RTM 2D

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Description

RTM Stands for Reverse Time Migration

 

If we know the seismic image at a shot time T and we have the velocity field information, then we can predict the seismic wavefield at time T + dT or T - dT. This is the basis behind forward and reverse wavefield extrapolation techniques.

 

The source wavefieldis created at the shot location by propagating forward in time. The receiver wavefieldis obtained by propagating the recorded wavefield from its boundary (the recording surface) into the earth with time running backward. Because of the receiver wavefield back propagation, we call this technology as Reverse Time MigrationThe image is typically constructed by taking the zero-lag cross-correlation of the extrapolated source and receiver wavefields, i.e., the “same time same place” imaging principle. Raypaths that are modelled in the both the Source and Receiver wavefields (i.e diving waves and reflections from velocity contrasts present in the velocity model), will correlate at all travel times leading to a low frequency smear in the data.

 

If we can explain RTM in more simplistic way:

 

clip0068_r

 

Figure 1. Schematic Diagram of RTMwork flow

Source Wave field forward modeling

 

clip0069_r

 

Where T is the maximum recorded time.

Input:   Output File name

            Imaging Condition Type

             DX      

             Use Wavelet

             Frequency

             Time Step

             Time Step for correlation

RTM works in shot domain and migrate the data shot by shot. Also we need regularized shot gathers.

RTM stores both Source Wavefield and Receiver Wavefield and we need more memory. To properly manage our resources, clip the values above the water bottom so that we can reduce the run time and disk space. Also RTM run time is directly proportional to the trace time. So depending on output depth and migration velocity, using the entire length of the input traces might not be necessary for migration.

 

Input data

Output file name image

Output file name illumination

Use snaps

Temporary snaps path

Depth velocity

Input SEG-Y data handle

Input trace headers

Image save type

Save type

Wavelet

Parameters

Imaging condition type

Calculate fold matrix

Detect topography

Air velocity

Create angles gathers

Decimation factor

Additional apperture

Padding size

Use wavelet

Frequency

Time step

Time step for correlation

Samples count