The S/N evaluation of high‐density seismic data after bin—divisible processing

Key technologies for complex surface seismic acquisition in the Sichuan Basin and their application effect

Seismic data usually contain various types of noise. Noise comes from signal collection environment, equipment (current noise), micro seismic, etc. Noise reduces the signal- to-noise ratio and resolution of seismic records, and affects the accuracy of seismic processing and stratigraphic interpretation. Improving the signal-to-noise ratio of seismic data is the primary task of seismic data processing. In practical research, many algorithms for suppressing random noise interference are proposed. In order to achieve better seismic data denoising technology, this paper introduces a new algorithm: improved shearlet transform algorithm. The basic principle of this algorithm is to perform shearlet transform on noisy seismic data, calculate the L2 norm of shearlet coefficients in different directions at each scale according to the distribution law of effective signals at different scales, and remove random noise according to the adaptive threshold in shearlet domain varying with scale and direction. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2022 in Houston, Texas.

Seismic data processing plays a key role in the field of geophysics. The collected seismic data are inevitably contaminated by various types of noise, which makes the effective signals difficult to be accurately discriminated. A fundamental issue is how to improve the signal-to-noise ratio of seismic data. Due to the complex characteristics of noise and signals, it is a challenge for the denoising model to suppress noise and recover weak signals. To suppress random noise in seismic data, we propose a multi-scale deformable convolution neural network denoising model based on U-Net, named MSDC-Unet. The MSDC-Unet mainly contains modules of deformable convolution and dilated convolution. The deformable convolution can change the shape of the convolution kernel to adjust the shape of seismic signals to fit different features, while the dilated convolution with different dilation rates is used to extract feature information at different scales. Furthermore, we combine Charbonnier loss and structure similarity index measure (SSIM) to better characterize geological structures of seismic data. Several examples of synthetic and field seismic data demonstrate that the proposed method is effective in the comprehensive results in terms of quantitative metrics and visual effect of denoising, compared with two traditional denoising methods and two deep convolutional neural network denoising models.

The collection of a range of different seismic data types has greatly improved our understanding of the crustal architecture of Australia's Archaean Yilgarn Craton over the last few years. These seismic data include broadband seismic studies, seismic receiver functions, wide-angle recordings and mine-scale to deep seismic reflection transects. Each data set provides information on the three-dimensional (3D) tectonic model of the Yilgarn Craton from the craton scale through to the mine scale. This paper demonstrates that the integration and rationalisation of these different seismic data sets into a multi-scale 3D geological/seismic model, that can be visualised at once in a single software package, and incorporating all available data sets, significantly enhances this understanding. This enhanced understanding occurred because the integrated 3D model allowed easy and accurate comparison of one result against another, and facilitated the integrated questioning and interrogation across scales and seismic method. As a result, there are feedback questions regarding understanding of the individual seismic data sets themselves, as well as the Yilgarn Craton as a whole. The methodology used, including all the data sets in the model range, had to allow for the wide range of data sets, frequencies and seismic modes. At the craton scale, P-wave, S-wave and surface wave variations constrained the 3D lithospheric velocity model, revealing noticeable large-scale velocity variations within and across the craton. An interesting feature of the data, easily identified in 3D, is the presence of a fast S-wave velocity anomaly (> 4.8 km s − 1 ) within the upper mantle. This velocity anomaly dips east and has a series of step-down offsets that coincide approximately with province and terrane boundaries of the Yilgarn Craton. One-dimensional receiver function profiles show variations in their crustal velocity across the craton. These crustal velocity variations are consistent with the larger-scale geological subdivision of the craton, and provide characteristic profiles for provinces and terranes. The receiver function results and the deep seismic reflection data both agree on the depth to the Moho, and both indicate an increase in Moho depth to the east. The 2D seismic refraction results in the south-west of the craton provide crustal thickness information, an indication of middle and lower crustal compositions, and information regarding the broad-scale architectural framework. At the province- and terrane-scale, the deep seismic reflection data and the mine-scale seismic data provide geometric constraints on crustal architecture, in particular the orientation of the region's fault systems as well as variations in the thickness of the granite–greenstone succession. Integration of the results from wide-angle seismic refraction data coincident with the deep seismic reflection data provided additional constraints on likely upper crustal lithologies. The integrated 3D seismic model implies the dominant geodynamic process involved the development of an orogenic belt that developed with a series of contractional (folding and thrusting) events, separated by equally important extensional events. The seismic reflection data in particular suggests that extensional movement on many shear zones was more common than previously thought. The seismic reflection data suggest that the dominant mineral systems involved deeply sourced fluid flowing up crustal-penetrating shear zones. These deeply sourced fluids were further focussed into sites located above fault-breached domal regions in the upper crust.

