JournalTOCs

Surveys in Geophysics
Journal Prestige (SJR): 1.813

Citation Impact (citeScore): 4
Number of Followers: 3

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-0956 - ISSN (Online) 0169-3298
Published by Springer-Verlag

[2469 journals]

Fluid Discrimination Based on Inclusion-Based Method for Tight Sandstone
Reservoirs
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  Abstract: Abstract Fluid discrimination is challenging for reservoir prediction, especially for tight sandstones with special petrophysical properties. In this paper, we first review the effective medium models that are widely used in seismic exploration and a variety of inversion methods and reservoir prediction strategies in reservoir prediction. Rock physics modeling takes an important role in reservoir prediction by linking petrophysical properties and elastic parameters. We also review the theoretical implications for different rock physics models that are based on the inclusion-based method, focusing specifically on the modeling workflow for conventional sand-shale reservoirs and two models for tight sandstones. The applicability of the conventional fluid substitution equations is analyzed in detail. Then, a new inclusion-based rock physics model for tight sandstones is proposed by considering the fluid pressure ratio between cracks and stiff pores. The proposed model helps to highlight the difference between different pores and present reasonable fluid information. In the application, a detailed prediction process for fluid discrimination is given, in which the Bayes posterior prediction framework is adopted to provide the maximum posterior probability solution and its posterior probability. Field data applications demonstrate the effectiveness of the proposed method.
  PubDate: 2022-06-23
Comments on “Core Eigenmodes and Their Impact on the Earth’s
Rotation”
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  PubDate: 2022-06-07
Acknowledgement of Reviewers for 2021
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  PubDate: 2022-06-01
Passive Surface-Wave Waveform Inversion for Source-Velocity Joint Imaging
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  Abstract: Abstract Reliable dispersion measurement between two seismic stations is an essential basis of surface wave imaging. Noise source directivity has become an inescapable obstacle and a main concern for passive seismic survey: It basically breaks the principle of Green’s function retrieval in travel-time tomography; moreover, the azimuthal effect of heterogeneous ambient noise sources will inherently cause different levels of early arrival on cross-correlation functions, and the apparent velocity of surface waves can be overestimated by either multichannel slant stackings or interstation frequency–time analysis. Waveforms intrinsically contain the features of travel-time, energy and asymmetry in cross-correlation functions, and in return, they can be mapped into the causative noise sources and medium structures. Based on the theoretical framework of full waveform ambient noise inversion, we proposed a method to jointly invert noise source distributions and the corresponding unbiased surface wave velocities. The coupled dependencies of source distributions and path velocities in waveform misfit function show necessity of source–structure joint inversion. The decoupling strategy of partial derivatives is approved by the synthetic tests. Field experiments in the Hangzhou urban area further reveal the practicability of the theory. The inverted noise source models are comparable with the in situ noise distributions in urban environment, and the delineated surface wave velocities have been verified by local borehole datasets. Finally, we concluded that the developed waveform joint imaging algorithm can well relieve the dilemma of source induced velocity uncertainties.
  PubDate: 2022-06-01
Salt Tectonic Modeling Using Reverse Time Migration Imaging and
Sensitivity Kernel Wavelength Analysis
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  Abstract: It is of particular importance for structural geology, geophysical exploration and also obvious economical purposes to retrieve structures possibly hidden below salt domes. And these domes could trap hydrocarbon or gas. We thus propose a sensitivity analysis of seismic data in salt tectonic areas to identify different wavelengths associated with the geological structures under study involving salt domes. The wavelengths associated with the density or seismic velocities of the medium can give us information about the localization of shallow or deep geological structures surrounding salt domes in off-shore contexts. Seismic data can be more sensitive to density or to seismic velocities. Depending on the wavelengths associated with those two different properties, the dome shape and the different interfaces can be located and recovered at different depths. In a first approach, using velocity and density models from a salt tectonic region in the Gulf of Mexico we simulate a two-dimensional seismic data acquisition. Using these synthetic data, we aim at retrieving the salt dome shape as well as the surrounding and deepest geological layers. For this purpose, we propose to compute better imaging conditions by attenuating free surface multiples and introducing an adjoint theory-based reverse time migration (RTM) method, enhancing the limits of salt bodies and also the layers under salt structures. To obtain these imaging conditions, we compute the compressional and density sensitivity kernels \(K_\lambda\) and \(K_\rho\) using seismic sources activated separately. To attenuate the free surface multiples, the synthetic “observed” data computed with the free surface are introduced as adjoint sources and we replace the free surface condition by PML absorbing conditions in both the forward, backward and adjoint simulations needed to compute the kernels. We compare the quality of the kernels applying different strategies related to the normalization of kernels by the forward or adjoint energy, and different property parametrizations were tested to improve the imaging conditions. The specific wavelengths associated with the different (shallow to deep) interfaces are obtained using signal-to-noise ratios (SNRs) applied to both density and seismic velocity kernels. In some cases, density or seismic velocity kernels are more suited to retrieve the interfaces at different depths.
