Geophysical Prospecting最新文献

Faults generated by seismic motion and stratigraphic lithology changes are essential research objects for seismic motion and hydrocarbon prospecting. This paper emphatically concentrates on the fault reconstruction from the existing fault probability volume. The core idea is to transform the separation of different fault sticks into a fitting and segmentation problem of point cloud data. First, we utilize the point cloud filtering algorithm to preprocess the probability volume and then complete the coarse segmentation of the fault sticks by the region growth algorithm. For the intersecting faults, we employ an enhanced random sample consensus methodology with the constraints of fault orientation and effective inliers to accomplish the detailed segmentation of different fault sticks. Finally, we take the faults identified by the region growth and the random sample consensus method as a priori to construct a random forest model to predict the fault sticks of additional data. By examining and comparing the proposed method with some other approaches with both synthetic and field data, the experimental results manifest that the novel method achieves better segmentation results than others. Moreover, the proposed method is efficient based on the fact that it can handle billions of voxels within a few minutes.

Time–frequency analysis is one of the effective methods for seismic thin-layer detection. Conventional time–frequency analysis technology for seismic thin-layer detection is interfered by the energy of adjacent frequency signals, and there is information redundancy in the frequency-domain analysis. Therefore, an S transform with improved window factor, which is based on the constrained non-negative matrix factorization, is constructed to realize seismic thin-layer detection. First, the seismic data is processed by the S transform of the improved window factor, and then we can obtain the frequency-domain information with strong time–frequency focus by changing the adjustment factor and attenuation factor in the window function. Furthermore, the key frequency of the seismic data spectrum, which can also be called the key frequency characteristic factor, can be calculated by the non-negative matrix factorization algorithm. Fortunately, the overthrust model shows a good correspondence between the key frequency characteristic factor and the thin-layer interface. The field data example shows that this approach provides a new approach for thin-layer detection.

Many studies have highlighted the superior performance of iterative solvers employing the auxiliary-space Maxwell solver preconditioner in controlled-source electromagnetic induction problems featuring isotropic conductivity. The importance of considering the presence of electrical anisotropy in controlled-source electromagnetic data has been well recognized. However, considering anisotropic conductivity will impose difficulty in robustly solving the final system of linear equations as the electrical anisotropy may significantly increase its condition number and degrade the performances of iterative solvers. Whether or not iterative solvers using the auxiliary-space Maxwell solver preconditioner have similar superior performances in the case of arbitrary electrical anisotropy is still an issue to be discussed. In this study, within the framework of finite element simulation employing unstructured tetrahedral meshes, we conduct a comprehensive examination to evaluate the performance of the flexible generalized minimum residual solver with the auxiliary-space Maxwell solver preconditioner for three-dimensional controlled-source electromagnetic forward modelling problems involving arbitrary anisotropic media. Tests on synthetic one- and three-dimensional models show that our iterative scheme performs better than widely used iterative or direct solvers for controlled-source electromagnetic anisotropy forward problems. Its convergence rate is nearly independent of working frequencies, anisotropy ratio and problem size. Finally, we applied the newly developed parallel iterative scheme to the Bay du Nord reservoir in a complicated real-life offshore hydrocarbon exploration scenario characterized by anisotropic conductivity, in which our iterative scheme with an auxiliary-space Maxwell solver preconditioner has good robustness. Furthermore, we investigated how data responses at different frequencies are sensitive to the actual hydrocarbon reservoir. Our sensitivity analysis revealed that data at large measuring offsets are considerably more sensitive to the reservoir than data at shorter measuring offsets. We also assessed the impact of neglecting anisotropy in data analysis for the realistic example and found that ignoring anisotropy can lead to noticeable changes in the data. This suggests that considering anisotropy in the interpretation of the observed data is essential to guarantee the precision of controlled-source electromagnetic field surveys.

