Lab 2: Seismic Data QC

QUALITY CONTROL OF SEISMIC DATA

  Quality control (QC) has generally been considered by the seismic data acquisition industry to be a method to determine if the recording system is performing within the tolerances of the instrument manufacturer’s specifications and that the geophysical specifications of the survey design are being matched. 

With today’s modern recording systems there is a large amount of information that is being recorded that can provide significant benefits beyond the normal QC perspective.

The QC process involves a series of steps to condition the data and prepare it for further quality control and processing. These steps include:

1. De-multiplexing: The data is transposed from the recording mode, where each record contains the same time sample from all receivers, to the trace mode where each record contains all time samples from one receiver. This is usually done in the field.

2. Reformatting: The data is converted from one seismic digital format (e.g., SEG-Y) to another format that is convenient to the processing software and used throughout the processing flow (e.g., MATLAB).

 3. Setup of field geometry: The geometry of the field is written into the data (trace headers) in order to associate each trace with its respective shot, offset, channel, and CMP.

 4. Trace editing: During this step, bad traces, or parts of traces, are muted (zeroed) or killed (deleted) from the data and polarity problems are fixed.

 5. Gain application: Amplitude corrections are applied to account for amplitude losses due to spherical divergence and absorption

 6. Application of field statics: In land surveys, elevation statics are applied to bring the sources and receivers to a common datum level. This step can be delayed until the static correction process where better near-surface velocities might be available.

Theory :

Seismic noise detection in raw data is one of the problems geophysicists must face in the first step of data processing. all seismic trace should be carefully inspected , in order to recognise and remove some very common types of seismic noise , i.e spikes , high frequencies , environmental noise  and ground roll . Noise is often troublesome in further processing steps and always detrimental to the final result . Seismic trace editing is one of the most man time consuming operations; it requires the   allocation   of skilled resources to a poorly gratifying job. The main Objective for this lab is To edit or remove noisy traces.

Trace Editing

In this lab , you will use the east Texas seismic data set where you already have noticed some high noisy amplitude traces from lab 1,  particularly, in trace 31 of shot gather number 16. This is due to the use of a bad geophone since we are dealing with land data.

OBJECTIVES:

·        To apply RMS AGC and instantaneous AGC on multiple shot gathers

• To edit or remove noisy traces

·        To compare effect of amplitude correction on shot gathers

Practical : 

clear all, clc, close all;

load SeismicData_A.mat

%% Assign header to the data

shot_num=1:18;

p=0;

[Dshot,dt,dx,t,offset]=extracting_shots(D,H,shot_num,p);

%% Dsiplay data before apply gain

scale =1;

figure(1);

mwigb(Dshot ,scale ,offset ,t)

xlabel('Offset(ft)','FontSize',14)

ylabel('Time(s)','FontSize',14)

title('Data before gain','FontSize',14)

Before muting, in shot record 16, from 2.25 to 3 ms, trace 31 has an unusual, irregular trace. After muting, by muting the trace and interpolating it after, we managed to remove the bad trace entirely and replace it with a normal trace

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a trace with abnormal amplitude exist in shot record 16 and it has been noticed that the bad trace is in trace 31. we zero the trace and interpolate the trace by averaging the properties from the neighbouring traces to remove anomaly and we replace the removed trace by normalized trace

Correction to Amplitude Losses

Among the various QC steps necessary to ultimately obtain an accurate seismic image of the subsurface structures is to correct for amplitude losses. There is a noticeable decreases in the amplitudes of its recorded traces with time as shows in Trace Editing figure (before muting).

Factors that lead to amplitude losses:

• Transmission loss: This occurs at each geological reflector where part of the propagating seismic incident waves will be reflected, refracted, diffracted, scattered, etc. There is no loss here in terms of the mechanical energy since the lost energy merely travels somewhere else.
• Geometric divergence: As the seismic wave spreads out from its source, its amplitude decays by an amount proportional to the reciprocal of the distance from the source to the location of the propagating seismic wave.
• Absorption: This occurs where the seismic energy is converted into heat by friction. This loss is proportional to the exponential of the distance from the source.

