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Machine learning-based seismic processing models are typically trained separately to perform seismic processing tasks (SPTs) and, as a result, require plenty of high-quality training data. However, preparing training data sets is not trivial, especially for supervised learning (SL). Despite the variability in seismic data across different types and regions, some general characteristics are shared, such as their sinusoidal nature and geometric texture. To learn the shared features and thus, quickly adapt to various SPTs, we develop a unified paradigm for neural network-based seismic processing, called Meta-Processing, that uses limited training data for meta learning a common network initialization, which offers universal adaptability features. The proposed Meta-Processing framework consists of two stages: meta-training and meta-testing. In the former, each SPT is treated as a separate task and the training dataset is divided into support and query sets. Unlike conventional SL methods, here, the neural network (NN) parameters are updated by a bilevel gradient descent from the support set to the query set, iterating through all tasks. In the meta-testing stage, we also utilize limited data to fine-tune the optimized NN parameters in an SL fashion to conduct various SPTs, such as denoising, interpolation, ground-roll attenuation, image enhancement, and velocity estimation, aiming to converge quickly to ideal performance. Extensive numerical experiments are conducted to assess the effectiveness of Meta-Processing on both synthetic and real-world data. The findings reveal that our approach leads to a substantial improvement in the convergence speed and predictive performance of the NN. [ABSTRACT FROM AUTHOR]

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In an ever more challenging context for the acquisition of seismic data in the Mediterranean Sea, reprocessing to improve the quality of legacy data has become increasingly important. This work presents the newly reprocessed, open access dataset SALTFLU acquired in the Algerian basin by the National Institute of Oceanography and Applied Geophysics (OGS) in 2012. We apply a ‘broadband’ reprocessing strategy adapted for offset-limited (3 km streamer for a target 4 km below the sea level) airgun reflection seismic data acquired in deep water settings. We then assess if the reprocessed images provide new geological insights on the Mediterranean sub-surface. The workflow relies on an integrated approach combining geophysics and geological interpretation to iteratively build the velocity model. In this way we aim to tackle some of the challenges linked to imaging deep complex geological structures containing high velocity contrasts with 2-D, offset-limited seismic data. We first broaden the bandwidth of the data through multi-domain de-noising, deghosting and a source designature using an operator derived from the seabed reflection. We then perform iterative migration velocity analysis, pre-stack time migration and multiple attenuation in the Radon domain to obtain time-migrated images. The initial velocity model is derived from the resulting time migration velocities, and geologically driven model updates are generated using a combination of travel-time tomography, seismic interpretation of the major salt horizons and velocity gradient flooding. The gradient flooding aims to reproduce the large scale first-order velocity variations, while the travel-time tomography aims to resolve the smaller second-order velocity variations. The results improve our deep geological knowledge of the under-explored Algerian basin down to the base salt and the pre-salt. Fluid indicators are imaged within the Plio-Quaternary of the Algerian basin, which we interpret as thermogenic or biogenic gas sourced from either the Messinian Upper Unit or from the pre-salt, migrating through a hydro-fractured salt. The reprocessed data image lateral and vertical seismic facies variation within the Messinian units that could shed new light on the tectono-stratigraphic processes acting during the Messinian Salinity Crisis. It also reveals numerous previously unresolved volcanic structures within the Formentera basin. [ABSTRACT FROM AUTHOR]

When processing seismic survey data, it is desirable to reduce random noise without lowering the seismic resolution or lessening the number of seismic stacking folds. To this end, here we introduce a wavelet denoising of multi-angle (WDMA) method for prestack seismic data. Unlike the traditional method of directly stacking multi-angle gathers, our proposed WDMA method does not rely on the simple averaging of multi-angle prestack data, and when denoising the final result does not require averaging of direct stacking. Instead, WDMA first decomposes single-angle gathers through wavelet decomposition to determine local noise and obtain a detailed estimation, following which the average weighting coefficient is calculated and the data are reconstructed. Based on the above steps, we mainly studied the wavelet decomposition, optimization of the coefficient weight and weight mode, and the number of angle gathers. We used synthetic prestack angle gathers and field seismic data to validate the effectiveness of the proposed method. Even when the ratio of maximum noise amplitude to maximum effective signal amplitude was 60%, our proposed method could still achieve a good denoising effect by conducting WDMA two or more times. Compared with soft threshold wavelet denoising or the traditional stacking method, our results demonstrate that the proposed WDMA method can obtain high-quality seismic data using fewer frames of angle gathers and can simultaneously perform denoising and stacking. [ABSTRACT FROM AUTHOR]

