Multiple attenuation based on connected-component analysis and high-resolution parabolic Radon transform

This article presents the pre-stack attenuation of multiple noises from a 2-D land seismic survey acquired on the Iraq-Kuwait border in southern Iraq. The processing workflow is performed using the Geovation software from CGG that employs a de-aliased High-Resolution Radon with a non-iterative process for seismic reflection data. First, we apply noise attenuation, surface deconvolution (predictive), and normal move-out (NMO) correction, which is executed using the root-mean-square velocity (RMS velocity) to flatten the primary event, and the Common Mid-Point gathers (CMP gathers) are converted into the Radon domain using a least-squares-parabolic Radon transform. Several tests are performed on some parameters to predict the multiple events using a High-Resolution de-aliased multiple attenuation (RAMUR) algorithm aimed to attenuate multiple events. RAMUR algorithms compute a model of primary and multiple events based on data decomposition into user-defined parabolas and are performed using a high-resolution, de-aliased least-squares method. The Radon transforms separate primary reflection and multiple reflection events in the (τ-q) domain based on move-out differences between primary and multiple events, which are characterized as events with slower velocity. Reflection events relating to parabolas with a higher curvature are counted as multiples, whereas events with smaller are counted as primary events. The RAMUR algorithms subtract the model of multiples from the input gathers. The workflow effectively attenuates reflection-based generated multiples events, which improves the overall seismic response after imaging, and enhances correlation with well information.

Hyperbolic Radon transform is an important method for multiple attenuation, but for VTI media and marine large offset seismic data, which reflected wave event can not meet hyperbolic time distance relationship, the primary wave and multiple wave energy cant not focus well in the Radon domain, which can affect the multiple wave attenuation effect. So this paper introduces the anisotropic parameters  into the time distance relationship when we describe the VTI medium and marine large offset seismic data time distance curve relationship, the primary wave and multiple wave energy can focus well in the Radon domain. Meanwhile, based on L1 norm sparse constraint in the model space, we introduce anisotropic high-resolution Radon transform based on CGG (Conjugate Guided Gradient) algorithm to improve the Radon transform resolution. By testing of model data and large offset actual data show that the method can achieve the multiple attenuation.

The parabolic Radon transform is one of the most commonly used multiple attenuation methods in seismic data processing. The 2D Radon transform cannot consider the azimuth effect on seismic data when processing 3D common-depth point gathers; hence, the result of applying this transform is unreliable. Therefore, the 3D Radon transform should be applied. The theory of the 3D Radon transform is first introduced. To address sparse sampling in the crossline direction, a lower frequency constraint is introduced to reduce spatial aliasing and improve the resolution of the Radon transform. An orthogonal polynomial transform, which can fit the amplitude variations in different parabolic directions, is combined with the dealiased 3D high-resolution Radon transform to account for the amplitude variations with offset of seismic data. A multiple model can be estimated with superior accuracy, and improved results can be achieved. Synthetic and real data examples indicate that even though our method comes at a higher computational cost than existing techniques, the developed approach provides better attenuation of multiples for 3D seismic data with amplitude variations.

In recent years a number of new algorithms have been added to the seismic data processor’s arsenal for dealing with multiple reflections. Nevertheless, in many regions of the world multiple reflections remain the biggest impediment to obtaining high‐quality, easily interpreted seismic surveys. In 1997 a workshop was held during the SEG Annual Meeting to compare and contrast some of the newer multiple attenuation methods. The workshop, called “A Comparison of Seismic Multiple Attenuation Techniques,” was organized by Simon Spitz, Fernanda Gasparotto, Art Weglein, and me, and was sponsored by the SEG Research Committee. The workshop goal were to learn what the relative strengths and weaknesses of the various approaches to multiple attenuation might be, and to improve our understanding of the overall status of the multiple problem: Is the problem solved? If so, by what methods and at what costs? If not, what remains to be done, and which approaches look most promising? What about multiples in 3‐D data sets?