Imaging Pleistocene volcanic edifices along the Egyptian Red Sea margin: Insights from reflection seismics and 3D constrained inversion of gravity and magnetic data

The undulating sand dunes in the Tadong region cause strong interferences in seismic da ta, which leads to poor signal-to-noise (S/N) when targeting the deeply-buried Lower Paleozoic carbonates. With respect to reducing and suppressing this interference from the sand dunes, we present methods for improving the S/N ratio of seismic data, including combining DEM data with a near-surface database for line selection, a point by point sand dune characterized geophone-array elevation difference design, and application of wide-line and a large geophone array together. Combined, these have achieved great improvement in the seismic data quality when applied in the Tadong region.

Ground-roll noise extraction and suppression using high-resolution linear Radon transform

Seismic data are increasingly required to be high quality for the continuous improvement of the degree of exploration. From the viewpoint of inversion, the utilization of more information is an effective way to improve the signal-to-noise ratio of seismic data. In this letter, we adopt simultaneous sparsity constraints of the first-order differences of signals along the time direction and two spatial directions, described by minimizing the Cauchy function, as a combined constraint (or regularization) term imposed on the time-domain data misfit to propose an inversion-based 3-D seismic denoising method. In this way, the redundancies among time slices and seismic sections along two spatial directions are simultaneously considered, and the edges along the spatial directions can be preserved. Through analyzing the first-order derivative of the sum of the data misfit term and the designed combined regularization term (or the objective function), we derive that the relationship between data and desired signal samples in the range of the first-order neighborhood can be expressed as a linear system with seven data-dependent coefficients. Furthermore, it can be inferred that the sparsity constraints of signal differences along different dimensional directions of 3-D data have some complementary functions of noise reduction and signal preservation. We use a 3-D synthetic data set, a 3-D real poststack data set, and a 3-D real prestack data set to determine that the proposed method is an effective amplitude-preservation denoising tool with an acceptable computational cost.

PreviousNext No AccessInternational Geophysical Conference, Beijing, China, 24-27 April 2018Application of multi-window dip scanning technique in the fault identification of carbonate rocks of Lower Ordovician, GC areaAuthors: Zhang ErhuaSong YongzhongJu LinboZhang ErhuaExploration and Development Research Institute of Daqing Oilfield Ltd.Search for more papers by this author, Song YongzhongExploration and Development Research Institute of Daqing Oilfield Ltd.Search for more papers by this author, and Ju LinboExploration and Development Research Institute of Daqing Oilfield Ltd.Search for more papers by this authorhttps://doi.org/10.1190/IGC2018-212 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract The reserving space of carbonate which locates in GC area, east of Tarim Basin is mainly secondary porosity, and the reservoir distribution is closely related to faults, so the identification of faults is very important. The vertical distance of strike-slip fault in this area is small and the signal-to-noise ratio of the seismic data is low, which give rise to difficulty to the fault identification inside carbonate rock. On the basis of structure oriented filtering which aims at improving the signal-to-noise ratio of seismic data, this paper uses the multi-window dip scanning technique to identify the characteristics of the faults inside the carbonate rock. Compared with the 3rd generation coherence, this method can recognize the faults with the direction of NNE and NW on the top surface of the limestone effectively and highlights the faults inside carbonate rocks. Keywords: Carbonate insider, Fault identification, Structure oriented filtering, Dip scanning with multi-windowPermalink: https://doi.org/10.1190/IGC2018-212FiguresReferencesRelatedDetails International Geophysical Conference, Beijing, China, 24-27 April 2018ISSN (online):2159-6832Copyright: 2018 Pages: 1821 publication data© 2018 Published in electronic format with permission by the Society of Exploration Geophysicists and Chinese Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished Online: 11 Dec 2018 CITATION INFORMATION Zhang Erhua, Song Yongzhong, and Ju Linbo, (2018), "Application of multi-window dip scanning technique in the fault identification of carbonate rocks of Lower Ordovician, GC area," SEG Global Meeting Abstracts : 870-872. https://doi.org/10.1190/IGC2018-212 Plain-Language Summary KeywordsCarbonate insiderFault identificationStructure oriented filteringDip scanning with multi-windowPDF DownloadLoading ...

