Geophysical Prospecting最新文献

The brittleness of a caprock layer is an important property to measure, as it influences sealing integrity for subsurface fluid injection projects. However, brittleness is a complex function of various factors, such as mineral composition, diagenesis and effective stress, and consequently can vary spatially. Because well log-based methods for brittleness estimation are often spatially limited, we develop a simple workflow to estimate the brittleness of a shale formation directly from seismic data. The shale in question is the Draupne Formation of the Upper Jurassic age, which acts as a primary seal of Viking Group sandstones in the Horda Platform area of the northern North Sea for hydrocarbon extraction (e.g., the Troll field) and geological CO₂ storage (e.g., Smeaheia). First, well log data from 26 wells in the Horda Platform area is aggregated, focusing on the compressional sonic, bulk density and resistivity values of the Draupne Formation. This data are used to establish a linear model relating the acoustic impedance and elastic properties-estimated brittleness index (BI) of the Draupne Formation; these two quantities display a correlation of 0.86. By combining this acoustic impedance information with a wavelet extracted from field seismic data and using average acoustic properties for the relatively homogeneous underlying sandstone reservoir, synthetic seismograms corresponding to different BI values of the Draupne Formation are generated. The amplitudes extracted from the synthetic seismograms are then used to establish a quadratic model relating seismic amplitudes at the base Draupne reflection with the BI. Applying this quadratic model on a 2D seismic line from the Stord Basin (south of the Horda Platform) results in BI values that are close to elastic-properties-based values at wells which intersect the seismic line and an expected trend of increasing brittleness with respect to depth. This integrated method can be used as part of a workflow to characterize top seal effectiveness, which may be useful in fluid storage prospect evaluation.

Image-domain least-squares migration (IDLSM), which typically employs a diagonally dominant Hessian with narrow bandwidth for the inverse problem, provides an efficient deconvolution strategy for subsurface reflectivity imaging. Conventional methods often rely on the adjoint of the Born/Kirchhoff modelling operator to compute the Hessian matrix. However, the adjoint-derived Hessian is highly ill-conditioned, leading to slow convergence during linear inversion and resulting in images with undesired resolution and amplitude fidelity. To overcome these limitations, this study introduces a novel IDLSM approach that integrates the state-of-the-art migration operator. We derive and compute the preconditioned Hessian matrix through a Kirchhoff migration engine with source-side and receiver-side illumination. The preconditioned Hessian matrix exhibits identical values along its main diagonal. This illumination compensation will explicitly reduce the condition number of the Hessian matrix and significantly improve the quality of migrated images in terms of amplitude fidelity. In addition, we remove redundant source wavelets from the migrated image and the Hessian matrix. As a result, these improvements will greatly accelerate the convergence of linear inversion solvers while enhancing the resolution and amplitude fidelity of the resulting images. Experiments on synthetic and field datasets demonstrate that the proposed IDLSM method retrieves high-fidelity reflectivity images with superior resolution and amplitude fidelity compared to conventional IDLSM techniques.

Seismic reflection traveltime tomography (RTT) is an effective technique for inverting subsurface low-frequency velocity models for prestack depth migration and full-waveform inversion of seismic data. However, the velocity model established using RTT demonstrates limited resolution for extremely shallow and deeply complex strata. Small-offset first-arrival wave effectively characterize velocity variations in shallow strata, whereas large-offset first-arrival wave can reflect the velocity distribution in deeper strata. Therefore, we propose a three-dimensional joint tomographic inversion of first-arrival and reflection waves based on the adjoint state method in this article. The method integrates first-arrival traveltime data, reflection traveltime data and slope data for inversion, enhancing the accuracy of the inversion model from shallow to deep. The adjoint state method is employed to calculate the gradient of the misfit function with respect to velocity and the spatial coordinates of reflection points, thereby reducing the computational memory requirements and improving the efficiency of velocity modelling. The results of synthetic data tests based on a theoretical model verify the accuracy and effectiveness of the proposed joint inversion method. The proposed method is applied to ocean bottom node and ocean bottom cable wide-line seismic data collected in an extremely shallow sea in eastern China, yielding a more accurate velocity model.

