IEEE Signal Processing - March 2018 - 80

|

C

B
A D

0

Reconstructed
Original

1

0

0.1

0.2

0.3

3

xa
Inputs

x2

x1

Bias
x0

2,260 2,280 2,300 2,320
Time (ms)

Original Porosity
Regularized Porosity

Regularization

Normalization

Integration

Preprocessing

0
2,220 2,240 2,260 2,280 2,300 2,320
Time (ms)

0.2

Original Porosity
Regularized
Porosity
Seismic
Amplitude

Inline

0.5
0
0.5
Frequency (Hz)

E

Inline

Porosity

5,000
2,220 2,240 2,260 2,280 2,300 2,320
0.4

Seismic
Amplitude

2
-5,000

zb

z2

z1

z0

yc

y2

y1

Outputs

4

Inline
Filtered Lithology Volume

Xline

6

Validation

Testing

Training

Algorithm Selection

Prediction

Hidden Layers

Bias
5

Xline

Inline
Inline/Xline/Time Slices of Lithology

Xline

7

Visualization

Filtering

Volume Generation

Inline

Generated Lithology Volume

Postprocessing

Time (ms)

lithology volumes; demonstrated algorithm: ANN).

Figure 6. A graphical abstract-a representative framework for RC consisting of different preprocessing, training, and postprocessing steps (inputs: seismic volumes, lithology logs; output: predicted and filtered

0
-1

0.1

0.2

0.3

0.4

Lithology Logs

Xline

Xline

Seismic Attributes

Seismic Volumes

1

Time (ms)

Time (ms)

Spectrum

March 2018
Porosity

|
Time (ms)

IEEE SIgnal ProcESSIng MagazInE

Time (ms)

80



Table of Contents for the Digital Edition of IEEE Signal Processing - March 2018

Contents
IEEE Signal Processing - March 2018 - Cover1
IEEE Signal Processing - March 2018 - Cover2
IEEE Signal Processing - March 2018 - Contents
IEEE Signal Processing - March 2018 - 2
IEEE Signal Processing - March 2018 - 3
IEEE Signal Processing - March 2018 - 4
IEEE Signal Processing - March 2018 - 5
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IEEE Signal Processing - March 2018 - 176
IEEE Signal Processing - March 2018 - Cover3
IEEE Signal Processing - March 2018 - Cover4
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