Geophysical Prospecting最新文献

Automatic first-break picking is a basic step in seismic data processing, so much so that the quality of the picking largely determines the effect of subsequent processing. To a certain extent, artificial intelligence technology has solved the shortcomings of traditional first-break picking algorithms, such as poor applicability and low efficiency. However, some problems still remain for seismic data, with a low signal-to-noise ratio and large first-break change leading to inaccurate picking and poor generalization of the network. In order to improve the accuracy of the automatic first-break picking results of the above seismic data, we propose a multi-view automatic first-break picking method driven by multi-network. First, we analysed the single-trace boundary characteristics and the two-dimensional boundary characteristics of the first break. Based on these two characteristics of the first break, we used the Long Short-Term Memory and the ResNet attention gate UNet (resudual attention gate UNet) networks to extract the characteristics of the first arrival and its location from the seismic data, respectively. Then, we introduced the idea of multi-network learning in the first-break picking work and designed a feature fusion network. Finally, the multi-view first-break features extracted by the Long Short-Term Memory and resudual attention gate UNet networks are fused, which effectively improves the picking accuracy. The results obtained after applying the method to field seismic data show that the accuracy of the first break detected by a feature fusion network is higher than that given by the above two networks alone and has good applicability and resistance to noise.

Quantification of data misfits and model structures is an important step in the non-linear iterative inverse scheme, allowing medium parameters to be iteratively refined through minimization. This study developed a new three-dimensional controlled-source electromagnetic inversion algorithm that allows general measures to be made selectively available for this evaluation. We adopt $�{\ell }_2$, $�{\ell }_1$, Huber, hybrid $�{\ell }_1$/$�{\ell }_2$, Sech, Cauchy, biweight and $�{\ell }_0$ norms as general measures. The inversion implementation is based on a regularized Gauss–Newton method, and non-quadratic measures are incorporated via the use of an iteratively reweighted least-squares scheme. To exploit current computing power, forward solutions are computed on an edge finite-element discretization using a parallel version of a direct sparse solver, while dense matrix operations in inversion are optimized using the LAPACK library. The behaviours of general measures for evaluating data misfits and model structures are examined in synthetic inversion experiments, focusing on elucidating weighting mechanisms and setting user-defined parameters. A preliminary demonstration is presented, showcasing simultaneous regularization in imaging a toy model containing both sharp and smooth property changes, alongside a field data application for imaging subsurface artificial structures. Our findings highlight the seamless integration of general measures, contributing to improved robustness against data outliers and enhanced spatial properties provided in output models.

Slope failure rates may be exacerbated by increased precipitation patterns associated with climate change. Such events are extremely disruptive for local communities affected. Rapid engineering remediation solutions generally require immediate site characterization, including information on depth to intact bedrock and groundwater conditions – often on dangerous or still-failing slopes. Horizontal-to-vertical spectral ratio is a low-impact technique capable of rapidly providing key information on the subsurface. Here we develop a robust workflow for constrained minimization of horizontal-to-vertical spectral ratio data and develop constrained horizontal-to-vertical spectral ratio profiling methodologies. We present results from a number of landslide sites in eastern Australia and demonstrate the utility of horizontal-to-vertical spectral ratio in delineating both fractured-rock aquifers at high-risk sites and colluvium–bedrock contact on active landslide sites, where traditional seismic methods were not practical.

As a young researcher, I was very interested in diffraction signal processing, and I recall attending many sessions and workshops dedicated to this topic during 2005–2009 at various conferences. At almost all these events, there was one individual who caught my attention with his depth of knowledge and dedication to the topic of diffraction. Yes, this was Tijmen Jan Moser who inspired many presenters and authors at these events.

Tijmen Jan has been Editor-in-Chief (EiC) of Geophysical Prospecting for over 16 years and has served the journal through several ups and downs. Throughout his tenure as EiC, he has managed to ensure that submitted manuscripts were all fairly ‘judged’ in order to meet the technical quality the journal's readership desires. Geophysical Prospecting is a ‘flagship’ journal of EAGE (European Association of Geoscientists and Engineers) and has served its membership and the broader geoscience community as an authoritative source of new research. During his tenure, the journal has steadily grown its impact factor.

As the successor to Tijmen Jan as EiC of Geophysical Prospecting, I had a chance to have a short interview with him, during which I gathered some key information and thoughts about his tenure. Tijmen Jan began his education at Utrecht University. Following graduation, he joined several organizations, including Amoco, IFP, the University of Bergen, the University of Karlsruhe, Norsk Hydro, the Geophysical Institute of Israel, Charles University in Prague and Fugro-Jason. He is currently an independent consultant. He was particularly fascinated by ‘ray-based methods’. Though now he shows more interest in its ‘failed baby’, ‘diffraction’, as he recently stated in a book that he authored with Enders Robinson (Moser and Robinson, 2024): ‘What Huygens could have written on diffraction’.

