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Sedimentary basins, integral to Earth's geological history and energy resource exploration, undergo complex changes driven by sedimentation, subsidence and geological processes. Gravity anomaly inversion is a crucial technique offering insights into subsurface structures and density variations. Our study addresses the challenge of complex subsurface structure assessment by leveraging deep neural networks to invert observed gravity anomalies. Optimization approaches traditionally incorporate known density distributions obtained from borehole data or geological logging for inverting basement depth in sedimentary basins using observed gravity anomalies. Our study explores the application of deep neural networks in accurate architectural assessment of sedimentary basins and demonstrates their significance in mineral and hydrocarbon exploration. Recent years have witnessed a surge in the use of machine learning in geophysics, with deep learning models playing a pivotal role. Integrating deep neural networks, such as the feedforward neural networks, has revolutionized subsurface density distribution and basement depth estimation. This study introduces a deep neural network specifically tailored for inverting observed gravity anomalies to estimate two‐dimensional basement relief topographies in sedimentary basins. To enhance computational efficiency, a one‐dimensional discrete cosine transform based discretization approach is employed. Synthetic data, generated using non‐Gaussian fractals, compensates for the scarcity of true datasets for training the deep neural network model. The algorithm's robustness is validated through noise introduction with comparisons against an efficient and traditional global optimization‐based approach. Gravity anomalies of real sedimentary basins further validate the algorithm's efficacy, establishing it as a promising methodology for accurate and efficient subsurface imaging in geological exploration. [ABSTRACT FROM AUTHOR]

This study aims to improve the accuracy of bathymetry predicted by gravity-geologic method (GGM) using the optimal machine learning model selected from machine learning techniques. In this study, several machine learning techniques were utilized to determine the optimal model from the performance of depth and gravity anomalies. In addition, a tuning density contrast calculated from satellite altimetry-derived free-air gravity anomalies (FAGAs) was applied to estimate enhanced bathymetry. By comparison with shipborne depth, the accuracy of the bathymetry estimated by using satellite altimetry-derived FAGAs and machine learning was evaluated. The findings reveal that the bathymetry predicted by the optimal machine learning using the Gaussian process regression and the GGM with a tuning density contrast can enhance the accuracy of 82.64 m, showing an improvement of 67.40% in the RMSE at shipborne depth measurements. Although the tuning density is larger than 1.67 g/cm3, bathymetry using satellite altimetry-derived FAGAs and machine learning can be effectively improved with higher accuracy. [ABSTRACT FROM AUTHOR]

This study aims to improve the accuracy of bathymetry predicted by gravity-geologic method (GGM) using the optimal machine learning model selected from machine learning techniques. In this study, several machine learning techniques were utilized to determine the optimal model from the performance of depth and gravity anomalies. In addition, a tuning density contrast calculated from satellite altimetry-derived free-air gravity anomalies (FAGAs) was applied to estimate enhanced bathymetry. By comparison with shipborne depth, the accuracy of the bathymetry estimated by using satellite altimetry-derived FAGAs and machine learning was evaluated. The findings reveal that the bathymetry predicted by the optimal machine learning using the Gaussian process regression and the GGM with a tuning density contrast can enhance the accuracy of 82.64 m, showing an improvement of 67.40% in the RMSE at shipborne depth measurements. Although the tuning density is larger than 1.67 g/cm3, bathymetry using satellite altimetry-derived FAGAs and machine learning can be effectively improved with higher accuracy.

