Slant f-k transform of multichannel seismic surface wave data

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. A19-A24 ◽  
Author(s):  
Aleksander S. Serdyukov ◽  
Aleksander V. Yablokov ◽  
Anton A. Duchkov ◽  
Anton A. Azarov ◽  
Valery D. Baranov
Keyword(s):  
Surface Wave ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Velocity Estimation ◽  
Seismic Exploration ◽  
Spectral Processing ◽  
Near Surface ◽  
Frequency Time Representation ◽  
Time Representation ◽  
S Transform

We have addressed the problem of estimating surface-wave phase velocities through the spectral processing of seismic data. This is the key step of the well-known near-surface seismic exploration method, called multichannel analysis of surface waves. To increase the accuracy and ensure the unambiguity of the selection of dispersion curves, we have developed a new version of the frequency-wavenumber ([Formula: see text]-[Formula: see text]) transform based on the S-transform. We obtain the frequency-time representation of seismic data. We analyze the obtained S-transform frequency-time representation in a slant-stacking manner but use a spatial Fourier transform instead of amplitude stacking. Finally, we build the [Formula: see text]-[Formula: see text] image by analyzing the spatial spectra for different steering values of the surface-wave group velocities. The time localization of the surface-wave packet at each frequency increases the signal-to-noise ratio because of an exclusion of noise in other time steps (which does not fall in the effective width of the corresponding wavelet). The new [Formula: see text]-[Formula: see text] transform, i.e., the slant [Formula: see text]-[Formula: see text] (SFK) transform, renders a better spectral analysis than the conventional [Formula: see text]-[Formula: see text] transform and yields more accurate phase-velocity estimation, which is critical for the surface-wave analysis. The advantages of the SFK transform have been confirmed by synthetic- and field-data processing.

scholarly journals High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. U53-U63 ◽  
Author(s):  
Andrea Tognarelli ◽  
Eusebio Stucchi ◽  
Alessia Ravasio ◽  
Alfredo Mazzotti
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Synthetic Seismograms ◽  
Seismic Exploration ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Geologic Setting ◽  
Analytic Signals

We tested the properties of three different coherency functionals for the velocity analysis of seismic data relative to subbasalt exploration. We evaluated the performance of the standard semblance algorithm and two high-resolution coherency functionals based on the use of analytic signals and of the covariance estimation along hyperbolic traveltime trajectories. Approximate knowledge of the wavelet was exploited to design appropriate filters that matched the primary reflections, thereby further improving the ability of the functionals to highlight the events of interest. The tests were carried out on two synthetic seismograms computed on models reproducing the geologic setting of basaltic intrusions and on common midpoint gathers from a 3D survey. Synthetic and field data had a very low signal-to-noise ratio, strong multiple contamination, and weak primary subbasalt signals. The results revealed that high-resolution coherency functionals were more suitable than semblance algorithms to detect primary signals and to distinguish them from multiples and other interfering events. This early discrimination between primaries and multiples could help to target specific signal enhancement and demultiple operations.

Predictive removal of scattered noise

Geophysics ◽  
2006 ◽  
Vol 71 (2) ◽  
pp. V41-V49 ◽  
Author(s):  
Gérard C. Herman ◽  
Colin Perkins
Keyword(s):  
Mathematical Model ◽  
Wave Propagation ◽  
Surface Wave ◽  
Seismic Data ◽  
Coherent Noise ◽  
Data Set ◽  
Near Surface ◽  
Unique Data ◽  
Surface Wave Propagation ◽  
Petroleum Development

Land seismic data can be severely contaminated with coherent noise. We discuss a deterministic technique to predict and remove scattered coherent noise from land seismic data based on a mathematical model of near-surface wave propagation. We test the method on a unique data set recorded by Petroleum Development of Oman in the Qarn Alam area (with shots and receivers on the same grid), and we conclude that it effectively reduces scattered noise without smearing reflection energy.