Predicting the water abundance of coal-bearing strata is crucial for ensuring mining safety. However, owing to the dispersion and attenuation characteristics caused by pore fluid flow, it is difficult to estimate the water abundance of coal seam roof aquifers using seismic data. To overcome this challenge, we provide the relationship between the frequency-dependent seismic wave velocity and water saturation based on the Chapman fracture model and the mixing fluid model. We propose a seismic dispersion attribute technique that can use dispersion information as an indicator of water abundance. Numerical experiment results show that the water saturation of the sandstone aquifer is positively correlated with the dispersion attribute. The results of low-frequency rock physical experiments are roughly consistent with those predicted by the model for the given parameters. Using seismic dispersion attribute inversion and the frequency slice wavelet transform method, we predicted the water abundance of sandstone in the coal seam roof of the Yuwang coal mine in Yunnan Province, China. The predicted sandstone water abundance was compatible with the actual water-rich scenario observed in well logs and downhole drilling in the study area. Therefore, the method proposed herein has the potential to quantitatively determine the water abundances of sandstone aquifers in coal seam roofs.

The reflection waveform inversion is a powerful technique to build a large-scale velocity model of the subsurface by fitting the reflected recorded seismic waves. The reflection waveform inversion is designed based on the pillar concept of model and data-scale separation. Therefore, its success is related to the ability of its forward modelling engine to separate reflected events distinctly from other propagation modes (diving waves, multiples, etc.). However, the standard Born modelling based on the two-way wave equation may generate internal multiples in case of an insufficient smooth background model. These internal multiples may lead to a distorted sensitivity kernel, which adds more non-linearity to the inverse problem. In addition, simulating the wave equation using two-way propagators is still an overburden step of the algorithm especially in large three-dimensional real surveys. In this proposal, we introduce an alternative to the two-way wave equation by using a one-way approach for the reflection waveform inversion. The Born modelling based on one-way propagators significantly reduces the computational cost and I think it should be allows to relax the smooth background velocity model assumption by restricting the forward modelling to primary reflected waves. After a brief theoretical description of the one-way waveform inversion, we present an application of the algorithm on the real marine dataset to review its promises and pitfalls. Our approach produces an acceptable large-scale velocity model whose accuracy is confirmed by the migrated image and the offset gathers.

The inverted velocity model obtained from the reflection tomography based on the angle domain common-image gathers has a certain fuzziness. The inverted velocity model's stratigraphic interface is always not clear enough in areas with complex stratigraphic structure. In order to improve the accuracy and resolution of the inverted velocity model, a double-difference constraint condition is added on the basis of minimizing the absolute travel-time residual at the subsurface imaging points. This constraint makes the inverted velocity model local structure information more refined by minimizing the differential travel-time residual at adjacent imaging points (i.e. closely spaced points within the same layer) and makes the variation of velocity model information within a certain range more accurate. The method in this paper is based on angle domain common-image gathers, the tomography inversion equation is established by using the ray tracing method, and the conversion relationship between the traveltime residual and the residual curvature of the angle domain common-image gathers. Then, by adding differential constraint and double-differential constraint conditions and using the least squares QR decomposition method to solve the set of equations, the inverted velocity model can be obtained through multiple iterations, which provides a high-precision velocity field for the migration and improves the accuracy of seismic imaging. Numerical experiments on both one typical model and a field data example demonstrate the effectiveness of the proposed double-difference constrained elastic reflection tomography in generating high-precision velocity models.

The accurate identification of water-bearing structures is urgently required for the safe construction of tunnel engineering. Currently, the direct current resistivity method is an effective method for detecting water-bearing structures in tunnels. In the advanced detection of the direct current resistivity based on the finite element method, the traditional hexahedron mesh performs poorly for the discretization of models of complex tunnel structure sections such as horseshoe-shaped and round sections. Therefore, this study adopts unstructured grid generation technology combining tetrahedra and hexahedra to achieve more accurate modelling of complex structures, such as round and horseshoe-shaped sections, and establishes a forward modelling method of the direct current resistivity in tunnels based on an unstructured mesh. The maximum error between the numerical simulation and theoretical results for an infinite tabular body in full space is less than 0.8%. It is more complicated to calculate the sensitivity matrix and model constraint term for the inversion region containing two types of grid than for one. For this purpose, the sensitivity matrix of different types of grid areas is calculated, a model constraint term based on the dual constraints of volume and distance is constructed, and finally, a partitioned domain-weighted least-squares inversion method based on an unstructured mesh is proposed. Synthetic examples of typical water-bearing structures are analysed, and the results show that the proposed forward and inverse methods of the direct current resistivity in tunnels based on an unstructured mesh can effectively capture the position and morphology of the water-bearing structure. Finally, an on-site application was conducted in the Yellow River Diversion Project in central Shanxi. The proposed method could effectively identify the water body in front of the tunnel face and guide the on-site construction of the project. These results can improve the interpretation of the direct current resistivity data in tunnels and play a positive role in promoting the use of the direct current resistivity method to prevent and control water-inrush disasters in tunnels with complex structures.

