Increases in Dynamic Range Through Trace Dependent Scaling in IESX

Keith Woollard - GeoCom Services Australia Pty Ltd

Introduction “The unique disk-efficient seismic data

storage procedure preserves the dynamic range of the Data”• How true is this statement?• How does it work?• What are the benefits?• What possible problems exist?• How can it be improved?

The test dataset

5gb of 32 bit data 170km2 3D North-West Shelf, Australia “True-ish” amplitude

The test dataset

Example line from test dataset

The test dataset

Example line from test dataset - Full time range

Testing Procedure32 bit

Input SEG-Y

8 & 16 bitSeisWorks and IESX

load

SEG-Y export(manual rescale for

SeisWorks data) DifferenceVolumes

PercentagedifferenceVolumes

Comparisons - 8 bit load

Difference plot - Conventional Difference plot - IESX

Comparisons - 8 bit load

Legend : Red IESX more accurate

Black IESX less accurate

Comparisons - 16 bit load

Difference plot - Conventional Difference plot - IESX

Arithmetic Difference

RMS of difference 8 bit 16 bit

Conventional 24.4 0.25

IESX 18.2 0.07

Input data RMS = 348

Amplitudes of each trace analysed

How Does it Work?

+127-127

These values set to F.S.D.

Min and max amp found for each trace

Traces sorted into 2n bins

How Does it Work? One scalar pair calculated for each trace Scalar stored along with trace Scalar can be reversed by software Other systems have one scalar per

line/load/survey and require user to document value

When does it have problems? In the presence of a strong time variant

amplitude gradient

Percentage error per sample

Time Variant Amplitude Issues

Trace dependent scalar ideal for spatial amplitude variation

0

10

20

30

40

50

60

0 1000 2000 3000 4000 5000 6000

Time

Error

Not suited to temporal variations

Suggestions:• 1 scalar per N samples • N scalar per trace

Time Variant Amplitude Issues

Difference plot - IESX Difference plot - 1 sec gates

Time Variant Amplitude Issues

% Difference plot - IESX % Difference plot - 1 sec gates

Single large amplitudes Spikes on input

Onshore data showing missing traces due to spikes

Single large amplitudes Typical seismic data has one or two sample

much larger than the rest In test dataset, second largest amplitude on

each trace is 82% of largest. Third largest is 54%

True amplitude histogram Histogram after AGC

Single large amplitudes Thus to preserve two samples, we are

halving the dynamic range of the rest. For old/on-shore/scanned data, single bad

samples will destroy whole trace Significantly better amplitude binning could

be obtained by using second or third largest amplitude

No problem for well-modulated data No need to run de-spike filters

Summary Marginally better amplitude representation

than conventional single scalers for 8 bit Significantly better amplitude representation

than conventional single scalers for 16 bit Easier data loading Seamless amplitude recovery Not perfect, especially when loading to 8 bit Two improvements possible

• time gated scaling• “second largest” amplitude method