Near-surface shear-wave velocity estimation based on surface-wave inversion

2016 ◽  
Vol 35 (11) ◽  
pp. 940-945 ◽  
Author(s):  
Peiming Li ◽  
Kui Zhang ◽  
Yimeng Zhang ◽  
Zhihui Yan
Keyword(s):  
Surface Wave ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Estimation ◽  
Surface Shear ◽  
Near Surface ◽  
Wave Inversion ◽  
Surface Shear Wave

Estimating randomness using seismic disorder

2014 ◽  
Vol 2 (1) ◽  
pp. SA93-SA97 ◽  
Author(s):  
Saleh Al-Dossary ◽  
Yuchun Eugene Wang ◽  
Mark McFarlane
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Hydrocarbon Exploration ◽  
Estimation Methods ◽  
Fracture Zones ◽  
Near Surface ◽  
Filter Operation ◽  
Gas Chimneys ◽  
Engineering Projects ◽  
Assess Data Quality

The new seismic disorder attribute quantitatively describes the degree of randomness embedded in 3D poststack seismic data. We compute seismic disorder using a filter operation that removes simple structures including constant values, constant slopes, and steps in axial directions. We define the power of the filtered data as the seismic disorder attribute, which approximately represents data randomness. Seismic data irregularities are caused by a variety of reasons, including random reflection, diffraction, near-surface variations, and acquisition noise. Consequently, the spatial distribution of the seismic disorder attribute may help hydrocarbon exploration in several ways, including identifying geologic features such as fracture zones, gas chimneys, and terminated unconformities; indicating the signal-to-noise ratio to assess data quality; and providing a confidence index for reservoir simulation and engineering projects. We present three case studies and a comparison to other noise-estimation methods.

Triangle Ranch Headquarters field development using shallow core holes and high‐resolution seismic data

Geophysics ◽  
1989 ◽  
Vol 54 (11) ◽  
pp. 1384-1396
Author(s):  
Howard Renick ◽  
R. D. Gunn
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Processing Parameters ◽  
Mapping Method ◽  
High Signal ◽  
Signal To Noise ◽  
Near Surface ◽  
Field Development ◽  
Reef Structure ◽  
Noise Ratio

The Triangle Ranch Headquarters Canyon Reef field is long and narrow and in an area where near‐surface evaporites and associated collapse features degrade seismic data quality and interpretational reliability. Below this disturbed section, the structure of rocks is similar to the deeper Canyon Reef structure. The shallow structure exhibits very gentle relief and can be mapped by drilling shallow holes on a broad grid. The shallow structural interpretation provides a valuable reference datum for mapping, as well as providing a basis for planning a seismic program. By computing an isopach between the variable seismic datum and the Canyon Reef reflection and subtracting the isopach map from the datum map, we map Canyon Reef structure. The datum map is extrapolated from the shallow core holes. In the area, near‐surface complexities produce seismic noise and severe static variations. The crux of the exploration problem is to balance seismic signal‐to‐noise ratio and geologic resolution. Adequate geologic resolution is impossible without understanding the exploration target. As we understood the target better, we modified our seismic acquisition parameters. Studying examples of data with high signal‐to‐noise ratio and poor resolution and examples of better defined structure on apparently noisier data led us to design an acquisition program for resolution and to reduce noise with arithmetic processes that do not reduce structural resolution. Combining acquisition and processing parameters for optimum structural resolution with the isopach mapping method has improved wildcat success from about 1 in 20 to better than 1 in 2. It has also enabled an 80 percent development drilling success ratio as opposed to slightly over 50 percent in all previous drilling.