  PubDate: 2022-06-01
Crustal Thermal Structure of the Brazilian Equatorial Margin Using Fourier
and Continuous Wavelet Transforms: A Comparative Analysis Based on
Different Magnetic Datasets
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  Abstract: Abstract In this work, we calculated the Curie Point Depth (CPD) for the Brazilian Equatorial Margin using the Fourier and continuous wavelet (CWT) transforms considering a linear inversion for random and fractal magnetization models with four different magnetic datasets. After comparing our results with Curie maps reported by previous studies, we concluded that the more consistent Curie isotherm was obtained by applying the random model based on CWT to the Brazilian Equatorial Margin Magnetic Map dataset, a compilation of airborne and marine magnetic surveys complemented with magnetic anomaly data extracted from the World Digital Magnetic Anomaly Map in the deep-water oceanic domain. In addition, we estimated heat flow using CPD results and compare with a global heat flow model based on geothermal measurements. In the continental domain, Curie values range from 18 to 35 km, shallowing westwards until reaching anomalously 10 km in the Tocantins Province. In turn, the heat flow decreases eastwards from 88 to 58 mW/m2 as the Curie depth increases within the continental crust. Meanwhile, in the deep-water oceanic domain, the heat flow is overall higher (between 72 and 87 mW/m2), indicating a younger and warmer oceanic crust, whereas the Curie isotherm is shallower, varying between 10 and 30 km. Even so, it is deeper than Moho, suggesting a magnetized lithospheric mantle.
  PubDate: 2022-06-01
Long-Term Evolution of the Seismic Activity Preceding the 2015 Seismic
Crisis at Deception Island Volcano, Antarctica (2008-2015)
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  Abstract: Abstract Deception Island is an active volcano located in the South Shetland Islands, Antarctica. Although the last eruptions occurred in 1967-1970, the volcano has undergone periods of seismic unrest in 1992, 1999, and 2015. In this work, we analyze continuous seismic data obtained by a permanent station for the period 2008-2015 preceding the 2015 unrest. We identify different types of seismic signals including tectonic and volcano-tectonic (VT) earthquakes and long-period (LP) seismicity, using a combination of visual and automated techniques. The temporal evolution of the seismicity displays three differentiated stages. In Phase 1 (2008-2010) the volcano was in a dormant state characterized by a moderate level of seismicity dominated by low-energy LP seismicity, and very few VT earthquakes. In Phase 2 (2011-2014), there was a gradual increase in the level of LP events and tremor, and an acceleration of the number and energy of VT earthquakes. In Phase 3 (2014-2015) the seismicity reached a climax, with the occurrence of seismic swarms comprising thousands of earthquakes, displaying maximum activity in September-October 2014 and February 2015. We propose that the change from Phase 1 to Phase 2 was due to the recharge of magma into the plumbing system at Moho depths. The emplacement of fresh magma increased the amount of gas (and heat) permeating the volcano edifice, triggering VT earthquakes in brittle regions and favoring the occurrence of LP seismicity in the shallow hydrothermal system. During Phase 2 magma ascended through the plumbing system, as evidenced by the acceleration of the seismicity rates, the detection of thermal anomalies, and a change in the deformation pattern that for 2013-2015 corresponded to an inflation process. Finally, in Phase 3 the magma intrusion reached its shallowest point before stalling at a depth of 6-10 km. The stress perturbations propagated through crustal fluids and produced a distal VT swarm SE of Livingston, as well as proximal VT swarms and very intense LP seismicity at Deception Island.