The Nyquist sampling theorem must be followed in conventional seismic data acquisition; however, due to missing traces or exploration cost constraints, field data acquisition cannot meet the sampling theorem, so prestack data must be reconstructed to meet the requirements. We proposed a new seismic data reconstruction approach based on a fast projection onto convex sets (POCS) algorithm with sparsity constraint in the seislet transform domain, based on compressive sensing (CS) theory in the signal-processing field. In comparison to traditional projection onto convex sets (POCS), the faster projection onto convex sets (FPOCS) can achieve much faster convergence (about two-thirds of conventional iterations can be saved). To address the slow convergence of typical threshold parameters during reconstruction, an exponential square root lowered threshold and process 2-D seismic data reconstruction with hard thresholding has been purposed. Because of the much sparser structure in the seislet transform domain, the seislet transform-based reconstruction approach can clearly achieve better data recoveryresults than f-k transform-based scenarios, in terms of both signal-to-noise ratio (SNR) and visual observation. The proposed approach’s performance is demonstrated using both synthetic and field data examples. [ABSTRACT FROM AUTHOR]

Smartphones equipped with motion sensors can be manipulated as a community seismic network for earthquake detection. But, there still have many challenges such as the limited sensing capability of the off-the-shelf sensors and unpredictable diversity of daily operations by phone users in current smartphones, which yield poor monitoring quality. So we present a suite of algorithms towards detecting anomalous seismic events from sampling data contaminated by users operations, including a lightweight signal preprocessing method, a two-phase events picking and timing scheme on local smartphones, and a decision fusion scheme to maximize anomaly detection performance at the fusion center while meeting the requirements on system false alarm rate. We experimentally evaluate the proposed approach on networked smartphones and shake tables. The results verify the effectiveness of our approach in distinguishing anomalous seismic events from noises due to the normal daily operation. [ABSTRACT FROM AUTHOR]

Gas hydrates are a potential energy source. Seismic methods have been extensively applied to detecting gas hydrates based on the interpretation of bottom-simulating reflectors (BSRs), for which the seismic response is characterized by many features such as a strong reflection and low-frequency shadow (LFS). Moreover, the frequency content depends of the offset, with the BSR response having a lower dominant frequency at large offsets. In this work, we intend to enhance the low amplitude of the BSR and to observe the LFS phenomena at the southern Hikurangi margin of New Zealand. To improve the resolution of the seismic image, we processed a multichannel seismic profile acquired over a distance of 125 km. The standard processing sequence for seismic reflection data has been performed with an emphasis on using high fold. The results reveal that the BSR is characterized by strong reflections and high amplitude owing to the seismic data being stacked at higher fold. In addition, a continuation of the BSR event was obtained. Moreover, the use of a higher fold allowed us to determine an LFS below the BSR event, which indicates the presence of gas. The findings support other evidence obtained through contemporary studies on identifying gas hydrates using seismic methods. [ABSTRACT FROM AUTHOR]

Chałupki Dębniańskie seismic profile 2D–3C is located in Carpathian Foredeep basin, Poland, and is an object of interest for geologists and geophysicists due to the presence of gas-bearing layers. Multicomponent seismic plays a significant role in supporting reservoir analysis related to accumulations of crude oil and natural gas. The purpose of the research was the optimal processing workflow design, which integrated seismic images of three-component 2D seismic line (2D–3C seismic). A complete processing flow for vertical and both horizontal components was conducted to obtain stacks and prestack gathers with preserved amplitude relations (RAP processing). The main issue of the research was the interpretation of S-wave velocity, which was not provided by well log data. The obtained results increased the reliability of seismic interpretation within Chałupki Dębniańskie area. The research provided valuable information regarding amplitude anomalies and helped in the verification of the potential gas accumulations. Several reservoir analysis tools were tested, including seismic attributes and AVO analysis. Conducted research confirmed the existence of reservoir which is characterized by good reservoir parameters. [ABSTRACT FROM AUTHOR]

To acquire refined seismic targets, the use of more accurate and more precise methods of seismic signal processing is crucial. Novel seismic processing approach is even more important in case of the complex geology of mountainous regions (e.g., Carpathians, Carpathian Foredeep) where sub-vertical layering of varying rock complex can be found, but also in case of old seismic data reprocessing (especially when the signal-to-noise ratio and general quality are low). Regardless of many research papers and significant progress in seismic processing techniques, a properly processed and interpreted seismic image is still hardly affordable for this region. Obtaining a new value in seismic data processing is a core function of the presented research. The use of dip-guided filtering combined with beam partitioned analysis and Z-domain dip analysis for reprocessing of 3D and 2D seismic data from the Carpathians region has been studied. [ABSTRACT FROM AUTHOR]