The seismoelectric effect is an electrokinetic phenomenon that arises when seismic waves propagate in water-containing geological formations. Given that seismoelectric signals are sensitive to the hydraulic properties of the probed porous medium, they have the capability to provide important information during subsurface characterization efforts. In this work, we present a physics-based model for the dynamic streaming potential coupling coefficient (SPCC) in partially saturated porous media. For this, we conceptualize the porous medium as a partially saturated bundle of capillary tubes. We take into account the variation of pore size to relate the capillary pressure to the water saturation in the porous medium of interest. We then up-scale the streaming current and conduction current within the saturated capillaries under oscillatory flow conditions from pore to sample scale. The results show that the dynamic SPCC is not only a function of water saturation and the probing frequencies but also of the properties of water, mineral–water interfaces and other microstructural parameters of the porous medium. We analyse and explain the characteristics of the dynamic SPCC for two different pore size distributions (PSD): fractal and lognormal. Results show that the PSD characteristics have a strong effect on the dynamic SPCC responses. The proposed model has a remarkable ability to replicate experimental data available in the literature. In addition, it is observed that the lognormal distribution can provide a better agreement with experimental data for sand samples, which display a relatively narrow PSD. The findings of this study provide a valuable basis for interpreting seismoelectric signals under partially saturated conditions. Our proposed technique can be applied to any PSD, regardless of the complexity, providing a flexibility that is not present in alternative models found in the literature.

A comprehensive deep learning approach was introduced, encompassing data denoising, inversion imaging and uncertainty analysis. For denoising transient electromagnetic (TEM) data, we utilized a Bidirectional Long Short-Term Memory (BiLSTM) network. In the data inversion process, a combination of convolutional neural network (CNN) and BiLSTM structures was employed, and their outputs were consolidated using a multi-head attention mechanism. To ensure robust performance under challenging noise conditions, we implemented a specialized multi-channel noise training protocol during model optimization. The framework incorporates Monte Carlo (MC) dropout techniques to systematically evaluate prediction reliability throughout the inversion pipeline. This approach has not only been validated on test datasets but has also been successfully applied to the field dataset collected at the Narenbaolige Coalfield in Inner Mongolia, China. The deep learning inversion results obtained from both raw and denoised data exhibit reduced vertical continuity and increased roughness characteristics. In contrast, the Occam's inversion method with smoothness constraints yields results demonstrating superior lateral continuity and vertical smoothness. It is noteworthy that both inversion approaches show consistent interpretations regarding the scale of basalt formations and their contact interfaces with underlying sedimentary layers. Further uncertainty analysis reveals relatively higher uncertainty characteristics in the transition zones between basalt and sedimentary layers, as well as in deeper formations. The elevated uncertainty at interface regions may be attributed to model resolution limitations and inversion ill-posedness issues, whereas the higher uncertainty in deeper formations is more likely caused by the volumetric effects of electromagnetic field detection and the influence of observational data noise.

Accurate simulation of seismic waves is essential for achieving high-precision full-waveform inversion (FWI). Within the Cartesian coordinate system-based frequency-domain finite-difference (FDFD) framework, we propose a one-direction composition average-derivative optimal method for the 3D heterogeneous isotropic elastic-wave equation, referred to as the 45-point scheme. The results of dispersion analysis and weighted coefficient optimization demonstrate that the 45-point scheme achieves higher dispersion accuracy than the existing 27-point average-derivative scheme. More importantly, by constructing the impedance matrix along the ‘composition’ direction, the bandwidth of the sparse impedance matrix increases only slightly, with nonzero elements compactly distributed in strips. On the basis of the multifrontal massively parallel sparse direct solver (MUMPS) on a supercomputer platform, the 45-point scheme does not significantly increase computational complexity compared to the 27-point scheme. To further test the performance of the 45-point scheme, we provide several numerical experiments, including simple homogeneous and complex SEG/EAGE overthrust models. In comparison with the 27-point scheme, the 45-point scheme yields a notable improvement in computational accuracy, particularly for large grid ratios, while imposing only a modest increase in computational cost. These findings thus strongly suggest that the 45-point scheme holds promise as a viable option for the forward part of frequency-domain FWI in practical high-accuracy seismic imaging applications.