  PubDate: 2022-06-01
3D Anisotropic P- and S-Mode Wavefields Separation in 3D Elastic
Reverse-Time Migration
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  Abstract: Abstract In 2D anisotropic media, non-stationary filters and low-rank approximation methods are classical strategies to compute the decomposition operators, but they suffer from expensive computational costs for 3D media. This study adopts the eigenform analysis into 3D vertical transverse isotropic (VTI) media and produces the separated vector P and S wavefields with the same amplitudes, phases, and physical units as the input elastic wavefields. We first built a 3D zero-order pseudo-Helmholtz decomposition operator by deriving the eigenvalues and eigenvectors of the 3D VTI wave equations in the wavenumber domain. The eigenvalues refer to the phase velocities of P-, SH-, and SV-wave, and the corresponding eigenvectors are pointing to their polarizations. Second, we use the pseudo-Helmholtz decomposition operator to construct a 3D anisotropic Poisson’s equation. Based on the laterally homogeneous assumption, Poisson’s equation is solved in the mixed domain \(z - k_{x} - k_{y}\) , where \(k_{x}\) , \(k_{y}\) , and \(z\) denote the horizontal wavenumbers and depth, respectively. Third, we obtain the vector P and S wavefields using the proposed 3D pseudo-Helmholtz decomposition operator in the space domain. Lastly, 3D PP and PS images are calculated with a dot-product imaging condition. The anisotropic amplitude versus offset (AVO) responses of the 3D elastic reverse-time migration (ERTM) images are also validated by analytical solutions (Ruger’s equations). Our proposed 3D pseudo-Helmholtz decomposition operator degrades to a gradient operator satisfying isotropic media conditions. In addition, the method is easy to extend into 3D due to its high-efficiency cost. Several numerical examples with large shear anisotropy are selected to demonstrate the feasibility of our proposed pseudo-Helmholtz decomposition method in 3D applications.
  PubDate: 2022-06-01
Impacts of Using the Rigorous Topographic Gravity Modeling Method and
Lateral Density Variation Model on Topographic Reductions and Geoid
Modeling: A Case Study in Colorado, USA
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  Abstract: Abstract Until now, the prismatic mass approximation of the topography and the constant density assumption have been mostly utilized in topographic reductions, which are rough approximations of reality and can be avoided. In this study, the more rigorous tesseroidal mass representation of topographic masses and the global lateral topographic density variation model UNB_TopoDens are considered in topographic reductions. Three tesseroidal modeling methods based on different combinations of numerical tesseroidal approaches are developed for precise topographic gravity modeling. The computational performances of the classic prismatic modeling method and new tesseroidal modeling methods in computing the residual terrain modeling (RTM), terrain correction (TC), full topographic, and Airy-Heiskanen (AH) model-based isostatic effects are tested in the Colorado area with rugged topography. In addition, the improvement of computational efficiency achieved by applying the OpenMP parallelizing technique and the contribution of considering the UNB_TopoDens model are investigated. Then, the RTM effects are applied to local geoid modeling to see the geoid model changes caused by using rigorous tesseroidal modeling methods and by considering lateral density variations. The main numerical findings are: (1) The application of the OpenMP parallelization can significantly reduce the computational time, while the efficiency improvement rate depends on the number of used threads; (2) The modeling method effect on the computation of the RTM, TC, full topographic, and AH isostatic effects is smaller than the lateral density variation effect; (3) In the case of using the RTM reduction, the use of the tesseroidal modeling method instead of the prismatic modeling method can cause geoid model differences at the millimeter level, while almost the same standard deviations are obtained by comparing the geoid models to the GSVS17 and historical GNSS-leveling data; (4) the differences in the geoid height due to lateral density variations can reach a magnitude of about 8 cm when using the RTM reduction scheme, while the validation of geoid models at the GSVS17 GNSS-leveling benchmarks revealed that the geoid considering the UNB_TopoDens model has a slightly larger standard deviation than the one using a constant density of \(2.67\;{\text{g}}/{\text{cm}}^{3}\) .
