Application of seismic reflection data to discriminate subsurface lithostratigraphy

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1498-1513 ◽  
Author(s):  
Amita Sinvhal ◽  
Kailash Khattri
Keyword(s):  
Discriminant Analysis ◽  
Seismic Reflection ◽  
Sedimentary Basin ◽  
Synthetic Data ◽  
Western India ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
One Step ◽  
Shaly Sand ◽  
Lithological Composition

A correlation between lithology and quantitative parameters abstracted from seismic reflection data is established. The concept and methodology developed on synthetic data has been successfully applied to discriminate between two different kinds of lithologies. A particular hydrocarbon‐bearing formation in a sedimentary basin in Western India has been considered, part of which is dominantly sandy (lithological composition: sand = 53 percent, shale = 21 percent, coal = 26 percent) and another part which is dominantly shaly (sand = 37 percent, shale = 60 percent, coal = 3 percent). These two different lithologies are mathematically modeled using one‐step Markov chains. Their seismic responses when scrutinized in time and frequency domain and subjected to statistical discriminant analysis give a fair idea about synthetic subsurface lithostratigraphy. Seismic reflection data from the same area were considered for a similar analysis. On subjecting the data to discriminant analysis, it was again possible to discriminate between the two lithologies. Also, seismograms from different areas of the same basin could be assessed in terms of subsurface lithology. Seven seismic discriminators of subsurface lithostratigraphy have been identified, three of which are abstracted from the autocorrelation function and four from the power spectrum of the seismogram. This analysis is a potential tool for diagnosing subsurface lithology from seismic data and may ultimately help discriminate an oil‐bearing stratigraphic trap from its barren surroundings in a sedimentary basin.

EXPLORATION HORIZONS FROM NEW SEISMIC CONCEPTS OF CDP AND DIGITAL PROCESSING

Geophysics ◽  
1967 ◽  
Vol 32 (2) ◽  
pp. 207-224 ◽  
Author(s):  
John D. Marr ◽  
Edward F. Zagst
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Synthetic Data ◽  
Digital Processing ◽  
Seismic Data Processing ◽  
Multiple Reflections ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Recent Developments

The more recent developments in common‐depth‐point techniques to attenuate multiple reflections have resulted in an exploration capability comparable to the development of the seismic reflection method. The combination of new concepts in digital seismic data processing with CDP techniques is creating unforeseen exploration horizons with vastly improved seismic data. Major improvements in multiple reflection and reverberation attenuation are now attainable with appropriate CDP geometry and special CDP stacking procedures. Further major improvements are clearly evident in the very near future with the use of multichannel digital filtering‐stacking techniques and the application of deconvolution as the first step in seismic data processing. CDP techniques are briefly reviewed and evaluated with real and experimental data. Synthetic data are used to illustrate that all seismic reflection data should be deconvolved as the first processing step.

Improving Q estimates from seismic reflection data using well‐log‐based localized spectral correction

Geophysics ◽  
2004 ◽  
Vol 69 (6) ◽  
pp. 1521-1529 ◽  
Author(s):  
Chris L. Hackert ◽  
Jorge O. Parra
Keyword(s):  
Seismic Reflection ◽  
Synthetic Data ◽  
Correction Method ◽  
South Florida ◽  
Test Case ◽  
Well Log ◽  
Seismic Line ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Q Values

Most methods for deriving Q from surface‐seismic data depend on the spectral content of the reflection. The spectrum of the reflected wave may be affected by the presence of thin beds in the formation, which makes Q estimates less reliable. We incorporate a method for correcting the reflected spectrum to remove local thin‐bed effects into the Q‐versus‐offset (QVO) method for determining attenuation from seismic‐reflection data. By dividing the observed spectrum by the local spectrum of the known reflectivity sequence from a nearby well log, we obtain a spectrum more closely resembling that which would be produced by a single primary reflector. This operation, equivalent to deconvolution in the time domain, is demonstrated to be successful using synthetic data. As a test case, we also apply the correction method to QVO with a real seismic line over a south Florida site containing many thin sandstone and carbonate beds. When corrected spectra are used, there is significantly less variance in the estimated Q values, and fewer unphysical negative Q values are obtained. Based on this method, it appears that sediments at the Florida site have a Q near 33 that is roughly constant from 170‐ to 600‐m depth over the length of the line.

