Geophysical Prospecting最新文献

Several satellite gravity anomaly models are freely available to calculate the free-air gravity anomaly in areas where shipborne gravity measurements are scarce. Two models produced by the Technical University of Denmark (DTU17) and the Scripps Institution of Oceanography (SIOv32.1), respectively, were selected to compute the free-air anomalies over the Cosmonaut Sea, East Antarctica. A statistical comparison analysis was performed to evaluate the resolution of satellite gravity anomaly models by comparing them with the shipborne surveying date. The radially averaged energy spectra of free-air anomaly from different sources were calculated and compared over two selected regions to further evaluate the reliability of the data derived from satellite gravity anomaly models. The satellite gravity anomaly models have a better resolution in the ocean basin than in the area near the continental shelf. The comparison analysis revealed that the precision of both DTU17 and SIOv32.1 is close to the shipborne gravity data, but on average, SIOv32.1 is a little bit better than DTU17. The spectral analysis showed that the shipborne measurements may provide higher resolution than the satellite gravity anomaly model at wavelengths shorter than 20 km, and the free-air data derived from SIOv32.1 have better resolution than the one from DTU17. These shipborne datasets will provide contributions for the updates of the Antarctic gravity anomaly and enable new high-resolution combined Earth gravity models to be derived in Antarctica.

We develop a two-dimensional controlled-source electromagnetic inversion algorithm employing a space domain forward modelling algorithm. The space domain forward modelling algorithm is devised by imposing boundary conditions on the plane perpendicular to the strike direction that passes through the source position. The boundary conditions for various source types are derived using the symmetric/antisymmetric character of the electric and magnetic fields. The benchmarking analysis reveals that roughly eight grids are sufficient for discretizing space in the strike directions for accurate forward response computations. For inverse modelling, the inexact Gauss–Newton optimization technique is utilized. Numerical inversion experiments of synthetic and real-field data clearly demonstrate the versatility and robustness of the developed algorithm. The inversion experimentations also concur with the forward response benchmarking analysis and suggest that only a few grids (around eight) are adequate to discretize space in the strike direction. The developed algorithm is more than one order efficient compared to a wavenumber domain code.

Enhancing magnetic data is often complicated due to the non-vertical orientation of the geomagnetic field and the orientation of remanent source magnetization. The complication can be reduced by reducing the data to the pole (mathematically making the geomagnetic field vertical), but this reduction process is problematic. The analytic-signal amplitude can be used to enhance the edges of two-dimensional sources without a reduction to the pole. However, the shape of the analytic-signal amplitude is weakly dependent on the magnetization direction for grid data. This study presents an improved technique, namely the tilt angle of the analytic-signal amplitudes of the horizontal gradient of the vertical integral. This quantity is also only weakly dependent on the magnetization direction and outlines the edges as well or somewhat better than other methods. It also implicitly involves second derivatives of the magnetic field, and we use synthetic data to demonstrate that noise is not amplified as much as it is when using other edge enhancement techniques that implicitly use second derivatives. A dataset of the Apiaí Terrane, Brazil, shows good lateral continuity of features compared with other edge-enhancement methods, and subtle features like faults are easier to identify in the images generated by our new method. Upward continuation of the field, which is normally required, was not necessary to reduce the impact of noise on this field example.

Noise is inevitable when acquiring seismic data, and effective random noise attenuation is crucial for seismic data processing and interpretation. Training and inferencing two-stage deep learning-based denoising methods typically require massive noisy–clean or noisy–noisy pairs to train the network. In this paper, we propose an unsupervised seismic data denoising framework called a re-visible blind block network. It is a training-as-inferencing one-stage method and utilizes only single noisy data for denoising, thereby eliminating the effort to prepare training data pairs. First, we introduce a global masker and a corresponding mask mapper to obtain the denoised result containing all blind block information, enabling simultaneous optimization of all blind blocks via the loss function. The global masker consists of two complementary block-wise masks. It is utilized to mask noisy data to obtain two corrupted data, which are then input into the denoising network for noise attenuation. The mask mapper samples the value of blind blocks in the denoised data and projects it onto the same channel to gather the denoised results of all blind blocks together. Second, the original noisy data are incorporated into the network training process to prevent information loss, and a hybrid loss function is employed for updating the network parameters. Synthetic and field seismic data experiments demonstrate that our proposed method can protect seismic signals while suppressing random noise compared with traditional methods and several state-of-the-art unsupervised deep learning denoising techniques.

Multicomponent seismic technology utilizes the kinematic and dynamic characteristics of reflected P-waves and converted S-waves to reduce ambiguity in seismic exploration. The imaging and inversion accuracy of P-SV-converted waves are important in determining whether multicomponent seismic exploration can achieve higher exploration accuracy than conventional P-wave exploration. Pre-stack inversion of P-SV-converted waves requires precise input of P-SV-converted wave angle-domain common-image gathers. Consequently, the P-SV-converted wave angle-domain common-image gather extraction accuracy will significantly affect the P-SV-converted wave inversion accuracy. However, existing methods for extracting P-SV-converted wave angle-domain common-image gathers are constrained by issues such as the P- and S-wave crosstalk artefacts, low-frequency noises and inaccurate calculation of P-wave incident angles, leading to poor imaging accuracy. We study an angle-domain cross-correlation imaging condition and address three key issues based on this condition: the decoupling of P- and S-waves, the separation of up-going and down-going waves and the precise calculation of P-wave incident angles. Our strategies facilitate high-precision extraction of P-SV-converted wave angle-domain common-image gathers using elastic wave reverse-time migration. In this paper, first, we employ the first-order velocity-dilatation-rotation elastic wave equations to decouple P- and S-waves automatically during source and receiver wavefield extrapolations. Second, we calculate the optical flow vectors of P- and S-waves to ensure stable calculations of wave propagation directions. Based on this, we obtain up-going and down-going waves of P- and S-waves. Meanwhile, we calculate the incident angle of the source P-wave using geometric relations. Lastly, we apply the angle-domain imaging condition to achieve high-precision extraction of P-SV-converted wave angle-domain common-image gathers. Model examples demonstrate the effectiveness and advantages of the proposed method.