  PubDate: 2022-05-27
Seismic Characterization of Naturally Fractured Reservoirs with Monoclinic
Symmetry Induced by Horizontal and Tilted Fractures from Amplitude
Variation with Offset and Azimuth
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  Abstract: Abstract Geological and geophysical data acquired from naturally fractured hydrocarbon reservoirs usually exhibit the presence of multiple sets of fractures. Two different nonorthorhombic sets of fractures embedded in isotropic background rocks can reveal the anisotropic characteristics of monoclinic symmetry with a horizontal symmetry plane. Here, we focus on the modeling and inversion of the effective elastic properties in fractured reservoirs with monoclinic symmetry induced by a set of horizontal fractures and a set of tilted fractures with rotationally invariant properties embedded in purely isotropic host rock. To facilitate the seismic characterization of fractured reservoirs with monoclinic symmetry, we introduce two sets of fracture weakness parameters to replace the Thomsen-type anisotropic parameters and describe these two nonorthogonal sets of rotationally invariant fractures. With the incident and reflected P wave in such a monoclinic anisotropic medium, we perform the seismic characterization of two nonorthogonal sets of rotationally invariant fractures based on the reflected amplitudes variation with offset and azimuth (AVOAz). Using the linear-slip theory, we first derive the effective elastic stiffness tensor as a function of background isotropic elastic moduli, normal and shear weakness parameters of horizontal and tilted fractures, and the dip angle. We then derive the first-order perturbations in elastic stiffness tensor and formulate the linearized PP-wave reflection coefficient based on the seismic scattering theory. Next, we propose a robust AVOAz inversion approach to characterize these two nonorthogonal fractures with rotationally invariant fractures. Finally, synthetic and real data examples are used to demonstrate that the background elastic moduli and fracture properties can be reasonably estimated using the azimuthal seismic reflected amplitudes. The new formulation and inversion approach may provide us a useful tool to characterize the naturally fractured reservoirs with monoclinic symmetry induced by horizontal and tilted fractures in a more reasonable manner than previous method.
  PubDate: 2022-05-27
Seismic Shot Gather Denoising by Using a Supervised-Deep-Learning Method
with Weak Dependence on Real Noise Data: A Solution to the Lack of Real
Noise Data
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  Abstract: In recent years, supervised-deep-learning methods have shown some advantages over conventional methods in seismic data denoising, such as higher signal-to-noise ratio after denoising, complete separation of signals and noise in shared frequency bands and intelligent denoising without artificial parameter tuning. However, the lack of real noise data matched with raw seismic data has greatly limited its further application. In this paper, we take the surface seismic shot gather as an example to explore the corresponding solutions and propose a novel supervised-deep-learning method with weak dependence on real noise data based on the data augmentation of a generative adversarial network. We utilize the generative adversarial network to augment the pre-arrival noise data acquired from the shot gather itself, thereby obtaining a large amount of synthetic noise data whose probability distribution is extremely similar to that of the real noise in shot gather; the augmented synthetic noise data and sufficient synthetic signal data obtained by forward modeling together form the augmented training dataset. Meanwhile, the dilated convolution and gradual denoising strategy are adopted to construct the basic architecture of denoising convolution neural network. Finally, the above augmented dataset is used to train the network, so as to establish a nonlinear and complex mapping relationship between raw seismic data and desired signals. Both synthetic and real experiments demonstrate that our method can realize the intelligent denoising of different common-shot-point records in shot gather with the help of limited pre-arrival noise data. Article Highlights We introduce the data augmentation strategy into the field of deep-learning-based seismic denoising, thereby alleviating the dependence of supervised-deep-learning methods on real noise data We propose a novel denoising network architecture with strong recovery ability for weak desired signals by using the gradual denoising strategy and dilated convolution The augmented synthetic noise data can meet the requirement of supervised-deep-learning methods on the quantity and authenticity of training data, so this data augmentation strategy by using the Generative Adversarial Net (GAN) is a solution to the lack of real noise data
  PubDate: 2022-05-27
Guest Editorial: Special Issue on “Lithosphere Dynamics and Earthquake
Hazard Forecasting”
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  PubDate: 2022-05-18
Earthquake Genesis and Earthquake Early Warning Systems: Challenges and a
Way Forward
