Geophysical Prospecting最新文献

Since many years ago, ultrasonic velocity has been used to investigate the physical and mechanical behaviour of rocks, thereby playing an important role in reservoir characterization and seismic interpretation. In order to develop the knowledge of ultrasonic tools, I performed a noble analysis on the ultrasonic behaviour of rocks under confining stress and evaluated a distinctive property of porous media that is measured as the area under the stress–velocity curve (here defined as S^*). I further investigated its relationship with elastic and mechanical behaviours of rock. To validate the theoretical framework developed in this work, 20 core plugs from various rock units with complex microstructures were subjected to triaxial compressional tests to calculate their area under the curve. Calculations were made for crack-closing, elastic and post-elastic stages (e.g. pore collapse) along the ultrasonic velocity–stress curve. Moreover, the selected samples had their microstructure investigated by thin-section studies to quantify their porosity and pore type. The results were analysed to check for the effect of pore type on S^* in different stages of the stress–velocity curve. Based on the outputs of the analysis of variance and Pearson's correlation coefficient analysis, the curve had its shape and underlying area closely related to the porosity and pore geometry. Indeed, the results showed that the shale and sandstone with micro cracks and carbonate with stiff pores correspond to smaller and larger areas under the curve in crack-closing and inelastic stages, respectively. Cross-correlating the results to compressibility (inverse of bulk modulus), it was figured out that the calculated area under curve was well consistent with the compressibility. In addition, S^* represents both static and dynamic behaviours of the rock, and the results revealed that the shape and curvature of the stress–velocity curve give valuable information about the rock microstructure. Another finding was the fact that the type of fluid and wave velocity seemingly affect the S^*. Our findings can help interpret wave velocity behaviour in reservoir rocks and other stressful porous media.

The interlayer wave-induced fluid flow is an important mechanism for seismic attenuation and dispersion, as well as frequency-dependent anisotropy, in the fluid-saturated porous layered medium. This mechanism is closely related to the medium physical properties, and thus quantifying this mechanism is of significance for the seismic inversion of medium physical properties. Although numerous models have been proposed to quantify this mechanism, most models do not consider the effects of layer intrinsic anisotropy. To solve this problem, the effective complex-valued and frequency-dependent stiffness coefficients are derived for the fluid-saturated porous medium composed of periodic transversely isotropic layers. Using the derived solutions, we study the effects of layer intrinsic anisotropy on seismic dispersion and attenuation, as well as frequency-dependent anisotropy. It has been found that different matrix or fluid property contrasts between adjacent layers lead to different effects of intrinsic anisotropy. In addition, the effects of intrinsic anisotropy are also influenced by the fluid distribution when both matrix and fluid properties contrast among adjacent layers exist. In the low- and high-frequency limits of wave-induced fluid flow, our model reduces to the previous known results, which validates the correctness of our model. Our model can be applied in the seismic inversion of physical properties of reservoirs with intrinsic anisotropy, such as shale and tight sandstone reservoirs. In addition, our model can also be extended to cases with more complex intrinsic anisotropy and, thus, can be applied to complex anisotropic fractured reservoirs in the future.

In recent years, self-supervised procedures have advanced the field of seismic noise attenuation, due to not requiring a massive amount of clean labelled data in the training stage, an unobtainable requirement for seismic data. However, current self-supervised methods usually suppress simple noise types, such as random and trace-wise noise, instead of the complicated, aliased ground roll. Here, we propose an adaptation of a self-supervised procedure, namely, blind-fan networks, to remove aliased ground roll within seismic shot gathers without any requirement for clean data. The self-supervised denoising procedure is implemented by designing a noise mask with a predefined direction to avoid the coherency of the ground roll being learned by the network while predicting one pixel's value. Numerical experiments on synthetic and field seismic data demonstrate that our method can effectively attenuate aliased ground roll.

