# SEP-110 (2001)

## Download

Book (pdf)

## Imaging

### Amplitude preserving prestack imaging of irregularly sampled 3-D data

(ps.gz 1336K) (pdf 1283K) (src 9837K)

**Biondi B. and Vlad I.**

We introduce a computationally efficient and robust method to regularize acquisition geometries of 3-D prestack seismic data before prestack migration. The proposed method is based on a formulation of the geometry regularization problem as a regularized least-squares problem. The model space of this least-squares problem is composed of uniformly sampled common offset-azimuth cubes. The regularization term fills the acquisition gaps by minimizing inconsistencies between cubes with similar offset and azimuth. To preserve the resolution of dipping events in the final image, the regularization term includes a transformation by Azimuth Moveout (AMO) of the common offset-azimuth cubes. The method is computationally efficient because we applied the AMO operator in the Fourier-domain, and we precondition the least-squares problem. Therefore, no iterative solution is needed and excellent results are obtained by applying the adjoint operator followed by a diagonal weighting in the model domain. We tested the method on a 3-D land data set from South America. Subtle reflectivity features are better preserved after migration when the proposed method is employed as compared to more standard geometry regularization methods. Furthermore, a dipping event at the reservoir depth (more than 3 km) is better imaged using the AMO regularization as compared to a regularization operator that simply smoothes the data over offsets.

Wave-equation prestack depth migration for sub-basalt P and converted wave imaging

(ps.gz 1953K) (pdf 1709K) (src 28765K)

**Brown M., Biondi B., and Kostov C.**

We apply 2-D wave-equation prestack depth migration to a North Sea basalt dataset. High velocity and impedance contrasts across a basalt layer causes low *P*-wave reflection signal-to-noise ratio under the basalt. We first migrate the *P*-wave data with a provided depth velocity model, and then replace sub-basalt *P*-wave velocity with a simple estimate of shear wave velocity and migrate locally-converted shear waves. Angle domain common image gathers assist our interpretation of a sub-basalt converted wave.

Time-reversal acoustics and maximum-entropy imaging

(ps.gz 74K) (pdf 87K) (src 72K)

**Berryman J. G.**

Target location is a common problem in acoustical imaging using either passive or active data inversion. Time-reversal methods in acoustics have the important characteristic that they provide a means of determining the eigenfunctions and eigenvalues of the scattering operator for either of these problems. Each eigenfunction may often be approximately associated with an individual scatterer. The resulting decoupling of the scattered field from a collection of targets is a very useful aid to localizing the targets, and suggests a number of imaging and localization algorithms. Two of these are linear subspace methods and maximum-entropy imaging.

Stolt residual migration for converted waves

(ps.gz 509K) (pdf 458K) (src 3485K)

**Rosales D., Sava P., and Biondi B.**

*PS* velocity analysis is a new frontier in converted-waves seismic imaging. To obtain one consistent image, it is necessary to estimate correctly both the P-waves velocity model and the S-waves velocity model. Stolt residual migration is a useful technique for image update and velocity analysis. This paper extends Stolt prestack residual migration in order to handle two different velocity fields. The operator that we introduce is promising for *PS* velocity analysis. We present a theoretical discussion of our new operator, and discuss its ability to focus *PS* images.

Effective AMO implementation in the log-stretch, frequency-wavenumber domain

(ps.gz 182K) (pdf 160K) (src 687K)

**Vlad I. and Biondi B.**

Azimuth moveout (AMO), introduced by Biondi et al. (1998), is used as part of the styling goal (in conjunction with a derivative as a roughener) in Biondi and Vlad (2001). This paper describes the implementation of AMO for the above-stated purpose, with a historical background, proof, and discussion of pitfalls and practical steps.

...