Summary Seismic imaging is dependent on the quality of the seismic field record, with geometry playing a crucial role in the integrity of the seismic wave-field. Geometric parameters are therefore considered key in seismic image processing and resolution. Geometries with high density and wide azimuth are shown to improve the seismic image, however, the overhead coverage remains high. Our paper analyzes and compares the effects of varying geometries on the quality of seismic image by constructing a mathematic model from raw data, forward modeling, generating seismic data records of different geometries, processing the seismic data and getting the images of several geometries. The research aims to improve imaging in conditions where complicated structures and rough surface topography typically increase the difficulty in seismic acquisition and data processing. Our test results show that geometries with uniform and symmetrical spatial sampling of both source and receiver can also improve images from a pre-stack migration model and are advantageous in minimizing workload and cost.

Relevance of the work. The paper considers challenging problems related with outlining of intervals with oil and gas presence in the mature Khylly field by use of latest 3D seismic survey techniques in order to gain larger crude resources base. The purpose of this research is to discover the most promising intervals of target horizons with relatively high reservoir properties outlined by 3D seismic data. The subjects of research are 3D seismic survey data, downhole seismic survey – Vertical Seismic Profiling (VSP) and well logging diagrams. The object of research is the Khylly deposit. The paper describes in brief geological and geophysical characteristics, stratigraphic and lithological features of rocks making the section. It is noted that despite repeated surveys by use of various geological and geophysical techniques, the field setting is not thoroughly studied and it has been covered by 3D seismic survey in 2012. Research results. 3D seismic survey applied across Khylly area is resulted in drawing of 4 structural maps for III and I horizons of Productive Series (PS), Akchagyl and Lower Absheron suites. Taking into account the relevance of structural planes of various stratigraphic levels and III horizon of PS being one of the major reference horizons the paper gives description of structural map drawn for this horizon. The detailed velocity model is designed based on VSP data with wide use of velocity analysis data. It has been made clear that Khylly area has block structure and each block has been described in detail. Based on acquired data it has been recommended to drill exploratory well R-1. Conclusion. Processing and interpretation of seismic data are aimed at solving some geological problems; the main task was to obtain results that ensure the study of the geological structure in the seismic survey area, including tracing of seismic horizons, faults and outlining the areas and section intervals which may be of interest due to possible oil and gas presence. VSP data acquired in well 2012 and velocity analysis made it possible to design velocity model of the section under the study, with the use of which the temporary 3D cube was transformed into a depth cube. The quality of seismic data is good and made it possible to solve the tasks set for this research.

