Abstract The detection of earthquake signals is a fundamental yet challenging task in observational seismology. A robust automatic algorithm strongly demanded view the ever‐growing global seismic dataset. Here, we develop an framework based on deep learning approach (SCALODEEP). It extracts high‐order features embedded three‐component seismograms by encoding time‐frequency representation data (scalogram) into network with skip connections. SCALODEEP trained and validated open‐source dataset...

SUMMARY Seismic inversion is one of the most commonly used methods in oil and gas industry for reservoir characterization from observed seismic data. Deep learning (DL) emerging as a data-driven approach that can effectively solve inverse problem. However, existing DL-based utilize only data input, which often leads to poor stability results. Besides, it has always been challenging train robust network since real survey limited labelled pairs. To partially overcome these issues, we develop...

Wave velocity dispersion and attenuation due to wave-induced fluid flow are important properties for seismic exploration studies of fracture characterization hydrocarbon identification. Existing inversions based primarily on an isotropic theory. However, both anisotropy should also be considered together. Based a model describing attenuation, we introduce frequency-dependent stiffness matrix azimuthal analysis, where the gradient weakness is novel indicator. Then, method inverting amplitude...

Abstract As an important part of China’s intangible cultural heritage, the characteristics and inheritance methods Yao ballads in Guangxi urgently need to be innovated order meet needs Internet era. The study summaries traits ballads, which include their rich vocal qualities, varied singing styles, extensive use song styles liner notes. On this basis, feasibility virtual reality technology development is analyzed, display path designed based on five-factor method user experience. immersive...

Reconstructing an accurate and high-resolution subsurface model is attractive in the fields of both geology seismology. However, due to band-limited characteristics seismic data, inversion greatly depends on reliability initial model. A fairly acceptable could lay a good foundation for inversion. In this article, we first introduce well-log interpolation method with local slope as constraint building high-fidelity starting prestack amplitude versus offset/angle (AVO/AVA) First, briefly...

ABSTRACT Erratic noise often has high amplitudes and a non‐Gaussian distribution. Least‐squares–based approaches therefore are not optimal. This can be handled better with non–least‐squares approaches, for example based on Huber norm which is computationally expensive. An alternative method been published involves transforming the data erratic to pseudodata that have Gaussian distributed noise. It then attenuated using traditional least‐squares approaches. previously used in combination...

Coherent seismic noise is usually difficult to attenuate due the similar morphological patterns between and useful signals. To coherent noise, special preknowledge should be utilized in a state-of-the-art approach, which causes significant inconvenience. Here, we develop an automatic method based on adaptive dictionary learning algorithm. The algorithm can learn features of both signals leave obvious differences atoms. These atoms transformed into statistical differences, measured then used...

Seismic waveform inversion has been one of the most studied topics in recent years, which can be implemented both common shot gather and prestack midpoint gather. However, there are still several intractable issues to addressed urgently, such as high-computational complexity, nonuniqueness, robustness. In this paper, we have developed a model-based (PWI) with generalized propagation matrix scheme forward operator, where regularized function is minimized limited...

Since most information on S-wave velocity and density exists in the middle to large angle range of seismic data, traditional inversion methods based Zoeppritz approximation have difficulty obtaining satisfactory results. Therefore, as a high-accuracy amplitude varied with (AVA) inversion, exact (EZ) equation has aroused lot attention recent years. As for any other nonlinear iterative convergence error are important problems. In this letter, Bayesian framework, we introduce optimal transport...

In situ stress estimation of a shale reservoir is critical for the design hydraulic fracturing and wellbore stability analysis. Fractured shales have orthogonal anisotropy (OA) because presence vertical fractures lamination. However, existing in method mainly focuses on transversely isotropic media. To accommodate orthogonally anisotropic media, an developed by using amplitude variation with angle azimuth inversion linear-slip theory. First, medium introduced to characterize fractured model,...

Spectral decomposition based on sparse constrained inversion, as proposed in recent years, is a high-resolution time-frequency domain analysis method. However, the traditional inverse spectral (ISD) algorithm an wavelet transform (IWT) whose mother Ricker function instead of adaptive wavelet, which causes poor continuity and instability ISD results. In this paper, we have extended into other linear transforms developed S (ISD-IST), has higher stability due to more adjustable adaptable...

The numerical solution of the inverse problem is usually obtained by solving a set linear algebraic equations, while system equations may suffer from ill-posedness due to insufficient data. Regularisation technique for making estimation problems well posed adding indirect constraints on estimated model, but regularisation parameter selection difficult. In geophysics, without explicit calculation methods and quantitative evaluation criteria, it based experience inversion engineers try achieve...

Five-dimensional (5D) seismic data reconstruction becomes more appealing in recent years because it takes advantage of five physical dimensions the and can reconstruct with large gap. The low-rank approximation approach is one most effective methods for reconstructing 5D dataset. However, main disadvantage method its low computational efficiency many singular value decompositions (SVD) block Hankel/Toeplitz matrix frequency domain. In this paper, we develop an SVD-free efficient denoising...

Prestack seismic inversion has emerged as a powerful technique for reconstructing parameters attribute to the subsurface properties and building geophysical parameter models. However, algorithms always suffer from spatial blur low resolution. Total variation (TV) regularization preserves boundary of data by highlighting sparsity first-order difference, which is regarded an important technical means image restoration. when do not change along grid direction, TV prone staircase effect. In this...

In exploration geophysics, AVO inversion is undoubtedly the most common inverse problem which ill-posed and must be regularized. Once regularization used, selection of parameter will become an important to solve. practice, proper value usually data dependent determined empirically. For one work area, engineers often give a fixed parameter. such case, results accompanied by strong artificial subjective factors. Besides, it difficult guarantee that could applied each trace seismic data. this...

Previous studies have reported immortalization and tumorigenicity of human mesenchymal stem cells (hMSCs) transduced with exogenous telomerase reverse transcriptase (hTERT). We also established a line hMSCs hTERT (hTERT-hMSCs) we cultured these for 290 population doublings (PDs) during which they demonstrated large proliferation potential but no tumorigenicity. The aim this study was to investigate the protein expression profile hTERT-hMSCs two-dimensional gel electrophoresis peptide mass...

ABSTRACT Ill‐posedness is one of the most common and intractable issues that arise when solving geophysical inverse problems. could be induced by various factors such as noise, band‐limited intrinsic property seismic data inappropriate forward operators. Regularization has been proven to an effective method widely accepted for mitigating adverse effects ill‐posedness. Aiming improve stability fidelity pre‐stack inversion process, we implement in a Bayesian framework, with logarithmic...

ABSTRACT Based on the fact that Hankel matrix constructed by noise‐free seismic data is low‐rank, low‐rank approximation (or rank‐reduction) methods have been widely used for removing noise from data. Due to linear‐event assumption of traditional method, it difficult define a rank optimally separates subspace into signal and subspaces. For preserving most useful energy, relatively large threshold often chosen, which inevitably leaves residual noise. To reduce energy noise, we propose an...