The Romanian segment of the Eastern Pannonian Basin and the Moesian Platform are known for their geothermal and hydrocarbon-bearing structures. We used seismic, gravity, and geothermal data to analyze the geothermal behavior in the Oradea and Timisoara areas, from the Romanian segment of Eastern Pannonian Basin, and the Craiova-Bals-Optasi area, from the Moesian Platform. We processed 22 seismic reflection data sets recorded in the Oradea and Timisoara areas to obtain P-wave velocity distributions and time seismic sections. The P-wave velocity distributions correlate well with the structural trends observed along the seismic lines. We observed a good correlation between the high areas of crystalline basement seen on the time seismic sections and the high heat flow and gravity-anomaly values. For the Craiova-Bals-Optasi area, we computed a three-dimensional (3D) temperature model using calculated and measured temperature and geothermal gradient values in wells with an irregular distribution on the territory. The high temperatures from the Craiova-Bals-Optasi area correlate very well with the uplifted basement blocks seen on the time seismic sections and high gravity-anomaly values. [ABSTRACT FROM AUTHOR]

Chirp sonar systems can be used to obtain high resolution seismic reflection images of the sub-seafloor during marine surveys. The exact knowledge of the Chirp signature allows the use of deterministic algorithms to process the data, similarly to that applied to Vibroseis data on land. Here, it is described an innovative processing sequence to be applied to uncorrelated Chirp data, which can improve vertical and lateral resolution compared to conventional methods. It includes application of a Wiener filter to transform a frequency-modulated sweep into a minimum-phase pulse sequence. In this way, the data become causal and can undergo predictive deconvolution to reduce ringing and enhance vertical resolution. Afterwards, FX-deconvolution and Stolt migration can be applied to obtain an improved imaging of the subsurface. The result of this procedure is a seismic reflection image with higher resolution than traditional ones, which are normally represented using the envelope function of the signal. This technique can be particularly useful for engineering-geotechnical surveys and archaeological investigations that require a fine detail imaging of the uppermost meters of the sub-seafloor. [ABSTRACT FROM AUTHOR]

Depth conversion of selected seismic reflections is a valuable procedure to position key reflectors in depth in a process of constructing or refining a depth-velocity model. The most widespread example of such procedure is the so-called map migration, in which normal-incidence, zero-offset (stacked) seismic data are employed. Since the late seventies and early eighties, under the assumption of an isotropic velocity model, map migration algorithms have been devised to convert traveltime and its first and second derivatives into reflector position, dip and curvatures in depth. In this work we revisit map migration to improve the existing algorithms in the following accounts: (a) We allow for fully anisotropic media; (b) In contrast to simple planar measurement surface, arbitrary topography is allowed, thus enlarging the algorithms applicability and (c) Derivations and results are much simplified upon the use of the methodology of surface-to-surface paraxial matrices. [ABSTRACT FROM AUTHOR]

Offset continuation (OCO) is a seismic configuration transform designed to simulate a seismic section as if obtained with a certain source-receiver offset using the data measured with another offset. Since OCO is dependent on the velocity model used in the process, comparison of the simulated section to an acquired section allows for the extraction of velocity information. An algorithm for such a horizon-oriented velocity analysis is based on so-called OCO rays. These OCO rays describe the output point of an OCO as a function of the Root Mean Square (RMS) velocity. The intersection point of an OCO ray with the picked traveltime curve in the acquired data corresponding to the output half-offset defines the RMS velocity at that position. We theoretically relate the OCO rays to the kinematic properties of OCO image waves that describe the continuous transformation of the common-offset reflection event from one offset to another. By applying the method of characteristics to the OCO image-wave equation, we obtain a raytracing-like procedure that allows to construct OCO trajectories describing the position of the OCO output point under varying offset. The endpoints of these OCO trajectories for a single input point and different values of the RMS velocity form then the OCO rays. A numerical example demonstrates that the developed ray-tracing procedure leads to reliable OCO rays, which in turn provide high-quality RMS velocities. The proposed procedure can be carried out fully automatically, while conventional velocity analysis needs human intervention. Moreover, since velocities are extracted using offset sections, more redundancy is available or, alternatively, OCO velocities can be studied as a function of offset. [ABSTRACT FROM AUTHOR]

Reasonable use of mathematical modeling and numerical simulation of regional earthquake activities has attracted more and more attentions in realistic seismicity studies in recent years. The inherent nature of their attendant multi-scale properties, from either the temporal or the spatial direction, necessitates the use of the cutting-edge massive parallel data processing techniques. Our study here is focused on the model construction and numerical simulation of the regional stress evolution after large earthquake sequences along the fault zones in Sichuan and Yunnan areas, using large-scale parallel finite element approximations with tens of millions of unstructured meshes on the distributed systems. The objective of our study is to provide a state-of-the-art model and a large-scale numerical simulation platform, on which estimation of the risk of large earthquake triggering sequences can be carried out in a middle or long-term time scale with realistic data and constrains inputted from field observation and geological survey. [ABSTRACT FROM AUTHOR]