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  Abstract: Several natural hazards, including earthquakes, may trigger disasters and the presence of disaster drivers further lead to the massive loss of life and property, every year around the world. The earthquakes are unavoidable, as exact earthquake prediction in terms of date, and time is difficult. However, with the advancement in technology, earthquake early warning (EEW) has emerged as a life-saving guard in many earthquake-prone countries. Unlike other warning systems (where hours of warning are possible), only a few seconds of warning is possible in the EEW system, but this warning may be very helpful in saving human lives by taking the proper action. The concept of EEW relies on using the initial few seconds of information from nearby instruments, performing basic calculations, and issuing the warning to the farther areas. A dense network or enough network coverage is the backbone of an EEW system. Because of insufficient station coverage, the estimated earthquake location is error-prone, which in turn may cause problems for EEW in terms of estimating strong shaking for the affected areas. Seismic instrumentation for EEW has improved significantly in the last few years considering the station coverage, data quality, and related applications. Many countries including the USA, Mexico, Japan, Taiwan, and South Korea have developed EEW systems and are issuing a warning to the public and authorities. Several other countries, namely China, Turkey, Italy, and India are in process of developing and testing the EEW system. This article discusses the challenges and future EEW systems developed around the world along with different parameters used for EEW. Article Highlights This article aims to provide a comprehensive review related to the development The explicit emphasis is on the scientific development of EEW parameters The challenges and future scopes for the effective implementation of EEWS are discussed in terms of the correct location, the magnitude estimation, the region-specific use of ground motion prediction equations, communication technologies, and general public awareness
  PubDate: 2022-05-16
Attenuation Compensation and Anisotropy Correction in Reverse Time
Migration for Attenuating Tilted Transversely Isotropic Media
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  Abstract: Abstract The propagation of seismic waves in attenuating and anisotropic earth media is accompanied by amplitude attenuation and phase distortion. If these adverse effects are not addressed in seismic imaging, we may end up with inaccurate reflector positions, dimming amplitudes, and reduced spatial resolution in the imaging results. We use a pure pseudo-viscoacoustic TTI wave equation as a forward engine to implement Q-compensated TTI reverse time migration (RTM) because the wavefields simulated by the conventional coupled pseudo-viscoacoustic tilted transversely isotropic (TTI) wave equation contain shear wave artifacts and are unstable when the anisotropic parameters ε < δ. The high-frequency noise in the wavefield will be amplified exponentially during amplitude-compensated extrapolation, resulting in numerical instability when using Q-compensated TTI RTM. To eliminate the destabilizing effect of boosted high-frequency noise, we introduce a complex velocity that can be used to describe amplitude compensation over the limited frequency band. Then, based on this complex velocity, we derive a stable amplitude-compensated operator and apply it to the Q-compensated TTI RTM. The numerical simulation results show that, in comparison with the coupled pseudo-viscoacoustic TTI wave equation, the pure pseudo-viscoacoustic TTI wave equation is free from shear wave artifacts and is not restricted by anisotropic parameters. In addition, the pure pseudo-viscoacoustic TTI wave equation has high accuracy in describing velocity anisotropy and attenuation isotropy. Synthetic and field data examples demonstrate the effectiveness of our Q-compensated TTI RTM in compensating amplitude dissipation and correcting phase distortion.
  PubDate: 2022-05-16
Fourier Coefficients Variation with Angle for Fracture Detection and Fluid
Discrimination in Tilted Transversely Isotropic Media
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  Abstract: Fracture detection and fluid discrimination play significant roles in the field of geothermics, hydrogeology, and exploration geophysics. However, it is still a challenging task how to reliably and robustly characterize fracture and fluid distribution from seismic data. Therefore, this paper focuses on fracture detection and fluid discrimination from reflected seismic data in the saturated rock with the tilted parallel fractures. And we adopt the dry fracture weakness parameters related with the fracture density and the fluid bulk modulus mainly affected by fluid as indicators of fractures and fluid, respectively. Firstly, using the anisotropic fluid substitution equation and the linear-slip model, the analytical approximate expressions of the stiffness parameters are derived for the gas-bearing rock. Numerical examples illustrate that these approximations possess satisfactory accuracies for the case with the small dry weakness parameters and small fluid bulk modulus. Further, following the connection between the reflection coefficient and the scattering function, and coupling rock physical relationships, we derive a novel linearized PP-wave reflectivity equation parameterized only by six unknown parameters, and rewrite it in terms of the Fourier series to decouple isotropic and anisotropic components of seismic data. Based on the analysis of the contribution of each unknown parameter to the reflection coefficient, a two-step Bayesian inversion method is proposed for estimations of the shear modulus, fluid bulk modulus, porosity, dry weakness parameters, and dip angle, in which the Karhunen–Loève transform is introduced to enhance robustness of inversion. Finally, synthetic and field data are utilized to verify feasibility and stability of the proposed method. Article Highlights Reflectivity is parameterized by only six model parameters for the gas-bearing rock with tilted aligned fractures. A two-step inversion incorporating the Fourier series and Karhunen–Loève transform can increase the prediction stability. This paper may be useful for the exploration and exploitation of gas-bearing fractured tight sandstones.