For the first time, HY-2A/GM-derived gravity anomalies determined with the least-squares collocation method and ship-borne bathymetry released from the National Centers for Environmental Information (NCEI) are used to predict bathymetry with the gravity-geologic method (GGM) over three test areas located in the South China Sea (105–122°E, 2–26°N). The iterative method is used to determine density contrasts (1.4, 1.5, and 1.6 g/cm3) between seawater and ocean bottom topography, improving the accuracy of GGM bathymetry. The results show that GGM bathymetry is the closest to ship-borne bathymetry at check points, followed by SRTM15+V2.0 model and GEBCO 2020 model. It is found that in a certain range, the relative accuracy of GGM bathymetry tends to improve with the increase of depth. Different geological structures affect the accuracy of GGM bathymetry. In addition, the influences of gravity anomalies and data processing method on GGM bathymetry are analyzed. Our assessment result suggests that GGM can be widely applied to bathymetry prediction and that HY-2A/GM-derived gravity data are feasible with good results in calculating ocean depth.

Marine gravity data from altimetry satellites are often used to derive bathymetry; however, the seafloor density contrast must be known. Therefore, if the ocean water depths are known, the density contrast can be derived. This study experimented the total least squares algorithm to derive seafloor density contrast using satellite derived gravity and shipborne depth observations. Numerical tests are conducted in a local area of the Atlantic Ocean, i.e., 34°∼32°W, 3.5°∼4.5°N, and the derived results are compared with CRUST1.0 values. The results show that large differences exist if the gravity and shipborne depth data are used directly, with mean difference exceeding 0.4 g/cm3. However, with a band-pass filtering applied to the gravity and shipborne depths to ensure a high correlation between the two data sets, the differences between the derived results and those of CRUST1.0 are reduced largely and the mean difference is smaller than 0.12 g/cm3. Since the spatial resolution of CRUST1.0 is not high and in many ocean areas the shipborne depths and gravity anomalies are much denser, the method of this study can be an alternative method for providing seafloor density variation information.

Quantifying the density contrasts of the Earth's inner core boundary (ICB) is crucial to understand core-mantle coupling and the generation of the geodynamo. The PKiKP/PcP amplitude ratio is commonly used to obtain the density contrast at the ICB, but its applications are limited by scattered observed data. In this study, we selected the PKiKP and PcP phases reflected at the same region of inner-core and core-mantle boundaries beneath Northeast Asia from different earthquakes for the first time, and the observations suggested that the PKiKP/PcP amplitude ratio is widely scattered. We also compared the PKiKP and PcP amplitudes, which demonstrated that the scatter cannot be attributed only to ICB anomalies but might also arise from raypath differences and heterogeneities throughout the crust and mantle. By fitting the observed PKiKP/PcP amplitude ratio, we obtained a density contrast of approximately 0.65 g cm−3 and a compressional velocity contrast of approximately 0.87 km s−1 at the ICB beneath Northeast Asia. The larger contrast values indicate the possible occurrence of local crystallization occurring at the inner core surface. [ABSTRACT FROM AUTHOR]

Predicting the instabilities that occur during the chemical reaction between a percolating fluid and a soluble rock leading to the development of macroscopic channels called wormholes is a key for understanding many geological processes. Their shape and their spatial distribution depend on two dimensionless numbers, namely Damköhler (Da) and Péclet (Pe) numbers. Although the dissolution phenomenon has been extensively studied both in the context of acid stimulation of oil wells in carbonate rocks and carbon capture and storage, few works have focused on the influence of the physical properties of fluids on wormhole patterns. Consequently, through interpretation of images acquired during the injection of pure water into a 2‐D reconstituted salt massif and considering different configurations of injection, we illustrate the buoyancy effects on wormhole formation. Contrarily to observation in fractures, experimental results suggest that dissolution regimes can still be described by the classical dimensionless numbers Da and Pe. As for the regime diagram, it remains practically unchanged for strong Péclet and weak Damköhler and undergoes a slowdown of the propagation of the dissolution front when the number of Richardson's increases. Analysis of morphological descriptors such as area, interface, and tortuosity shows that density contrast has an influence on intermediate‐ to high‐Richardson dissolution regimes that may be explained by the existence of buoyancy effects. Key Points: Use of a laboratory physical model and morphological descriptors to study the influence of density contrast on dissolution regimesNo additional pattern was observed but displacement of transition between patterns toward higher Péclet/lower Damköhler induced by buoyancyA modification of interface morphology, with larger roughness, has been highlighted for high Richardson number [ABSTRACT FROM AUTHOR]