He began serving the journal first as a reviewer, then as Associate Editor and then moved up quickly to Deputy Editor; on the request of Aldo Vesnaver, former EiC, he was appointed to the EiC role in 2008. At that time, the journal was facing several challenges.

Prior to Aldo Vesnaver (2006–2008), Roy White (2004–2006), Gerhard Diephuis (2002–2004) and Klaus Helbig (1969–1985) also served the journal as EiC. Klaus Helbig was Tijmen Jan's PhD supervisor. During a conversation I had with Tijmen Jan, I jokingly told him that he should let Klaus continue to retain the honour of being the longest serving EiC of the journal, given that he had been his PhD supervisor. My suggestion, in jest, worked, and Tijmen Jan served one year less than Klaus Helbig!

The voluntary position of EiC involves many serious duties. Tijmen Jan told me that he took over 4000 decisions during his tenure and managed numerous disputes about the fate of some of the manuscripts! Today, he feels disappointed that the level of challenge amongst our community seems to be reducing somewhat, and he encourages authors and reviewers to s

The basin environment is a widely studied subject in both geology and geophysics for its economic significance in energy and mineral explorations. However, the estimation of the basement depth is often a challenging task given the complexity of the basement relief and lateral physical property change. Previous works simplify the problem by only inverting for the depth to the basement, and more recent studies have suggested the need to incorporate the variation of physical properties to improve basement structure imaging. In this study, we develop an inversion method with the associated workflow to simultaneously recover both the depth to a magnetic basement and a laterally varying magnetic susceptibility in the basement rock. To achieve this, we employ a set of constraints on the inverse problem. Particularly, both the recovered susceptibility and basement depth models are bounded below a possible maximum value, and the depth model is guided by a few depth points obtained from the resistivity models that are obtained from the one-dimensional blocky inversions of magnetotelluric (MT) data. In addition, we apply the fuzzy C-means (FCM) clustering to the susceptibility model during the inversion and use the inverted cluster centers to differentiate for different geological units in the basement. To show the effectiveness of our work, we compare the existing approaches and our method using two test inversions on one synthetic model resembling the basin–basement environment before demonstrating our method on a field data example with magnetic data collected by the U.S. Geological Survey (USGS) over the Illinois Basin. Our results show improved recovery in both basement relief and susceptibility in the basement rock, and inversion with field data is able to identify three different susceptibility zones in basement rock below the Illinois Basin.

The fractal formalisms are well known for providing new understandings regarding the geometrical, spatial, and temporal behaviour of seismicity. Particularly, the fractal dimensions give information about the seismic events self-organization and self-similarity. On the other hand, the Gutenberg–Richter value, known as the b-value, has shown through the years to give handy information regarding the statistical distribution of earthquakes, on-site physical parameters, and geomechanical inputs. The Gutenberg–Richter value (b) and the capacity and correlation fractal dimensions, (D₀ and D₂), of the spatial distribution of earthquake hypocentres interact mathematically for micro- and macro-events. From this interaction, it is possible to obtain new insights into the fracture network development and the microseismicity source characterization in terms of single fractures, fault planes, or densely fractured volumetric spaces. Here we show this interaction for the open-source Decatur CO₂ project seismicity catalogue, comparing it with the results obtained for a natural earthquake catalogue of Illinois, in the United States. The fractal dimension D₀ is calculated using two different methodologies: box-counting and correlation integral partitioning. This last method is also used to calculate D₂. The results presented in this study allow us to describe how the fracture network geometry influences the earthquake complexity. Together with the calculation of the b-value, we present clear indications which show that seismicity recorded in the Illinois tectonic environment partially follows the Aki relationship D₀ ∼ 2b, which is not the case for induced events. In addition, the induced earthquake dataset shows that D₂ > D₀, an anomalous behaviour in terms of the fractal formalisms. All these facts might be used to establish spatial fracture network control techniques and seismicity-type distinctions in CO₂ injection sites located in highly active tectonic areas, respectively.

