structure

The thermal behavior analysis is undoubtedly the main concern when studying semiconductor devices' and structures' physical mechanics. To the best of our knowledge, simulations studies with an experimental validation of the temperature effect vs. mobility on electrical characteristics in semiconductor devices, specifically in LDMOSFET devices are not well explored in the research literature. Considering this, this paper investigates the thermal influence vs. mobility degradation in the N-LDMOS structure and its impact on electrical performance. It also addresses the temperature impact on channel current Ids and these effects on component performance. The zero-temperature coefficient (ZTC) is evaluated in a N-LDMOS structure using numerical simulations and experimental tests. A study of the drain current behavior at ZTC (IZTC) is proposed in the linear and saturation regions. The influence of temperature mobility degradation on IZTC is analyzed. The consequences of mobility degradation show that the temperature increase gives rise to two contradictory phenomena: firstly, the channel current Ids increases when its value is lower than the current level (IZTC) and secondly, decreases when is higher. These two phenomena are studied by using simulated and experimental approaches, in order to extract and prove the physical aspects near the gate-drain access region (hot spot, electric field, electron concentration, surface carrier density, electron mobility), at the parameter evaluation origin, using SILVACO-TCAD based numerical simulation. Mobility degradation due to the temperature effect is compared to the critical value in N-LDMOS based on I–V behavior obtained with experimentation and simulations. This is explained by the role of negative thermal coefficient in LDMOS transistors. This coefficient proves to be particularly beneficial in terms of mobility gain at low inversion densities.

Inversion of electron densities in plasma wakes of hypersonic targets

Focusing on the plasma wakes of hypersonic targets (PWHT), this work provides a method for the inversion of electron densities in the PWHT by integrating electromagnetic radiation theory and three-wave coupling theory (TWCT). Utilizing the Computational Fluid Dynamics (CFD) method, taking a blunt cone as an example, the spatial distribution characteristics of electron densities in the plasma wake are simulated and analyzed in detail. The Zakharov system of equations (ZSE) is applied to the PWHT for the discussion about the electromagnetic radiation generated by plasma parametric instability. Combining the wavenumber spectrum of electromagnetic radiation and the TWCT, an inverse method of the electron densities of plasma wakes is proposed and applied to a blunt cone model. The results indicate that the inversion error rate is effectively held below 1.37 %. Furthermore, reasons for errors are elucidated through the utilization of the wavenumber spectrum structure. The proposed method may contribute to the development of hypersonic wake diagnostic techniques, and offer new insights and directions for wind tunnel experiments, shock tube experiments, as well as research on hypersonic target detection.

Fluctuation-dissipation relation in cosmic microwave background

We study the fluctuation-dissipation relation for sound waves in the cosmic microwave background (CMB), employing effective field theory (EFT) for fluctuating hydrodynamics.Treating sound waves as the linear response to thermal radiation, we establish the fluctuation-dissipation relation within a cosmological framework.While dissipation is elucidated in established linear cosmological perturbation theory, the standard Boltzmann theory overlooks the associated noise, possibly contributing to inconsistencies in Lambda Cold Dark Matter (ΛCDM) cosmology. This paper employs EFT for fluctuating hydrodynamics in cosmological perturbation theory, deriving sound wave noise.Notably, the long-time limit of the noise spectrum is independent of viscosity details, resembling a Brownian motion bounded in a harmonic potential.The net energy transfer between the sound wave system and the radiation environment reaches a balance within Hubble time, suggesting the thermal equilibrium of the sound waves themselves.The induced density power spectrum is characterized as white noise dependent on the inverse of the entropy density, which is negligibly small on the CMB scale. The energy density of the entire sound wave system scales as a -4, akin to radiation. While the numerical factor is not determined in the present calculation, the back reaction of the sound wave system to the background radiation may not be negligible, serving as a potential source for various fitting issues in ΛCDM cosmology.

Frequency Diversity Arc Array with Angle-Distance Two-Dimensional Broadening Null Steering for Sidelobe Suppression

The frequency diversity arc array (FDAA) improves the structure of the traditional frequency diversity array (FDA) from a linear array structure to an arc array structure, so that the FDAA not only has the advantages of the FDA but also has a large angle and omnidirectional scanning capability. However, when it is equivalent to a linear array, this arc-shaped structure will lead to the phenomenon of inverse density weighting, which leads to a higher sidelobe level of the FDAA beam pattern. In order to solve the problem of a high sidelobe level at a certain position of the FDAA, a frequency diversity arc array with angle-distance two-dimensional broadening null steering is proposed for sidelobe suppression. Using a structural model of the FDAA, the problem of the high sidelobe was analyzed. The linear constrained minimum variance (LCMV) method was used to generate a null with a certain width at the position of the fixed strong sidelobe level in the angle domain and the distance domain of the FDAA beam pattern, to reduce the FDAA sidelobe level. Then, the angle domain and distance domain fixed positions of the FDAA were simulated to generate the null beam pattern. The simulation results verified the effectiveness of this method for reducing the sidelobe level.

