Depth conversion using normalized interval velocities

1986 ◽  
Author(s):  
Melvan D. Carter
Keyword(s):  
Interval Velocities

STACKING OF REFLECTIONS FROM COMPLEX STRUCTURES

Geophysics ◽  
1974 ◽  
Vol 39 (4) ◽  
pp. 427-440 ◽  
Author(s):  
Max K. Miller
Keyword(s):  
Deep Structure ◽  
Control Model ◽  
Layer Model ◽  
Low Velocity ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Static Correction ◽  
Reflection Data ◽  
Actual Field ◽  
Interval Velocities

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.

A method for direct estimation of interval velocities

Geophysics ◽  
1982 ◽  
Vol 47 (12) ◽  
pp. 1657-1671 ◽  
Author(s):  
Philip S. Schultz
Keyword(s):  
Estimation Procedure ◽  
Estimation Accuracy ◽  
Substantial Contribution ◽  
Interval Velocity ◽  
Direct Estimation ◽  
Enhanced Resolution ◽  
Prior Estimate ◽  
Sensitive Function ◽  
Interval Velocities ◽  
Ray Parameter

The most commonly used method for obtaining interval velocities from seismic data requires a prior estimate of the root‐mean‐square (rms) velocity function. A reduction to interval velocity uses the Dix equation, where the interval velocity in a layer emerges as a sensitive function of the rms velocity picks above and below the layer. Approximations implicit in this method are quite appropriate for deep data, and they do not contribute significantly to errors in the interval velocity estimate. However, when the data are from a shallow depth (vertical two‐way traveltime being less than direct arrival to the farthest geophone), the assumption within the rms approximation that propagation angles are small requires that much of the reflection energy be muted, along with, of course, all the refraction energy. By means of a simple data transformation to the ray parameter domain via the slanted plane‐wave stack, three types of arrivals from any given interface (subcritical and supercritical reflections and critical refractions) become organized into a single elliptical trajectory. Such a trajectory replaces the composite hyperbolic and linear moveouts in the offset domain (for reflections and critical refractions, respectively). In a layered medium, the trajectory of all but the first event becomes distorted from a true ellipse into a pseudo‐ellipse. However, by a computationally simple layer stripping operation involving p‐dependent time shifts, the interval velocity in each layer can be estimated in turn and its distorting effect removed from underlying layers, permitting a direct estimation of interval velocities for all layers. Enhanced resolution and estimation accuracy are achieved because previously neglected wide‐angle arrivals, which do not conform to the rms approximation, make a substantial contribution in the estimation procedure.

Sand injectite mapping using a resistivity-velocity transform function

2021 ◽  
Vol 40 (3) ◽  
pp. 202-207
Author(s):  
Anke S. Wendt ◽  
Monzurul Alam ◽  
Joao Paulo Castagnoli
Keyword(s):  
Residual Velocity ◽  
Rock Types ◽  
Geostatistical Approach ◽  
Spatially Distributed ◽  
Resistivity Logs ◽  
Hydrocarbon Fields ◽  
Interval Velocities ◽  
Resistivity Log ◽  
Measured Resistivity ◽  
Sand Bodies

Lack of resolution in the distribution of sand injectites in hydrocarbon fields is common and makes it difficult to predict drilling challenges and plan for optimum production. A practical workflow was developed that enables the distinction of shale and sand bodies by using a combination of low-resolution seismic data and high-resolution resistivity log data. Measured resistivity logs were used to predict synthetic velocity logs, which accurately match shale velocities and over- or underestimate velocities of other rock types. The synthetic velocity logs were spatially distributed in a 3D cube in order to predict synthetic velocities in between and away from the well locations. The 3D cube was representative of a field. It covered the interval from the seabed to below the reservoir. The spatial distribution was based on a geostatistical approach guided by measured seismic interval velocities. A residual velocity cube was calculated from the measured and synthetic velocities. The residual velocity cube produced near-zero velocities for shaly materials and velocity over- or underestimates for other rock types. Interpretation of the residual velocity cube required the identification of strong stratigraphic markers. The markers were removed from the residual cube by setting their specific layer velocities to 0 m/s. The final information stored in the residual velocity cube was then related to the over- or underestimated velocities in sand bodies.

Inverse Methods to Improve Accuracy of Water Content Estimates from Multi-offset GPR

2018 ◽  
Vol 23 (3) ◽  
pp. 349-361
Author(s):  
Andrew D. Parsekian
Keyword(s):  
Water Content ◽  
Careful Analysis ◽  
Subsurface Water ◽  
Geologic Materials ◽  
Improve Accuracy ◽  
The Subject ◽  
Interval Velocities ◽  
Ground Penetrating ◽  
Radar Wave ◽  
The Impact

Ground penetrating radar (GPR) is a powerful hydrogeophysical tool for estimating porosity and water content of geologic materials using radar wave velocities and appropriate petrophysical relations. In substrates with more than one layer of interest, surface-based multi-offset measurements require careful analysis to accurately retrieve physical properties for each layer. Frequently, Dix inversion is used to calculate interval velocities, however the assumptions and limitations of this approach are widely known. In particular for survey geometries and targets encountered with GPR, the assumptions inherent to Dix inversion are readily violated, and therefore inverse modeling is required to avoid velocity error. While the impact on velocity incurred by violating the assumptions of Dix inversion is well understood, the effects on water content estimates have not been widely reported and are therefore the subject of this work. In a subsurface representative of an unsaturated zone overlying an aquifer, error in excess of 50% in water content due to violating the assumptions of Dix inversion is demonstrated. Examples are shown using raytracing inversion to solve for subsurface water content structure that avoids the errors inherent to Dix inversion. These results are intended to underscore the importance of minimizing assumptions and using more correct physics when analyzing multi-offset GPR data, particularly due to the large potential errors that may be encountered if water content estimation is the main objective.

Fine layering effect on surface seismic interval velocities

1993 ◽  
Author(s):  
L. Nicoletis ◽  
S. Firdion ◽  
J. Arnaud ◽  
E. de Bazelaire
Keyword(s):  
Layering Effect ◽  
Interval Velocities
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