Crustal structure and variation in the southwest continental margin of the South China Sea: Evidence from a wide-angle seismic profile

Wei, Xiaodong; Ruan, Aiguo; Ding, Weiwei; Wu, Zhaocai; Dong, Chao; Zhao, Yanghui; Niu, Xiongwei; Zhang, Jie

doi:10.1016/j.jseaes.2020.104557

Cited by 12 publications

(7 citation statements)

References 60 publications

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“…After gravity stripping, the gravity anomaly caused by the Moho is shown in Figure 11d, and the mean Moho depth ( z 0 = 24.63 km) is estimated from seismic Moho depth control points (colored geometries in Figure 9) (Hung et al., 2021; Wei et al., 2020), which can also be applied as a reference for comparison between the Moho models and seismic measurements obtained from previous geological studies of the SCS.…”

Section: Resultsmentioning

confidence: 99%

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm

Rao,

Yu,

Chen

et al. 2023

Earth and Space Science

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The Moho is the interface between crust and mantle, and accurate location of the Moho is important for both resource exploration and deep earth condition and structural change investigations. The theory of the traditional Parker‐Oldenburg (P‐O) method is quite simple and it is widely applied in the frequency domain of Moho depth inversion. However, Moho fluctuation simulations using the P‐O method are not reliable because of the lack of field geographic data constraints during the inversion process and the excessively smoothing of data details caused by using filters to correct the source data signals. To solve those problems, we propose an improved iteration P‐O method with a variable density contrast model, the iterative process is constrained by geological data in the inversion parameters, and the variable depth of the gravity interface is iterated using an equivalent form of upward continuation in the Fourier domain, which is more stable and convergent than downward continuation term in original P‐O method. Synthetic experiments indicate that improved method has the better consistency among the simulations than original method, and our improved method has the smallest root mean square (RMS) of 0.59 km. In a real case, we employed the improved method to invert for the Moho depth of the South China Sea (SCS), and the RMS between our Moho depth model and the seismological data is the smallest value of 2.27 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient.

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Section: Resultsmentioning

confidence: 99%

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm

Rao,

Yu,

Chen

et al. 2023

Earth and Space Science

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“…Ultimately, this integration can lead to an improvement of seismic interpretation. [34]). The star indicates the position of the seismic source.…”

Section: Dense-wide Aperture Acquisitionmentioning

confidence: 99%

Seismic Exploration Methods for Structural Studies and for Active Fault Characterization: A Review

Bruno

2023

Applied Sciences

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In this paper, seismic exploration methods are reviewed with a particular emphasis on the use of the reflection seismology to investigate the subsurface structures and characterize active faults. The paper provides a descriptive overview, intended for a non-specialist audience, of the methods and of their recent developments aimed at improving the resolution, accuracy, and computational efficiency of seismic imaging. Techniques such as seismic ray tomography, full-waveform inversion and pre-stack depth migration are briefly introduced, highlighting their potential applications in structural geology studies. The main seismic attributes that have become increasingly important in the interpretation of faults and fractures are also presented, along with some examples of application. Finally, some case studies of active fault characterization are discussed. From these examples, the crucial role played nowadays by the seismic exploration methods for structural studies and for active fault characterization is evident.

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“…The seismic Moho depth data in the South China Sea are extracted from Z.-C. Wu et al (2017), Wei et al (2020), andHung et al (2021). The Earth2014 topographic model (Hirt & Rexer, 2015) used to create the Airy model can be downloaded from https://ddfe.curtin.edu.au/models/Earth2014/data_5min/topo_grids/.…”

Section: Data Availability Statementmentioning

confidence: 99%

“…As shown in Figures 10a and 10b, we utilized the seismic Moho depth control points (Wei et al, 2020;Hung et al, 2021) and the sediments-free gravity disturbance to estimate the mean Moho depth ( 𝐴𝐴 𝐴𝐴0 = 22.97 km) and the initial Moho density contrast ( 𝐴𝐴 𝐴 𝐴𝐴0 = 0.4015 g∕cm 3 ). The distribution of the 296 control points is depicted in Figure 8.…”

Section: Moho Model For the Scsmentioning

confidence: 99%

“…As shown in Figures 10a and 10b, we utilized the seismic Moho depth control points (Wei et al., 2020; Z.‐C. Wu et al., 2017; Hung et al., 2021) and the sediments‐free gravity disturbance to estimate the mean Moho depth (

{z}_{0}

= 22.97 km) and the initial Moho density contrast (

{\hat{\rho }}_{0}\,=\,0.4015\,\mathrm{g}/{\text{cm}}^{3}

).…”

Section: The Scs Casesmentioning

confidence: 99%

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An Improved Method to Moho Depth Recovery From Gravity Disturbance and Its Application in the South China Sea

Chen

2022

JGR Solid Earth

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The Mohorovĩcíc discontinuity (Moho) is the boundary between the Earth's crust and upper mantle. It is critical to determine accurate Moho depth for gaining insight into the deep structure of the Earth, material and energy exchange processes, and geodynamic problems (Ebbing et al., 2018;Gozzard et al., 2019;Xu et al., 2017). Currently, the seismic and gravimetric methods are the primary geophysical methods for determining the depth of Moho. Seismic methods are quite expensive, and seismic stations are sparse in many regions with extreme conditions (e.g., ocean, plateau, and polar). In addition, seismic methods could be ineffective for recovering three-dimensional (3D) Moho topography across vast regions. Along with seismic surveys, gravity observations can also be used to estimate the Moho depth. In recent decades, as satellite-gravity missions, the Gravity Recovery and Climate Experiment (GRACE) (Tapley et al., 2004), the Gravity field and steady-state Ocean Circulation Explorer (GOCE) (Floberghagen et al., 2011), GRACE Follow-On (GRACE-FO) (Kornfeld et al., 2019), and satellite altimetry (Sandwell et al., 2014) have advanced, it is now possible to obtain high resolution and accurate gravity data with almost global and homogeneous coverage. At the moment, several global gravity field models (GGMs) have been constructed with high accuracy and resolution by combining terrestrial, altimetric, and satellite gravity data, such as EGM2008 (Pavlis et al., 2012), EIGEN-6C4 (Förste et al., 2014), and XGM2019e_2159 (Zingerle et al., 2020. These GGMs with maximum degree/order of 2190 (Spatial resolution ∼10 km) have been

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Crustal structure and variation in the southwest continental margin of the South China Sea: Evidence from a wide-angle seismic profile

Cited by 12 publications

References 60 publications

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm

Seismic Exploration Methods for Structural Studies and for Active Fault Characterization: A Review

An Improved Method to Moho Depth Recovery From Gravity Disturbance and Its Application in the South China Sea

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