Deep seismic reflection data interpretation using balanced filtering method

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. N43-N49 ◽  
Author(s):  
Jin Zhang ◽  
Yanguo Wang ◽  
David C. Nobes ◽  
Guangnan Huang ◽  
Hongxing Li
Keyword(s):  
Seismic Reflection ◽  
Synthetic Data ◽  
Data Interpretation ◽  
Seismic Events ◽  
Seismic Reflection Data ◽  
Deep Seismic Reflection ◽  
Filtering Method ◽  
Reflection Data ◽  
Text Filtering ◽  
Seismic Records

Inverse [Formula: see text] filtering can perform energy compensation and phase correction of seismic reflection data, but it has an instability problem due to its high-pass characteristics. Although improved methods, such as gain-limited inverse [Formula: see text] filtering and stabilized inverse [Formula: see text] filtering, overcome the instability to some extent, they are not suitable for compensating deep seismic reflection events with weak energy. Focusing on the enhancement of deep seismic events, we have developed a balanced filtering method based on the ratio of the phase-compensated signal to its analytic signal counterpart. The method is insensitive to the depth of seismic records, and it can make shallow and deep seismic records visible simultaneously. When tested on synthetic data and real seismic data, compared with other methods, the balanced filtering method improves the amplitude strength of the deep reflection events and the continuity of shallow and deep seismic events effectively, which makes the deep reflection data easier to interpret.

Stereotomography of seismic data acquired on undulant topography

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. U35-U41 ◽  
Author(s):  
Changkun Jin ◽  
Jianzhong Zhang
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Synthetic Data ◽  
Topographic Effects ◽  
Seismic Reflection Data ◽  
West China ◽  
Depth Migration ◽  
Velocity Models ◽  
Reflection Data ◽  
Rugged Topography

Stereotomography is a robust method for building velocity models from seismic reflection data, and it has been applied to offshore seismic data, but there is almost no stereotomographic study with rugged topographic conditions. We study the topographic effects on the slopes of locally coherent events of seismic data and develop an approach to calculate the slopes on an undulant observation surface using the horizontal and vertical components of slowness vectors estimated. Then, we develop an extended stereotomography with undulant observation surface based on the conventional one. Tests on synthetic data validate the extended stereotomography. Application to the field seismic data in a foothill belt in Xinjiang of the West China indicates that the extended stereotomography is an effective tool to build velocity models for prestack depth migration of seismic data acquired on rugged topography.

Automated stacking of seismic reflection data based on nonrigid image matching

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. V171-V183 ◽  
Author(s):  
Sönke Reiche ◽  
Benjamin Berkels
Keyword(s):  
Image Matching ◽  
Seismic Reflection ◽  
Synthetic Data ◽  
Real Data ◽  
Seismic Line ◽  
Seismic Reflection Data ◽  
Velocity Models ◽  
Reflection Data ◽  
Seismic Image ◽  
Matching Techniques

Stacking of multichannel seismic reflection data is a crucial step in seismic data processing, usually leading to the first interpretable seismic image. Stacking is preceded by traveltime correction, in which all events contained in a common-midpoint (CMP) gather are corrected for their offset-dependent traveltime increase. Such corrections are often based on the assumption of hyperbolic traveltime curves, and a best fit hyperbola is usually sought for each reflection by careful determination of stacking velocities. However, assuming hyperbolic traveltime curves is not accurate in many situations, e.g., in the case of strongly curved reflectors, large offset-to-target-ratios, or strong anisotropy. Here, we found that an underlying model parameterizing the shape of the traveltime curve is not a strict necessity for producing high-quality stacks. Based on nonrigid image-matching techniques, we developed an alternative way of stacking, both independent of a reference velocity model and any prior assumptions regarding the shape of the traveltime curve. Mathematically, our stacking operator is based on a variational approach that transforms a series of seismic traces contained within a CMP gather into a common reference frame. Based on the normalized crosscorrelation and regularized by penalizing irregular displacements, time shifts are sought for each sample to minimize the discrepancy between a zero-offset trace and traces with larger offsets. Time shifts are subsequently exported as a data attribute and can easily be converted to stacking velocities. To demonstrate the feasibility of this approach, we apply it to simple and complex synthetic data and finally to a real seismic line. We find that our new method produces stacks of equal quality and velocity models of slightly better quality compared with an automated, hyperbolic traveltime correction and stacking approach for complex synthetic and real data cases.

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