A multiple attenuation method derived from an inverse scattering series is described. The inversion series approach allows a separation of multiple attenuation subseries from the full series. The surface multiple attenuation subseries was described and illustrated in Carvalho et al. (1991, 1992). The internal multiple attenuation method consists of selecting the parts of the odd terms that are associated with removing only multiply reflected energy. The method, for both types of multiples, is multidimensional and does not rely on periodicity or differential moveout, nor does it require a model of the reflectors generating the multiples. An example with internal and surface multiples will be presented.

Low RCS targets detection is a challenging problem for marine radar in sea clutter. In this paper, a new detection algorithm is developed based on Radon and inverse Radon transform which accounts for the linear feature of the targets in sea clutter. After Radon transform the SCR is increased and clutter can be suppressed more easily in Radon domain. Then the data in Radon domain can be inverse Radon transformed into time-range domain, and the target track can be detected. The simulation results show that the proposed algorithm makes the detection of very small targets possible.

Seismic data processing is essential in hydrocarbon exploration, with normal moveout (NMO) correction being a pivotal step in enhancing seismic signal quality. However, conventional NMO correction often suffers from the stretch effect, which distorts seismic reflections and degrades data quality, especially in long-offset data. This study addresses the issue by analyzing synthetic models and proposing a nonhyperbolic stretch-free NMO correction technique. The proposed method significantly improves seismic data quality by preserving up to 90% of the original amplitude, maintaining frequency content stability at 30 Hz, and achieving a high reduction of stretch-related distortions. Compared to conventional NMO, our technique results in clearer seismic gathers, enhanced temporal resolution, and more accurate velocity models. These improvements have substantial implications for high-resolution subsurface imaging and precise reservoir characterization.This work offers a robust and computationally efficient solution to a longstanding limitation in seismic processing, advancing the reliability of exploration in geologically complex environments.

The time-invariant Radon transform (RT) is commonly used to regularize and interpolate sparsely sampled or irregularly acquired prestack seismic data. The sparseness of the Radon model significantly influences the results of regularization. We have developed an effective and efficient method for the regularization and interpolation of 2D as well as 3D prestack seismic data. We used an accelerated sparse time-invariant RT in the mixed frequency-time domain to improve the performance of RT-based seismic data regularization. This 2D sparse RT incorporated the iterative 2D model shrinkage algorithm instead of the traditional iteratively reweighted least-squares (IRLS) algorithm in the time domain, and we computed the forward and inverse RTs in the frequency domain to solve the sparse inverse problem, which dramatically reduced the computational cost while obtaining a high-resolution result. The 2D synthetic and real data examples revealed that our 2D approach can better interpolate beyond aliasing a 2D prestack seismic record that contains a large gap, compared with the least-squares-based RT and the frequency-domain sparse RT methods. To extend the 2D technique to 3D more efficiently, we first formulate the 3D RT as a problem of solving a special matrix equation. Next, we use the iterative 3D model shrinkage algorithm to obtain a high-resolution 3D Radon model. The proposed 3D sparse RT method can be applied in the regularization of 3D prestack gathers, such as in the cable interpolation in a 3D marine survey. We achieved robustness and effectiveness with our 3D approach with successful applications to 3D synthetic and real data.

Seismic waves split in an anisotropic medium, instead of rotating horizontal component to principal direction, Radon-Fourier is derived to observe the signature of shear wave reflection. Synthetic model with fracture is built and discretized using finite difference scheme for spatial and time domain. Common depth point (CDP) with single shot gives traces and automatic gain is preprocessed before Radon Transform (RT), a filtering technique gives radon domain. It makes easier to observe fractures at specific incidence and improves its quality in some way by removing the noise. A comparison of synthetic data and BF-data is performed on the basis of root means square error (RMS) values. The RMS error is minimum at the 10 th trace in radon domain.