With respect to the importance of a multiphase flow behaviour in a microchannel, this study is focused on developing a numerical modelling of two-phase flows using lattice Boltzmann method (LBM). This method utilizes a different vision for surveying the behaviour of fluids. The LBM be able to capture fluid motion via a microscopic vision in contrary to classical CFD methods (Navier–Stokes approach). Based on this capability, the LBM is a powerful method for solving complex problems in multiphase and multicomponent fluid dynamics problems. This research attempts to employ the chromo-dynamic model, which is compatible for high-density ratio flow in a microchannel and introduces different approaches to achieve this objective. This study examined both Huang and Lishchuk methods and the obtained results show a sharp interface between two phases by using Haung model. However, utilization of this method can impose some difficulties on stability of calculation. The research tries to eliminate or at least weaken numerical errors caused by density contrast in the interface of different phases from the exertion of an artificial force. A numerical modelling approach comprises an accurate treatment of the surface tension between phases and a passive-scalar heat transfer method. This research used a high-performance simulation to obtain real-time flow visualizations. The proposed method is applied to a new geometry with variable cross section. A correlation introduced between this geometry and dimensionless numbers (Bejan number, Laplace number, Reynolds number). This new correlation defines an operational criterion for a step-contracted microchannel and enables us to capture the delay time between fluctuations. The results are compared to available exact solutions for high-density ratio flow in a microchannel. [ABSTRACT FROM AUTHOR]

We utilized a high-resolution tailored gravity dataset to investigate the geological structure beneath the Southern Benue Trough of Nigeria and along the Cameroon Volcanic Line (CVL). The tailored gravity data was obtained by applying a stochastic combination technique to integrate global gravity field model, terrestrial gravity data, and residual gravity data over the study area. We then carried out gravity techniques to compile the Bouguer gravity map and to estimate the crustal thickness. To obtain suitable estimates of the reference depth and density contrast of the Moho interface, we fitted the gravimetrically determined Moho geometry to the seismic estimates by minimizing the Root-Mean-Square of their differences. A minimum RMS of 3.6 km at a reference depth of 26 km and a density contrast of 450 kgm−3 was achieved over the study area. Our results reveal a dense magmatic feature criss-crossing the central portion of the study area. This phenomenon led to a thinning of the crust and formation of various geological structures, mainly at the southern end. We could see a very thick sedimentary cover within some of these structures possibly occasioned by compressional and extensional tectonic forces acting at the southwest end. Our study reveals that these compacted sedimentary covers could be important habitats for mineralization. We have also been able to refine and depict the lateral extent of the crustal architecture at a fine scale using our tailored gravity dataset. We concluded that the tectonic events beneath the study area are complex and point to several geophysical factors earlier revealed in published studies. However, a narrowing of two or more conjugate plates (margins) propelled by an upward force may have primarily led to the upward displacement of some of the magmas in-between those plates forming the intrusive rocks. • Dense magmatic feature criss-crossing and forming intrusive rocks in the study area. • Crustal thickening beneath the CVL resulting from the uplift of crustal roots. • Upward displacement of magmas caused by narrowing of conjugate plates. • Refinement of the lateral extent of the lithospheric architecture at a fine scale. • Important habitat for different mineral resources revealed in our compiled maps. [ABSTRACT FROM AUTHOR]

Abstract High-resolution X-ray tomography was used to observe a partially hydrated geosynthetic clay liner (GCL) specimen to gain a better understanding of the interaction of its compnents (i.e., geotextiles, fibres and bentonite) on partial hydration when deployed as part of a composite liner system. Detailed in-situ studies of hydration processes in GCLs has proven difficult despite more than two decades of effort. X-ray tomographs were collected at spatial resolutions of 12 and 7 μm to identify the different components within a GCL, as well as to examine in finer detail their interaction within the GCL after initial partial hydration. Tomograph projections provided an excellent aspect of the interaction of these components and some concepts, such as the presence of shearing features within the bentonite component, may require re-consideration based on evidence from X-ray tomography. [ABSTRACT FROM AUTHOR]