Forward and Inverse Energy Cascade in Fluid Turbulence Adhere to Kolmogorov's Refined Similarity Hypothesis.

We study fluctuations of the local energy cascade rate Φ_{ℓ} in turbulent flows at scales (ℓ) in the inertial range. According to the Kolmogorov refined similarity hypothesis (KRSH), relevant statistical properties of Φ_{ℓ} should depend on ε_{ℓ}, the viscous dissipation rate locally averaged over a sphere of size ℓ, rather than on the global average dissipation. However, the validity of KRSH applied to Φ_{ℓ} has not yet been tested from data. Conditional averages such as ⟨Φ_{ℓ}|ε_{ℓ}⟩ as well as of higher-order moments are measured from direct numerical simulations data, and results clearly adhere to the predictions from KRSH. Remarkably, the same is true when considering forward (Φ_{ℓ}>0) and inverse (Φ_{ℓ}<0) cascade events separately. Measured ratios of forward and inverse cascade probability densities conditioned on ε_{ℓ} also confirm the applicability of the KRSH to analysis of the fluctuation relation from nonequilibrium thermodynamics.

Joint data and model-driven simultaneous inversion of velocity and density

SUMMARY Density is an important parameter for both geological research and geophysical exploration. However, for model-driven seismic inversion methods, high-fidelity density inversion is challenging due to seismic wave traveltime insensitivity to density and crosstalk that density has with velocity. To circumvent the challenge of density inversion, some inversion methods treat density as a constant value or derive density from velocity through empirical equation. On the other hand, deep learning approaches are completely driven by data and have strong target-oriented characteristics, offering a new way to solve multiparameter coupling problems. Nevertheless, the accuracy of the inversion results of data-driven algorithms is directly related to the amount and diversity of the training data, and thus, they lack the universality of model-driven algorithms. To achieve accurate density inversion, we propose a simultaneous inversion algorithm for velocity and density that combines the advantages of data- and model- driven approaches: A neural network model (U-T), combining the U-net and Transformer architectures, is proposed to construct non-linear mappings between seismic data as inputs and the velocity and density as predictions. Next, the model-driven inversion algorithm uses the U-T prediction as the initial model to obtain the final accurate solution. In the model-driven module, envelope-based sparse constrained deconvolution is used to obtain full-band seismic data, while a variable dominant frequency full waveform inversion algorithm is used to perform multiscale inversion, ultimately leading to accurate inversion results of velocity and density. The performance of the algorithm on the Sigsbee2A and Marmousi models demonstrates its effectiveness.

Tidal, density and wind-driven subtidal circulation in a hypersaline coastal lagoon

Subtidal circulation patterns were studied along an elongated hypersaline system. Month-long data were collected using three acoustic Doppler current profilers. These profilers were moored at depths of around 15 m in three locations: 10 km inland from the mouth of the lagoon, within the central region, and near the head of the lagoon. The variability of temporal and spatial subtidal circulation was explored using Empirical Orthogonal Functions analysis, which explained 93% of the variability through the first three modes. The first mode was influenced by tidal advection, resulting in a tidally-driven residual circulation for elongated channels, with inflows occurring over the shoals and outflows in the deeper channel sections. During the neap-tide cycle, inverse density gradients became relevant, coinciding with the peaks of mode 2 amplitude that accounted for 15% of the total variability. The gravitational circulation exhibited its highest intensity near the head, characterized by a vertically sheared flow with inflow occurring near the surface and outflow underneath. Predominant onshore wind stresses had a significant impact on the subtidal circulation and displayed a strong correlation with the mode 3 amplitude, explaining 11% of the total variability. Wind-driven circulation exhibited a vertically sheared profile, characterized by downwind near-surface flow and upwind flow underneath in the lagoon mouth and head, and a homogeneous downwind profile in the central part of the lagoon. It is concluded that tidal stresses governed the subtidal circulation, followed by density gradients, and wind stresses modified spatial circulation patterns induced by tides and density gradients. This research provides new observational evidence on tidal residuals in long channels and contributes to the understanding of the interactions between the main subtidal circulation drivers in hypersaline lagoons.

Wasserstein distance-based full waveform inversion method for density reconstruction

Reliable density information is an essential factor in lithologic interpretation and reservoir evaluation. However, density reconstruction is hampered by a lack of long-wavelength information and the crosstalk between different parameters. The powerful nonlinearity in density inversion constrains the multi-parameter full waveform inversion application. This paper introduces the Wasserstein distance into the full waveform inversion for velocity and density based on the optimal transport theory. We construct an objective function with better convexity to avoid the cycle-skipping caused by the poor initial model. Furthermore, due to the sensitivity of the quadratic Wasserstein distance to low-frequency, we add the low-wavenumber component absent in the conventional density inversion. We acquire a long-wavelength density background using optimal transport inversion and then apply it as an initial model for least-squares inversion. Numerical examples show that our optimal transport inversion effectively builds a reasonable density background model for FWI. Density inversion can be improved by incorporating optimal transport and least-squares theory, leading to a reliable quantitative description for petroleum exploration and development.