Two-way traveltime (TWT) is one of the most important seismic attributes for reservoir characterization. Erroneous analysis of TWT can lead to incorrect estimates of velocity models resulting in improper structural interpretation of the subsurface. TWT analysis starts with the most fundamental step of seismic data processing, namely, normal moveout (NMO) correction. NMO correction is generally performed in the offset-time (X-t) domain, by fitting a hyperbolic curve to the observed traveltimes corresponding to each reflection event. The commonly used NMO equation is valid for small offsets and does not consider anisotropy — an effect commonly observed in fractured media. The performance of NMO correction depends on the quality of data in the prestack domain and the underlying geology. In the plane wave (τ-p) domain, the estimation of layer parameters can be done using an exact equation for delay-time free from the approximation errors present in the X-t domain. In this domain, a layer stripping approach can also be used to account for the presence of multiple anisotropic and isotropic layers.

Interbed multiples occur in all types of seismic datasets and are difficult to address. These multiples can appear very similar to primaries due to comparable velocities, and may be difficult to differentiate from primary energy and/or distort the amplitude of primary reflections. Interbed multiple prediction (IMP)-based on the 1D earth assumption and applied to post-migration gathers has been partially successful in removing these complex multiples, but cannot be considered a full solution as it is applied late in the seismic data processing sequence, limiting the derivation of an accurate velocity, which is critical for imaging, time or depth, and for further reservoir characterization. This problem is further compounded in onshore and OBC seismic data. These, in general, have wide acquisition geometries and suffer from poor sampling, especially for shallow reflectors, which adds to the challenges of multiple attenuation. In this paper, two complimentary data-driven multiple attenuation techniques are discussed (Deterministic interbed demultiple (DID) and Extended interbed multiple prediction (XIMP)). These address the various challenges posed by the complexity of acquired data and the generated interbed multiples. We demonstrate complementary approaches to address the challenges of interbed multiple attenuation in land and OBC environment and show a case studies from seismic datasets. As there is little or no discrimination in velocity or dip, multiples cannot be easily attenuated using conventional methods based on periodicity and velocity or dip discrimination. To address the specific challenges of each survey, a careful analysis of the data is required and usually a combination of methods and approaches is the best solution. DID and XIMP are methods that naturally complement each other, allowing compensation for the limitations of land and OBC geometries and addressing the full interval of the multiple generators from top to bottom of the section. Theory In this paper, two methods to attenuate interbed multiples are discussed.Deterministic interbed demultiple (DID).Extended interbed multiple prediction (XIMP). DID is a deterministic method of predicting the internal multiples that are created by a single layer in the earth's subsurface. Originally designed to handle shallow water-column-related multiples (Moore and Bisley, 2006), it was later adapted to attenuate interbed multiples. The prediction is accomplished by a wavefield extrapolation. The method predicts all multiples created by a targeted layer as shown in Figure 1. DID requires a model of the layer, including estimated reflection coefficients at top and bottom. The main assumption of the method is that the layer has a moderate complexity within the 3D gather. In other words, DID relies on a local 1D assumption for the layer. Nevertheless, it does account properly for the non-periodic moveout of multiples in traces at non-zero offsets. Because the layer is assumed to be flat, there are no azimuthal effects accounted for by the multiple prediction. DID works with 3D gathers and outputs multiple models for each trace of the input data. Overall, it can form a reliable 3D model as long as geological complexity is moderate.

A simple shearlet-based 2D Radon inversion with an application to computed tomography