How to decide a proper scale parameter is still an issue to deal with. In this paper, we propose an adaptive spectral clustering algorithm based on weighted density(WDSC), which solves the sensitivity of the scale parameter in the similarity matrix made from Gaussian kernels. It takes weighted K nearest neighbor distance of each data as the scale parameter, and the reciprocal of the scale parameter as its density. It also brings in a new density contrast to adjust the similarity matrix. It takes the neighbor distribution of each data into consideration, so it is robust to outliers and insensitive to scale parameters. Experiments on different datasets and comparative experiments demonstrate the effectiveness and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Knowledge of isostasy provides insights into how excess (or deficit) of mass on and within the lithosphere is maintained over different time scales, and also helps decipher the vertical dynamics. In continental regions, isostasy is primarily manifested as a crustal root, the extent of which is defined by the lithospheric strength and the density contrast at the Moho. In this study, we briefly review the methodology for extracting the density contrast across the Moho using the amplitudes of the P-to-s converted and free-surface reverberating phases in a receiver function (RF). We test the efficacy of this technique by applying it on synthetic and real data from 10 broadband seismic stations sited on diverse tectonic provinces in the Indian shield. We determine the density contrast after parameterizing the shear-wave velocity structure beneath the stations using the nearest neighbourhood algorithm. We find considerable variation in the density contrast across the Moho beneath the stations (0.4–0.65 gm/cc). This is explained in terms of isostatic compensation, incorporating the existing estimates of lithospheric strength (Te). Crustal roots computed using the estimated Te and the deduced density contrast substantiate the crustal thickness values inferred through RF analysis, and vice versa. This illustrates isostasy as a combination of variation in density contrast and Te. The density contrasts and crustal thicknesses inferred from RF analysis explain well the isostatic compensation mechanism in different regions. However, unusually large density contrasts (∼0.6 gm/cc) corresponding to elevated regions are intriguing and warrant further investigations. Our observation of varied density contrasts at the Moho in a Precambrian continental setting is interesting and raises a question about the existence of such situations in other parts of the world. [ABSTRACT FROM AUTHOR]

Geological granular flows are highly complex, gravity-driven phenomena whose different behaviors depend on the mechanical properties, density and granulometric distributions of the constituent materials. Years of research have produced significant advances in understanding transport and deposition processes in granular flows. However, the role and effects of clast densities and density contrast in a granular flow are still not fully understood. In this paper we show the effect that pumice has on dry granular flows; specifically on flow velocity and longitudinal segregation of the deposits. Our work confirms, by experimental results, field observations on pumice/lithic segregation and longer pumice runout. We report results of velocity decay and deposit architecture for a granular flow passing over a break in slope (from 38° to 4° inclination). The 30 experimental runs were carried out in a five-meter long laboratory flume equipped with a series of sensors that include laser gates and high-speed cameras (400 fps). We used two polydisperse mixtures of dacitic lithics and rhyolitic pumice in varying amounts, with Weibull and Gaussian particle size distributions. The pumice/lithic ratio changes the flow response passing over a break in slope. This effect is particularly evident starting from 10% of pumice volume into the flow mixture, independently of its granulometric distribution. Runout relates to mass following a power law, with an exponent close 0.2. The experiments confirm that pumice segregation affects polydispersed mixtures, similarly to what has been observed in real field deposits, where density decoupling produces lithic-enriched proximal areas and pumice-enriched distal areas. The results obtained prove that the presence of low-density materials in a dense granular flow has a strong influence on its behavior. [ABSTRACT FROM AUTHOR]