Random noise attenuation by planar mathematical morphological filtering

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. V11-V25 ◽  
Author(s):  
Weilin Huang ◽  
Runqiu Wang
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Seismic Exploration ◽  
Noise Attenuation ◽  
Seismic Waveforms ◽  
Morphological Filtering ◽  
Alternative Techniques ◽  
The Difference ◽  
The Relationship

Improving the signal-to-noise ratio (S/N) of seismic data is desirable in many seismic exploration areas. The attenuation of random noise can help to improve the S/N. Geophysicists usually use the differences between signal and random noise in certain attributes, such as frequency, wavenumber, or correlation, to suppress random noise. However, in some cases, these differences are too small to be distinguished. We used the difference in planar morphological scales between signal and random noise to separate them. The planar morphological scale is the information that describes the regional shape of seismic waveforms. The attenuation of random noise is achieved by removing the energy in the smaller morphological scales. We call our method planar mathematical morphological filtering (PMMF). We analyze the relationship between the performance of PMMF and its input parameters in detail. Applications of the PMMF method to synthetic and field post/prestack seismic data demonstrate good performance compared with competing alternative techniques.

THREE-DIMENSIONAL DATA COLLECTION AND PROCESSING

1978 ◽  
Vol 18 (1) ◽  
pp. 116
Author(s):  
E. G. Selby
Keyword(s):  
Data Collection ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Depth Map ◽  
Seismic Survey ◽  
Seismic Exploration ◽  
Two Dimensional ◽  
Additional Advantage ◽  
Information Giving

There are many limitations in the ultimate accuracy of a conventional two dimensional seismic survey. One of the most important of these is that, in general, a prospect is not a two dimensional model but a three dimensional one. For a complete interpretation of a prospect area the final result should be a migrated time or depth map. With limited sampling (a seismic grid typically consists of loops with dimensions at least 1 km by 1 km) it is necessary to interpolate grid points to allow map migration and this method has inherent inaccuracies.The three dimensional seismic exploration technique is designed to provide a sufficiently close sampled grid of seismic traces, typically with a line and depth point spacing as close as 50-100 m, to allow the seismic data itself to be migrated three dimensionally. This allows the interpreter to work with migrated seismic sections and to contour directly the migrated map.Several techniques exist to allow practical and economic collection of seismic data to provide this close sampling. These techniques can be adapted to various terrain and cultural conditions.The main advantages of three dimensional data collection are correct imaging of the seismic information giving true vertical reflection time sections and improved signal-to-noise ratio due to the increased fold inherent in the three dimensional migration process. The additional advantage to the interpreter is that the data has a sampling which gives a line intersection at each depth point in the prospect.

Applying integrated seismic technology to complex foothill areas of foreland basins in China

2019 ◽  
Vol 38 (8) ◽  
pp. 597-603
Author(s):  
Yong Fang ◽  
Wenshan Luo ◽  
Xiaoxia Luo ◽  
Xukui Feng ◽  
Bo Zhao ◽  
...  
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
New Technologies ◽  
High Density ◽  
Hydrocarbon Exploration ◽  
Western China ◽  
Seismic Exploration ◽  
Foreland Basins ◽  
Near Surface ◽  
True Surface

Due to complicated near-surface conditions, including large elevation changes and complex geologic structures, accurate imaging of subsurface structures for hydrocarbon exploration in the foreland basins of western China has been challenging for many years. After decades of research and fieldwork, we developed an effective seismic exploration workflow that uses the latest technologies from acquisition to imaging. They include 3D high-density and wide-azimuth (WAZ) acquisition, 3D true-surface tilted transverse isotropy (TTI) anisotropic prestack depth migration, and dual-detachment structural modeling and interpretation. To further reduce uncertainty in velocity model building and improve imaging quality, our geologists, geophysicists, and reservoir engineers worked closely through the exploration cycle (seismic acquisition, processing, and interpretation). This exploration model has been used successfully in hydrocarbon exploration of many complex foothill areas in western China. Three-dimensional WAZ high-density seismic surveys have been conducted over 40,000 km2 of the foreland basins, greatly improving the field seismic data quality. After application of 3D true-surface TTI anisotropic depth model building and imaging with integrated structural interpretation, new discoveries of hydrocarbon reservoirs have increased. The application of new technologies not only increased drilling success but also reduced depth well-tie errors between seismic data and wells.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

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