In seismic exploration, it is very important to consider the presence of anisotropy in order to image the subsurface correctly. The knowledge of anisotropic parameters leads to more precise characterization of reservoir, fracture density and flow paths. However, conventional geophysical methods do not directly measure these parameters, and it is useful to have a method to estimate them from seismic data. In the weak transverse isotropy approximation, the fields to be considered are the vertical and horizontal velocity components and the Thomsen parameters $�\epsilon$ and $�\delta$. We present a method for estimating the anisotropic Thomsen parameters in the presence of weak vertical transverse isotropy using P-wave traveltime tomography based on anisotropic ray tracing. Depending on the available information, we propose different approaches to retrieve the unknowns. A conventional three-dimensional traveltime tomography algorithm has been extended to include anisotropic ray tracing and using the algebraic reconstruction technique or modified simultaneous iterative reconstruction technique to retrieve the unknowns. We test the method on synthetic examples for the inversion of transmitted and reflected traveltimes, and we evaluate the sensitivity of the tomographic results to the available information. Furthermore, we also consider the case of tilted transverse isotropy in a seismic reflection example.

The accurate numerical solution at an acoustic–elastic interface is important for offshore exploration. The solution requires careful implementation for the acoustic–elastic boundary conditions. In this work, we leverage a nodal discontinuous Galerkin method, in which the unstructured uniform triangular meshes are used for the model meshing and an explicit upwind numerical flux derived from the Riemann problem is adopted to handle the boundary conditions at the acoustic–elastic interface. Several numerical results are provided to assess the accuracy and convergence properties of this method. The convergence analysis is carried out in the coupled model with a flat interface, and the accuracy of the proposed method is verified in the curved interface coupled model. Finally, a more complex model with a salt dome, inspired by real geophysical applications, is carried out in this study. The numerical results demonstrate that the proposed nodal discontinuous Galerkin method is effective and accurate for dealing with the coupled acoustic–elastic media with complex geometries.

S-wave velocity plays a crucial role in various applications but often remains unavailable in vintage wells. To address this practical challenge, we propose a machine learning framework utilizing an enhanced bidirectional long short-term memory algorithm for estimating S-wave sonic logs from conventional logs, including P-wave sonic, gamma ray, total porosity, and bulk density. These input logs are selected based on traditional rock physics models, integrating geological and geophysical relations existing in the data. Our study, encompassing 34 wells across diverse formations in the Delaware Basin, Texas, demonstrates the superiority of machine learning models over traditional methods like Greenberg–Castagna equations, without prior geological and geophysical information. Among these machine learning models, the enhanced bidirectional long short-term memory model with self-attention yields the highest performance, achieving an R-squared value of 0.81. Blind tests on five wells without prior geologic information validate the reliability of our approach. The estimated S-wave velocity values enable the creation of a basin-scale S-wave velocity model through interpolation and extrapolation of these prediction models. Additionally, the bidirectional long short-term memory model excels not only in predicting S-wave velocity but also in estimating S-wave reflectivity for seismic amplitude variation with offset applications in exploration seismology. In conclusion, these S-wave velocity estimates facilitate the prediction of further elastic properties, aiding in the comprehension of petrophysical and geomechanical property variations within the basin and enhancing earthquake hypocentral depth estimation. 

A time-domain finite-element method based on an arbitrary quadrilateral mesh is proposed to simulate two dimensional seismoelectric and electroseismic waves in SHTE mode. By decoupling the electrokinetic coupling equation, we can solve seismic waves and electromagnetic waves independently. For the simulation of seismic wavefield, we utilize a more compact second-order unsplit perfectly matched layer that is easier to implement in finite-element methods. Moreover, to avoid errors caused by the quasi-static approximation, we directly solve the full-wave electromagnetic equations when simulating the electromagnetic wavefield. Our computational domain is discretized using arbitrary quadrilateral meshes, which offers possibilities in handling undulating terrain and complex anomalies in the underground. To ensure computational accuracy, we utilized biquadratic interpolation as our finite-element basis functions, which provides higher precision compared to bilinear interpolation. We validate our time-domain finite-element method by comparing its results with analytical solutions for a layered model. We also apply our algorithm to the modelling of an underground aquifer and a complex anomalous hydrocarbon reservoir under undulating terrain.