On asymmetric Stolt residual migration for imaging under salt edges

(ps.gz 109K) (pdf 346K) (src 1970K)

**Rosales D. and Biondi B.**

Imaging under salt remains a problem for the oil industry Muerdter et al. (1996); Prucha et al. (1998) due to illumination problems and poor velocity resolution under the salt body. Residual Stolt migration is a proved technique for updating the image and the velocity field Sava (1999), because of that ...

## Velocity

### Data dependent parameterization and covariance calculation for inversion of focusing operators

(ps.gz 1531K) (pdf 1611K) (src 3036K)

**Cox B. E.**

The Common Focus Point (CFP) method makes it possible to convert conventional two way traveltimes to focusing operators that represent one way traveltimes. These focusing operators are inverted to obtain a velocity model. The under-determined nature of the inversion problem is addressed by the data dependent adjustment of the parameterization by means of the a posteriori covariance. This results in an efficient, non-laborious algorithm producing well determined inversion problems. The required a posteriori covariance is normally explicitly solved in the explicit matrix calculation during optimization. However, these explicit calculations are not feasible in larger problems. Fortunately, algorithms have been proposed to extract the a posteriori covariance from the more efficient approximate matrix inversion algorithms that are available.

Born-compliant image perturbation for wave-equation migration velocity analysis

(ps.gz 528K) (pdf 540K) (src 3355K)

**Sava P. and Biondi B.**

Wave-equation migration velocity analysis produces wrong results if it starts from an image perturbation which is not compliant with the assumed Born approximation. Earlier attempts to correct this problem lead to either unreliable or hard to implement solutions. In this paper, we present a new method designed to construct image perturbations that are always compliant with the Born approximation. This new method is robust, easy to implement, and produces results that are consistent with those obtained using the ideal operators.

Ray-based tomography with limited picking

(ps.gz 2260K) (pdf 2001K) (src 12462K)

**Clapp R. G.**

In ray-based reflection tomography picking reflectors is an integral and painful part of the process Clapp (2001); Kosloff et al. (1996); Stork (1992); van Trier (1990). The general methodology is to pick a series of reflectors from a migrated image. A set of rays are then calculated ...

## Filtering

### A new multiscale prediction-error filter for sparse data interpolation

(ps.gz 118K) (pdf 157K) (src 1568K)

**Curry W. and Brown M.**

Prediction-error filters (PEFs) have been used to successfully interpolate seismic data. Using conventional methods, PEFs often cannot be estimated on sparse, irregularly sampled data. We implement an algorithm in which we resample the data to various scales to estimate a single PEF. We show that compared to PEFs estimated from single data scales, our PEF provides a robust first guess for a nonlinear interpolation scheme.

Estimation of systematic errors in tracked datasets using least squares crossing point analysis

(ps.gz 2109K) (pdf 1861K) (src 20851K)

**Brown M.**

Geophysical data often contains both systematic and random errors. If left unchecked, the systematic errors can cause acquisition footprint in the final map. I present a method to estimate systematic error by analyzing measurements at points where two acquisition swaths cross. I then subtract the estimated systematic error from the data and generate a map with a familiar least squares formulation. I test the method on bathymetric data from the Sea of Galilee. Compared to two previous least squares formulations, my new method produces final maps which are relatively free of acquisition footprint, and which exhibit preservation of underlying bathymetric features.

Whitening track residuals with PEFs in IRLS approach to the Sea of Galilee

(ps.gz 1899K) (pdf 1578K) (src 26278K)

**Karpushin A. and Brown M.**

We applied an Iteratively Reweighted Least Squares (IRLS) approach to create a map of the Sea of Galilee. We use a bank of Prediction Error Filters (PEFs) as a residual whitener to reduce the acquisition footprint and map artifacts caused by non-Gaussian noise in the data.

## AVA

### 5th dimension warning for 4D studies

(ps.gz 612K) (pdf 281K) (src 1480K)

**Artman B.**

It has been well documented that reservoirs show sometimes staggering amounts of compaction over years of production. The aquifer under Las Vegas, the Ecofisk development, and the Lake Maracaibo area are all examples where the subsidence of porous reservoirs have undergone a compaction observable to the naked eye. Studies of the elastic deformation of the surrounding country rock have shown the distribution of failure types to be associated with the volumetric collapse of a reservoir structure Segall (1998). However, ...