<p>Reducing multiple contaminations in reflection seismic data remains one of the greatest challenges in seismic processing and its effectiveness is highly dependent on geologic settings. We undertook two-dimensional reflection seismic data crossing the upper and lower accretionary wedge slopes off SW Taiwan to test the efficiency of various multiple-attenuation scenarios. The area has resulted from an incipient arc-continent collision between the northern rifted margin of the South China Sea and the Luzon volcanic arcs. The wedge extends from shallow water to deep water bathymetries, hence promoting both short-period and long-period multiples within the seismic records. The multichannel seismic data were achieved under 468 hydrophones, 4-ms sampling rate, 12.5-m channel spacing, 50-m shot spacing and 15-second recording length. Preprocessing flow includes swell noise removal, direct wave mute, and missing channel and shot restoration. A subset of demultiple methods based on the periodicity nature and the spatial move-out behavior of multiples were explored to attenuate multiples energy under different geologic environments. The first step relies on the simultaneous subtraction of surface-related multiples, which combined wave-equation multiple attenuation (WEMA) and surface-related multiple elimination (SRME). WEMA is a shot domain multiple attenuations based on a combination of numerical wave extrapolation through the water layer and the water bottom reflectivity. This method was capable to partially suppress the water layer multiples. SRME was applied to attenuate the residual multiple energy at near-offset. This method assumes surface-related multiples can be kinematically predicted by convolution of prestack seismic traces at possible surface multiple reflection locations. Some primary reflections seem to be better retained after the combined subtraction process than using WEMA or SRME filtering independently. The second step lies on parabolic Radon transform to attenuate far-offset multiples by subtracting the noise energy in <em>tau-p</em> on input gathers that have been corrected for normal move-out and inverse transform the remaining primary energy back to CMP-offset domain. Predictive deconvolution in the <em>x-t</em> domain was performed to attenuate low-frequency reverberations in the upper wedge slope. A double-gap deconvolution operator was extended to predict reverberations with correct relative amplitudes, followed by time-variant bandpass filtering to reduce much of residual multiple energy. In general, WEMA and predictive deconvolution were more effective in attenuating the multiples energy at the upper wedge slope where the water depths are shallower; whereas SRME and parabolic Radon were capable of reducing the energy of multiples at the lower wedge slope. Nevertheless, multiples energy could not be fully eliminated due to several factors. The dependency of some demultiple methods (e.g. parabolic Radon, WEMA, SRME) on velocity function may perturb the forward multiple predictions before subtraction as primary velocities might not be present due to the highly tilted strata in the thrust belts domain. Furthermore, parabolic Radon may not perform well in shallow water and area with slowly increasing velocities with depth (e.g. the upper wedge slope). Since the reflection seismic dataset spans various tectonic environments and water depth, results suggest there was no single demultiple method capable to suppress multiples in all environments.</p>

X-ray computed tomography (CT) reconstruction with sparse projection views was proposed to reduce both the radiation dose and scan time. However, lacking of sufficient projection views may lead to severe artifacts for analytical reconstruction method such as the filtered back projection (FBP). Although the projection data is incomplete, we can generate the full-sampling system matrices according to the sufficient-sampling conditions [5]. Thus, we propose a novel iterative reconstruction model to fit the target images and the corresponding high resolution measurements in Radon domain by the full-sampling system matrices. Our proposed model is solved by the learned alternating minimization method, which accounts for a forward operator in deep neural network by the unrolling strategy. Numerical results demonstrate that the proposed approach outperforms some latest learning based reconstruction methods for the sparse-view CT problems.

The Longnan mountainous area, characterized by its complex geological structure and fragile geological environment, is one of the four major regions in China prone to geological disasters. Previous studies have employed traditional evaluation methods to assess landslide susceptibility in the Longnan mountainous area. However, these traditional methods are often subjective, and their accuracy and efficiency are difficult to guarantee. This study, supported by GIS technology, focuses on Wen County in Longnan City, a region frequently affected by landslide disasters. Based on 260 collected landslide disaster points, the study combines the ReliefF model to evaluate and zone landslide susceptibility in Wen County, Longnan City, based on feature contribution values. The lithology and rainfall factors have significant impacts on geological disasters, respectively. Areas along rivers and roads, with loose soil, heavy rainfall, steep slopes, and dense vegetation, are more prone to landslide disasters due to the combined effects of natural factors and human activities. This study also uses the receiver operating characteristic (ROC) curve to validate the accuracy of the evaluation results. The area under the curve (AUC) for the ReliefF feature fusion method is 0.853, which is higher than the 0.838 obtained from the information value method. The ReliefF method demonstrates excellent performance in landslide susceptibility evaluation, offering better predictive capability at a lower computational cost, thus achieving a balance between accuracy and efficiency. This approach can provide valuable references for rapid decision-making by relevant geological disaster prevention and management departments.