  PubDate: 2022-05-05
Geophysical Well-Log Evaluation in the Era of Unconventional Hydrocarbon
Resources: A Review on Current Status and Prospects
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  Abstract: Abstract Geophysical well-log evaluation in the era of unconventional hydrocarbon resources (mainly tight oil and gas, shale oil and gas) is complicated and challenging. This review aims to fill this gap between well-log evaluation and unconventional hydrocarbon resources by characterizing the source rock property, reservoir property and engineering property using petrophysical well logs. The advanced well-log series used for unconventional oil and gas evaluation include nuclear magnetic resonance (NMR) log, image logs, array acoustic logs, elemental capture spectroscopy (ECS) and LithoScanner logs. The source rock property in terms of total organic carbon content is predicted using conventional logs and LithoScanner log. Then petrophysical parameters including porosity, permeability and oil saturation are calculated, and the appearance of natural fracture is predicted from conventional, sonic logs, image logs and NMR logs. Additionally, the reservoir property is evaluated to optimize the favorable layers with high hydrocarbon bearing property and productivity. Brittleness index as well as in situ stress direction and magnitudes are characterized by the comprehensive use of density, sonic log, ECS log and image logs. Then, the engineering property (high brittleness index but low horizontal stress difference) is evaluated to screen out the prospected layers for hydraulic fracturing. The internal relationships between the three types of properties are unraveled, and the geological and engineering sweet spots are optimized by integrating lithology, reservoir quality, hydrocarbon bearing property, source rock property, brittleness and in situ stress magnitude and direction. This multidisciplinary approach provides a comprehensive method for optimizing sweet spots in unconventional play, and will support petroleum geoscientists’ and engineers’ decisions in exploration and exploitation of unconventional hydrocarbon resources.
  PubDate: 2022-04-29
Water Resources in Africa under Global Change: Monitoring Surface Waters
from Space
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  Abstract: The African continent hosts some of the largest freshwater systems worldwide, characterized by a large distribution and variability of surface waters that play a key role in the water, energy and carbon cycles and are of major importance to the global climate and water resources. Freshwater availability in Africa has now become of major concern under the combined effect of climate change, environmental alterations and anthropogenic pressure. However, the hydrology of the African river basins remains one of the least studied worldwide and a better monitoring and understanding of the hydrological processes across the continent become fundamental. Earth Observation, that offers a cost-effective means for monitoring the terrestrial water cycle, plays a major role in supporting surface hydrology investigations. Remote sensing advances are therefore a game changer to develop comprehensive observing systems to monitor Africa’s land water and manage its water resources. Here, we review the achievements of more than three decades of advances using remote sensing to study surface waters in Africa, highlighting the current benefits and difficulties. We show how the availability of a large number of sensors and observations, coupled with models, offers new possibilities to monitor a continent with scarce gauged stations. In the context of upcoming satellite missions dedicated to surface hydrology, such as the Surface Water and Ocean Topography (SWOT), we discuss future opportunities and how the use of remote sensing could benefit scientific and societal applications, such as water resource management, flood risk prevention and environment monitoring under current global change. Article Highlights The hydrology of African surface water is of global importance, yet it remains poorly monitored and understood Comprehensive review of remote sensing and modeling advances to monitor Africa’s surface water and water resources Future opportunities with upcoming satellite missions and to translate scientific advances into societal applications
  PubDate: 2022-04-20
Revisiting Force Model Error Modeling in GRACE Gravity Field Recovery
