Seismic expression of the Upper Morrow sands, western Anadarko Basin

Geophysics ◽  
1988 ◽  
Vol 53 (3) ◽  
pp. 290-303 ◽  
Author(s):  
Jens R. Halverson
Keyword(s):  
Seismic Data ◽  
Seismic Inversion ◽  
Seismic Facies ◽  
Excellent Correlation ◽  
Signal To Noise ◽  
Anadarko Basin ◽  
One Dimensional ◽  
Impedance Contrast ◽  
Mapping Techniques ◽  
Good Signal

In the western Anadarko Basin, the Lower Pennsylvanian Upper Morrow sands are both a prolific and an elusive exploration target. Initial production from some of these sands can reach well over 1000 barrels of oil per day, and yet an offset well just 350 m away from a good producer can miss the Morrow sand entirely and result in a dry hole. One‐dimensional merged log modeling, two‐ dimensional log interpolation modeling, color seismic inversion processing, and seismic facies mapping techniques have been applied to the Lear and Darden fields, two Upper Morrow sand fields in the Texas Panhandle. Here the Morrow sands reach an isopach thickness of 10 to 15 m at a depth of 2500 to 3000 m. These Morrow sands are within the thin‐bed regime (below the tuning point) so that there is a correlation between the amplitude of the reflection and the thickness of the sand. The velocity and density contrasts of the shales and sands are sufficient to produce a good acoustic impedance contrast, making the sands detectable on seismic data with good signal‐to‐noise ratios. The comparison of geologic isopach mapping and geophysical seismic facies mapping shows an excellent correlation in the delineation of the Upper Morrow sands.

A method of ground‐roll elimination

Geophysics ◽  
1988 ◽  
Vol 53 (7) ◽  
pp. 894-902 ◽  
Author(s):  
Ruhi Saatçilar ◽  
Nezihi Canitez
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Wave Motion ◽  
Frequency Interval ◽  
Vertical Resolution ◽  
Matched Filters ◽  
One Dimensional ◽  
Frequency Bands ◽  
Ground Roll ◽  
Seismic Reflections

Amplitude‐ and frequency‐modulated wave motion constitute the ground‐roll noise in seismic reflection prospecting. Hence, it is possible to eliminate ground roll by applying one‐dimensional, linear frequency‐modulated matched filters. These filters effectively attenuate the ground‐roll energy without damaging the signal wavelet inside or outside the ground roll’s frequency interval. When the frequency bands of seismic reflections and ground roll overlap, the new filters eliminate the ground roll more effectively than conventional frequency and multichannel filters without affecting the vertical resolution of the seismic data.

Integrated VTI model building with seismic data, geologic information, and rock-physics modeling — Part 1: Theory and synthetic test

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. C177-C191 ◽  
Author(s):  
Yunyue Li ◽  
Biondo Biondi ◽  
Robert Clapp ◽  
Dave Nichols
Keyword(s):  
Seismic Data ◽  
Seismic Anisotropy ◽  
Model Building ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Additional Information ◽  
Synthetic Test ◽  
Rock Physics Modeling ◽  
Physics Modeling ◽  
Geologic Information

Seismic anisotropy plays an important role in structural imaging and lithologic interpretation. However, anisotropic model building is a challenging underdetermined inverse problem. It is well-understood that single component pressure wave seismic data recorded on the upper surface are insufficient to resolve a unique solution for velocity and anisotropy parameters. To overcome the limitations of seismic data, we have developed an integrated model building scheme based on Bayesian inference to consider seismic data, geologic information, and rock-physics knowledge simultaneously. We have performed the prestack seismic inversion using wave-equation migration velocity analysis (WEMVA) for vertical transverse isotropic (VTI) models. This image-space method enabled automatic geologic interpretation. We have integrated the geologic information as spatial model correlations, applied on each parameter individually. We integrate the rock-physics information as lithologic model correlations, bringing additional information, so that the parameters weakly constrained by seismic are updated as well as the strongly constrained parameters. The constraints provided by the additional information help the inversion converge faster, mitigate the ambiguities among the parameters, and yield VTI models that were consistent with the underlying geologic and lithologic assumptions. We have developed the theoretical framework for the proposed integrated WEMVA for VTI models and determined the added information contained in the regularization terms, especially the rock-physics constraints.

scholarly journals Batch seismic inversion using the iterative ensemble Kalman smoother

2021 ◽  
Author(s):  
Michael Gineste ◽  
Jo Eidsvik
Keyword(s):  
Seismic Data ◽  
Time Windows ◽  
Seismic Inversion ◽  
Efficient Estimation ◽  
Solution Strategy ◽  
Adaptive Procedure ◽  
Waveform Data ◽  
Kalman Smoother ◽  
Seismic Waveform ◽  
Single Batch

AbstractAn ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main focus of this work is the challenge associated with ensemble-based inversion of seismic waveform data. The amount of seismic data is large and, depending on ensemble size, it cannot be processed in a single batch. Instead a solution strategy of partitioning the data recordings in time windows and processing these sequentially is suggested. This work demonstrates how this partitioning can be done adaptively, with a focus on reliable and efficient estimation. The adaptivity relies on an analysis of the update direction used in the iterative procedure, and an interpretation of contributions from prior and likelihood to this update. The idea is that these must balance; if the prior dominates, the estimation process is inefficient while the estimation is likely to overfit and diverge if data dominates. Two approaches to meet this balance are formulated and evaluated. One is based on an interpretation of eigenvalue distributions and how this enters and affects weighting of prior and likelihood contributions. The other is based on balancing the norm magnitude of prior and likelihood vector components in the update. Only the latter is found to sufficiently regularize the data window. Although no guarantees for avoiding ensemble divergence are provided in the paper, the results of the adaptive procedure indicate that robust estimation performance can be achieved for ensemble-based inversion of seismic waveform data.

Estimating Optimum Filter Length in Linear Prediction

1997 ◽  
Vol 51 (5) ◽  
pp. 718-720 ◽  
Author(s):  
O.-P. Sievänen
Keyword(s):  
Raman Spectra ◽  
Prediction Error ◽  
Linear Prediction ◽  
Signal To Noise Ratio ◽  
New Method ◽  
Signal To Noise ◽  
Filter Length ◽  
Optimum Filter ◽  
Good Signal ◽  
Prediction Filter

In this article a new method to estimate optimum filter length in linear prediction is described. Linear prediction was used to enhance resolution of a spectrum. In particular, the dependence of prediction error on filter length has been studied. With calculations of simulated spectra it is shown that the prediction error falls rapidly when the filter length attains its optimum value. This effect is quite pronounced when the spectrum has a good signal-to-noise ratio and the modified covariance method is used to calculate prediction filter coefficients. The method is illustrated with applications to real Raman spectra.

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