Amplitude correction is applied to seismic data sets a t various stage. Geometric divergence and absorption loss is corrected at pre-processing stage. The weak signal are being boost by adding more gain to the data. Figure below shows the amplitude enhancement gained on this shot gather. The figure below shows the seismic data shot gather number 8: before and after applying AGC method.

Objective : 

To compensate for amplitude losses due to transmission loss, geometric divergence and absorption.

...................................

%% Apply Gain

pow =2;

T=0;

Dg=iac(Dshot,t,pow,T);

Dgz=Dg;

%% Dsiplay data after apply gain

scale =1;

figure(2);

mwigb(Dg ,scale ,offset ,t)

xlabel('Offset(ft)','FontSize',14)

ylabel('Time(s)','FontSize',14)

title('Data after gain','FontSize',14)

%% Amplitude env gain

tnum=33;

seis_env_dB(Dshot,Dg,t,tnum)

seis_env_dB(Dshot,Dg,t)

%% Apply gain also

agc_gate =0.5;

T=1;

Dg1=AGCgain(Dshot,dt,agc_gate,T);

%% Dsiplay data after apply gain

scale=1;

figure(3);

mwigb(Dg1,scale ,offset ,t)

xlabel('Offset(ft)','FontSize',14)

ylabel('Time(s)','FontSize',14)

title('Data after gain','FontSize',14)

%% Also apply gain

agc_gate=0.5;

T=2;

Dg2=AGCgain(Dshot ,dt ,agc_gate ,T);

%% Dsiplay data after apply gain

scale=1;

figure(4);

mwigb(Dg2,scale ,offset ,t)

xlabel('Offset(ft)','FontSize',14)

ylabel('Time(s)','FontSize',14)

title('Data after gain','FontSize',16)

%%

clear D,clear Dg,clear Dshot,clear dt,clear dx,clear i,clear j

clear offset,clear p,clear pow,clear shot_num,clear t,clear T

save SeismicDataA_gain

in shot record 33, the amplitude is concentrated in the shallower section only. The loss in amplitude towards the deeper section can be due to geometrical spreading,. After gain, the amplitude is balanced throughout the record length. 

blue line shows before gain, the average amplitude envelope the traces shows the \ decrease in amplitude over time.After gain (red line), we can observe the amplitude is more balanced .gain in deeper section can be observed .

• RMS amplitude AGC: This method requires segmenting each trace into fixed time gates and then:
  • Calculate the RMS value in each gate.
  • Divide the desired RMS scaler by the RMS value of step 1 and multiply it by the amplitude of the sample at each gate center.
  • Interpolate between these gate centers and multiply the result by the amplitude of samples corresponding in time.
• Instantaneous AGC: this is a bit different from the RMS AGC:
  • 1. Calculate the absolute mean value for in a given gate of length w.
  • 2. Divide the desired RMS scaler by the mean value of step 1 and multiply it by the amplitudes of all the samples in the gate.
  • 3. Slide the gate down by one sample and repeat steps 1-2 until you have calculated all the amplitudes of all trace samples that have been corrected.

The figure below shows the seismic data shot gather number  after applying the AGC using (a) instantaneous method (b) RMS method 

Computer Assignment

• Shot gathers used in this computer assignment is shot gathers 11 till 14 as shows in the figure below.

• Multiplication by a power of time and exponential gain function corrections with a,b = 1.8, 2.2 and 3.4 on the selected shot gathers. Then RMS AGC and instantaneous AGC method were applied on the same shot gathers.

Seismic data shot gather with a = 1.8, before and after applying amplitude correction gain method.

Seismic data with a= 1.8, shot gather after applying the AGC using the instantaneous and RMS based methods.

Seismic data shot gather with b = 1.8 before and after applying amplitude correction gain method.

DISCUSSION:

  AGC  method introduces an extreme amplitude gain at the bottom center. With increasing α, this noise is preserved while the upper reflection is greatly reduced. With exponential correction, most reflectors in the upper part are somehow diminished except in lower time window.However, increase in β also diminish lower reflectors.

CONCLUSION:

·        Quality control of seismic data is very crucial in the pre-processing of seismic data

·        AGC is an effective tool for gain control.

·        When conducting gain control, it is important to exclude extreme amplitude by trace editing so
       that it won’t be included in averaging process and to prevent masking the true reflectors.