AVA attributes (2 for 1 special)

(ps.gz 794K) (pdf 798K) (src 2791K)

**Artman B.**

Once satisfied that an amplitude, as produced by the user's favorite migration process/algorithm, contains sufficiently accurate and interesting information, the use of that knowledge must be simple and enlightening. Herein I will introduce an AVA (or O if you insist) attribute that is easily calculated, quickly interpreted, and physically meaningful. This attribute will be derived from a different, though related, cross-plot that shows significant improvement over the classic *Intercept-Gradient* plane. ...

## Computing

### Ricksep: Interactive display of multi-dimensional data

(ps.gz 1185K) (pdf 947K) (src 12K)

**Clapp R. G.**

SEP has always been interested in displaying and interacting with multi-dimensional datasets Biondi and van Trier (1993); Claerbout (1981); Clapp et al. (1994); Clapp and Biondi (1994); Clapp (1995); Mora et al. (1995, 1996); Ottolini and Rocca (1986); Ottolini (1983, 1988, 1990); Sword (1981) ...

### Using the NTSC color space to double the quantity of information in an image

(ps.gz 1690K) (pdf 1448K) (src 7092K)

**Vlad I.**

Geophysical images are, by their nature, intensity images: matrices of real numbers. Thus, representing an image in a color scale will only enlarge the visible dynamic color range without adding any information. But color can be used to encode information taken from a second geophysical image. The combination of the two images produces a meaningful image that can be understood better if two criteria are fulfilled: 1) The information used to create color (referred to from now on as the chrominance image) is entirely separated from the shading (black and white) information (referred to from now on as the luminance image). 2) The frequency content of the ...

## Manual

### SEP manual

(ps.gz 5K) (pdf 3K)

**Clapp R., Prucha M., Sava P., Dellinger J., and Biondi B.**

- Biondi, B., and van Trier, J., 1993, Visualization of multi-dimensional seismic datasets with CM-AVS: SEP-
**79**, 1-12. - Claerbout, J. F., 1981, On-line movies: SEP-
**28**, 1-4. - Claerbout, J. F., 1992, Earth Soundings Analysis: Processing versus Inversion: Blackwell Scientific Publications.
- Clapp, R. G., and Biondi, B., 1994, Iterative velocity model building for 3-D depth migration by integrating GOCAD and AVS: SEP-
**80**, 635-644. - Clapp, R. G., Biondi, B., and Karrenbach, M., 1994, AVS as a 3-D seismic data visualizing platform: SEP-
**82**, 97-106. - Clapp, R. G., 1995, SEP AVS User Guide: SEP-
**84**, 395-408. - Cole, S., and Dellinger, J., 1989, Vplot: SEP's plot language: SEP-
**60**, 349-390. - Dellinger, J., 1989, Why does SEP still use vplot: SEP-
**61**, 327-336. - Mora, C. B., Clapp, R. G., and Biondi, B., 1995, Velocity model building in avs: SEP-
**89**, 133-144. - Mora, C. B., Clapp, R. G., and Biondi, B., 1996, Visualization of irregularly sampled seismic data with AVS: SEP-
**93**, 75-86. - Ottolini, R., and Rocca, F., 1986, Movies of data lag histograms with application to deconvolution research: SEP-
**50**, 35-42. - Ottolini, R., 1983, Movie cubes: SEP-
**35**, 235-240. - Ottolini, R., 1988, Movies on the Macintosh II: SEP-
**59**, 255-268. - Ottolini, R., 1990, Seismic movies on the XView graphics system: SEP-
**65**, 315. - Sword, C. H., 1981, SEP goes to the movies: SEP-
**28**, 11-20. <