The gravimetric forward method is crucial in geophysical applications for a gravimetric interpretation of the Earth's inner structure. In this study, we present the gravimetric forward modelling open-source software that incorporates a graphical user interface. This software allows data preparation, manipulation and result interpretation both spatially and spectrally. For spatial domain modelling, it uses prism and tesseroid elements, whereas in the spectral domain, it extends Parker's formulas within specified boundaries. The software's utility is demonstrated through synthetic models and real-world applications, including calculating corrections for topography, sediments and consolidated crust using ETOPO1 and CRUST1.0 models. Performance comparisons show that Parker's method delivers computation speed superior to that of the prism, tesseroid and Terrain gravity forward (TGF) software, with variances ranging within ±12 mGal for $�G_z$ and ±0.3 E for $�G_{�z�z�}$ across different geological scenarios.

Experimental investigation of the elastic behaviours of lacustrine shales remains sparse, although they play an essential role in source rock evaluation, unconventional reservoir exploration and development, and the seal integrity evaluation for geological storage of CO₂ and nuclear waste disposal. We make the ultrasonic velocity measurement of 63 organic-rich shale samples (Chang 7, Qingshankou and Lucaogou formation) from three typical lacustrine basins in China. It is found that the P- and S-wave velocity of Chang 7 and Qingshankou shale corresponding to the fresh-brackish lacustrine depositional environment is mainly impacted by the clay and organic matter content, whereas their elastic anisotropic magnitude is mostly influenced by clay content. The P- and S-wave velocities of Lucaogou shale corresponding to the saline lacustrine depositional environment are mainly affected by the total organic carbon and porosity and exhibit weak anisotropy linked to organic matter enrichment. Exponential law well captures the relationship between anisotropic magnitude and velocity perpendicular to bedding for both saline and fresh-brackish water lacustrine shales, although there exists notable discrepancy, particularly at low velocities. The disparity in elasticity between laminations has a profound impact on the magnitude of elastic anisotropy and shapes the trend of velocity variations.

Marine magnetometry very close to the targeted sources, even in very deep waters, is today a reality with the advent of autonomous underwater vehicles. We argue that a successful approach is to fully integrate the magnetometer onboard the autonomous underwater vehicle and to deal with its static magnetic noise, that is induced and permanent fields of the drone, with a 3-axis vector measurement of the Earth's magnetic field. This argument is supported by results from three magnetic surveys performed with different fluxgate magnetic sensors embedded in autonomous underwater vehicles of increasing sizes. They show that simple specifically defined figures of merit coupled to an optimized scalar calibration procedure derived from aeromagnetic and satellite-borne developments produce reliable magnetic measurements from autonomous underwater vehicles for geophysical mapping or detection applications. Results are impressive and show that even weak magnetic anomalies smaller than 10 nT can be highlighted even though the magnetic signatures of autonomous underwater vehicles can be orders of magnitude higher.

We reprocessed a 50-km long legacy 2D reflection seismic profile acquired in 1986, under a project funded by the National Geophysics Program to improve the delineation of complex geological structures that host the platinum-bearing horizons (known as the UG2 reef; a chromitite horizon) on the south-eastern edge of the Western limb of the Bushveld Complex and to investigate the continuity of the reef below the thick cover. The pre-stack seismic data quality was improved through conventional processing steps. We applied standard Kirchhoff pre-stack depth migration as well as advanced coherency migration techniques. Both imaging techniques yielded good structural images of the platinum deposits, their hanging wall and footwall rocks. In particular, the coherency migration technique has provided significantly better images in complex faulted regions, yielding a better understanding of the interrelationship between fault activity and platinum deposit distribution, and the relative chronology of tectonic events. Moreover, the regional geological structures (Crocodile River fault and Chaneng structure) that crosscut the profile are clearly defined.

To meet the demand for long-distance and highly accurate detection in tunnel construction, a vibroseis source has been introduced into tunnel forward prospecting. However, serious noise in tunnels reduces the resolution of vibroseis signals, and small-scale structure recognition in tunnels requires higher signal resolution. Thus, we develop a time-frequency domain correlation method based on the synchrosqueezed wavelet transform for tunnel vibroseis data. Time-frequency domain correlation may capture more information than a single time or frequency domain correlation method, and its effectiveness depends on the time-frequency transformation method. The synchrosqueezed wavelet transform allows us to obtain high-resolution time-frequency spectra and thus helps to extract high-resolution effective signals. The advantages and disadvantages of different correlation methods are highlighted using numerical examples, in which the high resolution and strong robustness of the time-frequency domain correlation method based on the synchrosqueezed wavelet transform are demonstrated. A detailed field case study in an iron mine tunnel further demonstrates the reliability of the time-frequency domain correlation method based on the synchrosqueezed wavelet transform for practical data.