Building a reliable S-wave velocity model remains challenging from P-wave land seismic data as multi-parameter elastic full waveform inversion which updates P- and S-wave velocities simultaneously is not yet widely adopted due to its computational cost, highly nonlinear nature and noise contamination from land seismic data. To overcome this challenge, we propose implementing the SH-wave full waveform inversion to obtain the S-wave velocity model. The value of this approach has been examined by applying two-dimensional time-domain SH- and P-wave acoustic full waveform inversion to a nine-component three-dimensional seismic survey acquired in the Midland Basin. The nine-component seismic survey was acquired by using both vertical and horizontal component vibrators and receivers, which enables us to apply both SH- and P-wave full waveform inversion to the raw and preprocessed shot gathers along a two-dimensional line. The SH- and P-wave full waveform inversion applied to the raw shot gathers provide more detailed P- and S-wave velocities compared to the velocities from the stacking velocity analysis. Additionally, there are no problematic artefacts in the inverted S-wave velocity model, which shows the stability of the SH-wave inversion. Through the SH-wave full waveform inversion from the preprocessed shot gathers, we reveal the lateral velocity variations in the Grayburg–San Andres interval, which coincides with the depositional environment changes suggested by the previous regional study mainly based on well log and cores. These variations demonstrate that SH-wave full waveform inversion can identify additional geological features that are not observed in the inverted P-wave velocity model. The inverted P- and SH-wave velocities are validated by the flattening of the events observed in the common image gathers after Kirchhoff depth migration. The SH-wave migration image further reveals the irregular geometries of carbonates in the Spraberry formation. V_p/V_s ratios calculated from the independently inverted P- and S-wave velocity models show strong lateral variations in the Wolfcamp interval (key-producing interval), which could be caused by the organic content variations between the reservoir and non-reservoir rocks. The inversion results demonstrate that the SH-wave full waveform inversion can be used to provide an S-wave velocity model that is comparable to the P-wave velocity model derived from acoustic full waveform inversion, which is widely used for P-wave velocity model building from P-wave land seismic data.

The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time-of-flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take-off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto-identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross-correlation method, the level threshold method and the short window-long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme-based auto-identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments.

Coalbed methane is a hot spot for gas exploration at present, and fractures are widely developed in the coals. However, despite being essential for a number of geophysical applications such as reservoir prediction and hydraulic fracturing, the influence of fractures on the elastic properties and anisotropy of coals is still poorly understood. Therefore, three groups of cylindrical coals were drilled along the face and butt cleat directions to study the effects of pressure and fracture on the elastic properties and anisotropy of tectonic coals. The velocity along the face cleat direction is less sensitive to the pressure than that along the butt cleat direction due to the difference in compliant pore and fracture content. Coals display a strong directional dependence in petrophysical and elastic properties. The permeabilities and velocities of samples along the butt cleat direction are much lower than those along the face cleat direction. The fracture densities are quantitatively characterized by the theoretical model. The values along the face cleat direction are much smaller than those along the butt cleat direction. The influence of fractures on the elastic properties and anisotropy is comprehensively studied by theoretical and laboratory methods. The mineralogy and fracture effects are important factors to the elastic anisotropy of coals, the latter can be a dominant factor to the coal elastic anisotropy. The results can contribute to the understanding of the cleat system of coalbed methane reservoir and can provide a critical rock physics basis for micro-seismic fracture monitoring and reservoir prediction.