Seismic reflection and drill-hole data from central Syria provide a detailed view of the subsurface structure (10–15 km depth) of the relatively little-studied intracratonic Palmyride fold and thrust belt. The data set, together with surface geologic mapping, constrains a structural/stratigraphic section spanning the northeast sector of the belt and the surrounding subprovinces of the Arabian platform. The seismic reflection and drill-hole data show Mesozoic stratigraphic sequences thickening abruptly into the Palmyrides from the adjacent, arched Paleozoic platforms. Neogene (Alpine) folding and thrusting of the Mesozoic basin, as documented on the seismic data, are sharply restricted to the narrow width of the belt (~ 100 km), in contrast to the relatively undeformed Phanerozoic strata of the platforms to the north and south. The regional subsurface structure of the northeastern Palmyrides consists of a northeast-plunging anticlinorium whose outer flanks are marked by smaller superimposed asymmetrical anticlines associated with outward-verging thrusts, giving this part of the belt a rough symmetry. The general structural style of folding is characterized by simple, relatively narrow anticlines and broad synclines that can be traced concordantly from the surface to at least 5 km deep on the seismic data—the level of any decollement appears to be below the imaged Mesozoic sequence. A fundamental feature of the surrounding Arabian platform subprovinces is a deep (approximately 6–7 km, maximum) and pervasive bright reflector that forms the base of the reflective section of the platform but disappears abruptly beneath the Palmyrides. This basal reflector is important as a regional strain marker and may represent a Cambrian/Infracambrian carbonate-evaporite sequence or a remarkably uniform crystalline basement surface. The seismic and drill-hole data support the hypothesis that the Palmyrides began as a Permian–Triassic failed rift connected to the Levantine passive continental margin, which was inverted and complexly deformed by the interfering effects of Cenozoic movements along the Dead Sea transform fault system and the Turkish Bitlis convergent zone. The seismic data provide a first view into the extent and depth of the early basin formation and subsequent compressional deformation, and as such represent a necessary element for constraining reconstructions of northern Middle East plate motions.

Seismic reflection amplitude data are increasingly used in reservoir modeling to provide information on changes in earth properties away from well locations. In geostatistical reservoir modeling, the most common application is to use seismic data as background data in some form of comodeling. Seismic data image reflectors and not earth layer properties. Therefore, prior to use in comodeling, seismic data must first be transformed into an earth layer property. Typically, the transform is to acoustic impedance using an appropriate seismic inversion method. Seismic inversion methods generate results that are generally band limited in nature, resulting in limits to vertical resolution. The vertical resolution achieved can be an order of magnitude below the vertical model resolution required from geostatistical reservoir modeling, which is in the order of well-log resolution. Hence, in using seismic data, geostatistical modelers encounter a problem of downscaling, not the more commonly encountered upscaling problem. This difference in scale introduces scatter between the primary data with well-log order resolution and the secondary seismically derived rock property data used in the comodeling. As a result, to preserve vertical heterogeneity, only limited use of the secondary data can be made in comodeling procedures. This results in models that only partially fit the seismic data, i.e., only limited use is made of the seismic information. If the secondary data are more strongly imposed, the fit to the seismic data improves, but the required vertical heterogeneity is not preserved. The inability to overcome this difference in scale issue, therefore, limits the value of the application of comodeling methods to integrate seismic data into reservoir models. One class of geostatistical methods that overcomes this limitation relies on iterative geostatistical modeling. In these methods, referred to as geostatistical seismic inversion, the iterative modeling process is conditioned such that the final models generated closely match the seismic data while maintaining the required vertical heterogeneity. The application of these methods is computationally expensive relative to comodeling methods but is now practical for large models on today's desktop hardware. Relative to comodeling, geostatistical seismic inversion methods make full use of the information carried in the seismic data, resulting in a significant reduction in model uncertainty away from well control.

Enhancing the detection of small coal structures by seismic diffraction imaging

Deconvolution is an essential step in seismic data processing. Sparse-spike deconvolution often is used to enhance the resolution of the seismic image by adding a model-driven regularization term. However, this method does not consider the features of the data, nor does it exactly describe the relationship between seismic data and the desired attribute (such as seismic reflectivity). We have developed a data and model dual-driven seismic deconvolution method based on error-constrained joint sparse representation (SR) using borehole measurement and surface seismic data. The combined features of the borehole reflectivity and the surface seismic data can be obtained through joint dictionary learning. With the help of the joint dictionary, the relationship between seismic waveforms and reflectivity is captured by the sparse coefficients. We construct the regularization term of deconvolution by alternately decomposing the error of the synthesized data via sparse reconstruction and the observed seismic data. Unlike model-driven methods, the constraint term of the new method can be established by the error-constrained SR. Based on this SR, the initial model of reflectivity is obtained to realize the sparse deconvolution of seismic data under the constraint of borehole data features. In general, this method is a data and model dual-driven deconvolution. Synthetic and field data tests demonstrate that this method can effectively improve the resolution and accuracy of deconvolution.