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  Abstract: Abstract The gravity field recovery from GRACE (Gravity Recovery and Climate Experiment) mission data is contaminated by both observation noise and dynamic force errors, especially the temporal aliasing errors. To reduce their influence, four approaches are widely adopted, namely the estimation of empirical accelerations (ACC approach), the estimation of K-band range-rate parameters (KBR approach), the incorporation of the full variance–covariance matrix of observations into the least-squares adjustment (COV approach), and the time series model-based filtering (FILT approach). Essentially, the ACC and KBR approaches can be grouped into the method of functional model compensation, while the COV and FILT approaches belong to the method of stochastic model compensation. The four approaches are systematically revisited in this paper concerning their connections and differences from both theoretical perspectives and numerical simulations. Results show that all of them can significantly reduce errors in the recovered monthly gravity field models compared to the nominal approach not applying any of the four approaches. Moreover, their performances are quite consistent in the simulation case where only white observation noise is included. When both colored observation noise and temporal aliasing effects are considered, however, their performances are different. The noise reduction ratio can reach up to 87% by the ACC, COV and FILT approaches, while it is 79% in the KBR approach. The discrepancy can be explained by the compromise between noise reduction and signal absorption in the KBR approach due to the lack of constraints on empirical parameters. Moreover, in the spectral domain, ACC and KBR approaches function as high-pass filters, whereas the stochastic method, COV or FILT approach, can competently cope with colored noise in a full-spectrum manner.
  PubDate: 2022-04-19
Probabilistic Estimation of Seismically Thin-Layer Thicknesses with
Application to Evaporite Formations
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  Abstract: Abstract The identification of potassium (K) and magnesium (Mg) salts prior to the well drilling is a key factor to avoid washouts, closing pipes, fluid loss damage, and borehole collapse. The Bayesian classification combines the outcomes from statistical rock physics and seismic inversion, providing the spatial occurrence of the most-probable salt types. It serves as a facies identifier of Mg–K-rich salts (bittern salts) before drilling. Nevertheless, the most-probable classification is limited to the seismic resolution which may underestimate seismically thin-layer thicknesses. Along with the most-probable facies, the Bayesian classification renders the facies probability volume. We demonstrate that the facies probability and facies-specific total thickness highly correlate to each other even under the threshold of seismic resolution. Thus, we employ the bittern-salts probability volume to predict thin-bed bittern-salts thickness in undrilled locations. To capture the variability of the seismic estimation, we resort to Monte Carlo-assisted simulations of wells that emulate the layering patterns of a site-specific deposition environment. These simulations are crucial to assist the estimation of the joint probability density function between the facies volume and the total thickness. Therefore, given the facies probability, the joint probability density function enables us to derive the conditional expectation and percentiles of thin-bed thicknesses. Furthermore, this paper proposes a method to quantify the negative influence of seismic noise in the estimation of thin-bed thicknesses. The blind well confirms the consistency of this technique to unfold the uncertainty in the seismic predictability of thin layers. We argue that this procedure is extendable to other facies.
  PubDate: 2022-04-18
Numerical Modelling of Lithospheric Block-and-Fault Dynamics: What Did We
Learn About Large Earthquake Occurrences and Their Frequency'
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  Abstract: Abstract Dynamics of lithospheric plates resulting in localisation of tectonic stresses and their release in large earthquakes provides important information for seismic hazard assessments. Numerical modelling of the dynamics and earthquake simulations have been changing our view about occurrences of large earthquakes in a system of major regional faults and about the recurrence time of the earthquakes. Here, we overview quantitative models of tectonic stress generation and stress transfer, models of dynamic systems reproducing basic features of seismicity, and fault dynamics models. Then, we review the thirty-year efforts in the modelling of lithospheric block-and-fault dynamics, which allowed us to better understand how the blocks react to the plate motion, how stresses are localised and released in earthquakes, how rheological properties of fault zones exert influence on the earthquake dynamics, where large seismic events occur, and what is the recurrence time of these events. A few key factors influencing the earthquake sequences, clustering, and magnitude are identified including lithospheric plate driving forces, the geometry of fault zones, and their physical properties. We illustrate the effects of the key factors by analysing the block-and-fault dynamics models applied to several earthquake-prone regions, such as Carpathians, Caucasus, Tibet-Himalaya, and the Sunda arc, as well as to the global tectonic plate dynamics.
  PubDate: 2022-04-01