STACKING OF REFLECTIONS FROM COMPLEX STRUCTURES

Geophysics ◽  
1974 ◽  
Vol 39 (4) ◽  
pp. 427-440 ◽  
Author(s):  
Max K. Miller

Common‐depth‐point seismic reflection data were generated on a computer using simple ray tracing and analyzed with processing techniques currently used on actual field recordings. Constant velocity layers with curved interfaces were used to simulate complex geologic shapes. Two models were chosen to illustrate problems caused by curved geologic interfaces, i.e., interfaces at depths which vary laterally in a nonlinear fashion and produce large spatial variations in the apparent stacking velocity. A three‐layer model with a deep structure and no weathering was used as a control model. For comparison, a low velocity weathering layer also of variable thickness was inserted near the surface of the control model. The low velocity layer was thicker than the ordinary thin weathering layers where state‐of‐the‐art static correction methods work well. Traveltime, moveout, apparent rms velocities, and interval velocities were calculated for both models. The weathering introduces errors into the rms velocities and traveltimes. A method is described to compensate for these errors. A static correction applied to the traveltimes reduced the fluctuation of apparent rms velocities. Values for the thick weathering layer model were “over corrected” so that synclines (anticlines) replaced false anticlines (synclines) for both near‐surface and deep zones. It is concluded that computer modeling is a useful tool for analyzing specific problems of processing CDP seismic data such as errors in velocity estimates produced by large lateral variations in overburden.

2016 ◽  
Vol 4 (3) ◽  
pp. SH1-SH9
Author(s):  
Steven D. Sloan ◽  
J. Tyler Schwenk ◽  
Robert H. Stevens

Variability of material properties in the shallow subsurface presents challenges for near-surface geophysical methods and exploration-scale applications. As the depth of investigation decreases, denser sampling is required, especially of the near offsets, to accurately characterize the shallow subsurface. We have developed a field data example using high-resolution shallow seismic reflection data to demonstrate how quickly near-surface properties can change over short distances and the effects on field data and processed sections. The addition of a relatively thin, 20 cm thick, low-velocity layer can lead to masked reflections and an inability to map shallow reflectors. Short receiver intervals, on the order of 10 cm, were necessary to identify the cause of the diminished data quality and would have gone unknown using larger, more conventional station spacing. Combined analysis of first arrivals, surface waves, and reflections aided in determining the effects and extent of a low-velocity layer that inhibited the identification and constructive stacking of the reflection from a shallow water table using normal-moveout-based processing methods. Our results also highlight the benefits of using unprocessed gathers to pragmatically guide processing and interpretation of seismic data.


Geophysics ◽  
1986 ◽  
Vol 51 (1) ◽  
pp. 12-19 ◽  
Author(s):  
James F. Mitchell ◽  
Richard J. Bolander

Subsurface structure can be mapped using refraction information from marine multichannel seismic data. The method uses velocities and thicknesses of shallow sedimentary rock layers computed from refraction first arrivals recorded along the streamer. A two‐step exploration scheme is described which can be set up on a personal computer and used routinely in any office. It is straightforward and requires only a basic understanding of refraction principles. Two case histories from offshore Peru exploration demonstrate the scheme. The basic scheme is: step (1) shallow sedimentary rock velocities are computed and mapped over an area. Step (2) structure is interpreted from the contoured velocity patterns. Structural highs, for instance, exhibit relatively high velocities, “retained” by buried, compacted, sedimentary rocks that are uplifted to the near‐surface. This method requires that subsurface structure be relatively shallow because the refracted waves probe to depths of one hundred to over one thousand meters, depending upon the seismic energy source, streamer length, and the subsurface velocity distribution. With this one requirement met, we used the refraction method over a wide range of sedimentary rock velocities, water depths, and seismic survey types. The method is particularly valuable because it works well in areas with poor seismic reflection data.


2009 ◽  
Author(s):  
Steven D. Sloan ◽  
Don W. Steeples ◽  
Georgios P. Tsoflias ◽  
Mihan H. McKenna

Geophysics ◽  
1955 ◽  
Vol 20 (1) ◽  
pp. 68-86 ◽  
Author(s):  
C. Hewitt Dix

The purpose of this paper is to discuss field and interpretive techniques which permit, in favorable cases, the quite accurate determination of seismic interval velocities prior to drilling. A simple but accurate formula is developed for the quick calculation of interval velocities from “average velocities” determined by the known [Formula: see text] technique. To secure accuracy a careful study of multiple reflections is necessary and this is discussed. Although the principal objective in determining velocities is to allow an accurate structural interpretation to be made from seismic reflection data, an important secondary objective is to get some lithological information. This is obtained through a correlation of velocities with rock type and depth.


2017 ◽  
Vol 90 (2) ◽  
pp. 187-195
Author(s):  
A. I. Opara ◽  
C. C. Agoha ◽  
C. N. Okereke ◽  
U. P. Adiela ◽  
C. N. Onwubuariri ◽  
...  

Geophysics ◽  
1985 ◽  
Vol 50 (6) ◽  
pp. 903-923 ◽  
Author(s):  
T. N. Bishop ◽  
K. P. Bube ◽  
R. T. Cutler ◽  
R. T. Langan ◽  
P. L. Love ◽  
...  

Estimation of reflector depth and seismic velocity from seismic reflection data can be formulated as a general inverse problem. The method used to solve this problem is similar to tomographic techniques in medical diagnosis and we refer to it as seismic reflection tomography. Seismic tomography is formulated as an iterative Gauss‐Newton algorithm that produces a velocity‐depth model which minimizes the difference between traveltimes generated by tracing rays through the model and traveltimes measured from the data. The input to the process consists of traveltimes measured from selected events on unstacked seismic data and a first‐guess velocity‐depth model. Usually this first‐guess model has velocities which are laterally constant and is usually based on nearby well information and/or an analysis of the stacked section. The final model generated by the tomographic method yields traveltimes from ray tracing which differ from the measured values in recorded data by approximately 5 ms root‐mean‐square. The indeterminancy of the inversion and the associated nonuniqueness of the output model are both analyzed theoretically and tested numerically. It is found that certain aspects of the velocity field are poorly determined or undetermined. This technique is applied to an example using real data where the presence of permafrost causes a near‐surface lateral change in velocity. The permafrost is successfully imaged in the model output from tomography. In addition, depth estimates at the intersection of two lines differ by a significantly smaller amount than the corresponding estimates derived from conventional processing.


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