Artificial caverns in salt rock formations play an important role in the net-zero energy transition challenge, both for covering short-term fluctuations in energy demand and serving as safe locations for long-term underground gas storage both for hydrogen and natural gas. Geophysical tools can serve for monitoring geomechanical changes in the salt cavern during selection and development, and during gas storage/extraction activities, but the use of common geophysical monitoring techniques has been very limited in this area. Here, we present experimental work on physical and transport properties of halite rocks within the energy storage context and assess the potential of seismic and electromagnetic data to monitor gas storage activities in salt formations. First, we analysed the stress-dependency of the elastic and transport properties of five halite rocks to improve our understanding on changes in the geological system during gas storage operations. Second, we conducted two dissolution tests, using cracked and intact halite samples, monitored with seismic (ultrasonic P- and S-waves velocities and their attenuation factors) and electromagnetic (electrical resistivity) sources to evaluate (i) the use of these common geophysical sensing methods to remotely interpret caverning development and (ii) the effect of structural discontinuities on rock salt dissolution. Elastic properties and permeability showed an increasing trend towards rock sealing and mechanical enhancement with increasing pressure for permeabilities above 10⁻²¹ m², with strong linear correlations up to 20 MPa. In the dissolution tests, the ultrasonic waves and electrical resistivity showed that the presence of small structural discontinuities largely impacts the dissolution patterns. Our results indicate that seismic and electromagnetic methods might help in the selection and monitoring of the caverning process and gas storage operations, contributing to the expected increase in demand of large-scale underground hydrogen storage.

Rock physics connects with geophysics, petrophysics and geomechanics to adequately characterize geological reservoirs, optimize monitoring operations in the field, interpret in situ and laboratory test data, and develop accurate predictive models for extraction/injection activities. The application of rock physics is crucial to achieving net-zero carbon emissions worldwide, as we need to combine large-scale mitigation technologies like carbon capture usage and storage, together with an increasing use of renewables such as geothermal and underground hydrogen storage (UHS).

In this special section, we introduce the role of rock physics on the energy transition challenge. The papers presented herein are representative of the topics discussed during 6th International Workshop in Rock Physics (6iWRP) that took place in A Coruna, Spain, between 13 and 17 of June 2021 (Delgado-Martín et al., 2022). This biannual event gathers rock physicists from all over the world to discuss, beyond the state of the science, experimental and theoretical rock physics topics covering spatial scales from grain to sample to basin scale. The 6iWRP focused on energy transition and climate change mitigation topics, such as CO₂ storage in geological formations, H₂-based energy storage in porous rocks and geothermal energy. Other topics covered in the conference included homogeneous/heterogeneous materials with different degrees of anisotropy and fracturing and their influence in fluid flow in fractured porous media, the coupled phenomena associated with rock-fluid interaction under reservoir conditions, data analysis and interpretation using combined rock physics models and machine learning models.

This special section was proposed to encourage submissions of papers from pure, fundamental research to more applied demonstrations and integrated case studies around the topics covered during the 6iWRP. This call resulted in five papers accepted from 12 submitted manuscripts. The research presented in these papers demonstrates the potential of rock physics to contribute to meeting net-zero goals timely. We would like to express our gratitude to all the contributors and reviewers for their substantial efforts and significant contributions to this special section. Find below a brief summary of the published contents.

Deheuvels, Faucher and Brito proposed a novel approach to determining the frequency-dependent attenuation of low-attenuation materials, with application to inversion analysis in viscoelastic media. They apply a Gaussian filter to infer frequency-dependent attenuation from a multiple wave reflection source, using relative amplitude decay in the seismogram. They tested the method experimentally in aluminium and dry Fontainebleau sandstone at ultrasonic frequencies.

Falcon-Suarez, Dale and Marin-Moreno presented dual experimental research on the physical and transport properties of sal