To enhance the 3D numerical simulation of the induced polarization method within anisotropic media, our study employs the 2D Fourier transform technique. This technique is utilized to convert the 3D integral of the abnormal potential from the space domain into a 1D integral in the wave number domain. Subsequently, we apply the shape function integration method, which is founded on quadratic interpolation, to resolve the 1D integral equation effectively. This methodology significantly decreases the necessary computational resources and storage while simultaneously harnessing the high efficiency and accuracy of the 1D shape function integration method, as well as the high efficiency of the fast Fourier transform, optimizing the numerical simulation process of the induced polarization method. We validate the accuracy of our algorithmic approach using an equivalent uniform layered model. Furthermore, by employing the sphere model, we conduct a comparison of computation time with the finite element method, thereby demonstrating high efficiency of the proposed algorithm. Utilizing the OpenMP parallel algorithm, we confirm that the proposed algorithm has a high degree of parallelism. We also analyse the differences in the equivalent apparent resistivity and apparent polarizability for various electrical parameters, using a prismatic model as the basis for our analysis. Our results clearly indicate that the anisotropy of the polarizability exerts substantial influence on the observe data. Consequently, the implications of polarizability anisotropy are deemed critical and not be disregarded in the field detection applications.

Acoustic logging is an important method used to determine formation velocities near boreholes. However, in practice, determining accurate formation velocities from acoustic logging data is challenging because of the presence of various noise interferences. Accordingly, a method to increase the amplitudes of refracted waves in open boreholes is proposed herein on the basis of the directional radiation technology of pulse compression signal–driven linear phased array acoustic transmitters. The waveforms generated by a Ricker monopole acoustic transmitter, linear frequency modulation monopole acoustic transmitter and pulse compression signal–driven linear phased array acoustic transmitter in a fluid-filled open borehole are numerically simulated by employing the finite-difference method. The effects of the pulse compression signal–driven linear phased array parameters on the amplitudes of the refracted compressional and shear waves are studied. Results show that borehole mode waves with the same velocities and dispersion characteristics can be determined using the pulse compression signal–driven linear phased array acoustic and Ricker monopole acoustic transmitters in fluid-filled open boreholes. Pulse compression signal–driven linear phased array acoustic transmitters leverage the advantages of pulse compression and phased array technologies, ensuring that a single element can radiate more acoustic energy, whereas pulse compression signal–driven linear phased array parameters can be modulated to further increase the amplitudes of the refracted compressional and shear waves. Compared with Ricker and linear frequency modulation monopole acoustic transmitters, pulse compression signal–driven linear phased array acoustic transmitters can provide downhole received waveforms of better quality and improved a signal-to-noise ratio of the mode wave dispersion curves obtained using the downhole received waveforms. Because pulse compression signal–driven linear phased array acoustic transmitters use linear frequency modulation drive signals of longer duration, the recording time required for the received waveforms is also longer and the amount of data generated is larger, presenting new challenges for downhole data processing and high-speed data transmission.

Transversely isotropic media with a tilted symmetry axis (TTI) exits widely underground due to tectonic movement and mineral orientation. Traditional full waveform inversion (FWI) based on isotropic media or transversely isotropic media with a vertical symmetry axis (VTI) cannot deal with such situations. To address this limitation, TTI–based FWI was developed. However, its practical application faces challenges in estimating the symmetry axis tilt angle $�{\theta }_t$. Previous studies have generally assumed that $�{\theta }_t$ is equal to the strata dip angle, which is incorrect in complex structures such as salt domes and magmatic intrusion zones. Another theoretically robust way to estimate $�{\theta }_t$ is to treat it as the parameter to be inverted, but there are still some problems unresolved. First, the parameter $�{\theta }_t$ increases the nonlinearity of the inversion process, and its impact mechanism on inversion is not yet clear. Second, there is severe crosstalk (also known as trade-off or coupling) between parameters, but the current parameter decoupling technique for TTI–based FWI is not mature. To address the first problem, we assess the interaction between $�{\theta }_t$ and other parameters by analysing the radiation patterns in the TTI background. Our analysis reveals that $�{\theta }_t$ is most coupled by S-wave vertical velocity

Missing data and random noise are prevalent issues encountered during the processing of acquired seismic data. Interpolation and denoising represent economical solutions to address these limitations. Recovering regularly missing traces is challenging because of the spatial aliasing, and the extra difficulty is compounded by the presence of noise. Hence, developing an effective approach to realize denoising and anti-aliasing is important. Projection onto convex sets is an effective method for recovering missing seismic data that is typically used for processing data with a good signal-to-noise ratio. The computational attractiveness of the projection onto convex sets reconstruction approach is compromised by its slow convergence rate. In this study, we aimed to efficiently implement simultaneous seismic data de-aliasing and denoising. We combined a discrete wavelet transform with a seislet transform to construct a hybrid wavelet transform. A new fast adaptive method based on the fast projection onto convex sets method was proposed to recover the missing data and remove random noise. This approach adjusts the projection operator and iterative shrinkage threshold operator. The result is influenced by the threshold value. We enhanced the processing accuracy by adopting an optimal threshold strategy. Synthetic and field data tests indicate the effectiveness of the proposed method.