A convolutional neural network approach to deblending seismic data

Author:

Sun Jing1ORCID,Slang Sigmund1ORCID,Elboth Thomas2ORCID,Larsen Greiner Thomas3ORCID,McDonald Steven2,Gelius Leiv-J.4

Affiliation:

1. University of Oslo, Department of Geosciences, Sem Sælands vei 1, 0371 Oslo, Norway, and CGG..

2. CGG..

3. University of Oslo, Department of Geosciences, Sem Sælands vei 1, 0371 Oslo, Norway, and Lundin Norway AS, Strandveien 4, 1366 Lysaker, Norway..

4. University of Oslo, Department of Geosciences, Sem Sælands vei 1, 0371 Oslo, Norway..

Abstract

For economic and efficiency reasons, blended acquisition of seismic data is becoming increasingly commonplace. Seismic deblending methods are computationally demanding and normally consist of multiple processing steps. Furthermore, the process of selecting parameters is not always trivial. Machine-learning-based processing has the potential to significantly reduce processing time and to change the way seismic deblending is carried out. We have developed a data-driven deep-learning-based method for fast and efficient seismic deblending. The blended data are sorted from the common-source to the common-channel domain to transform the character of the blending noise from coherent events to incoherent contributions. A convolutional neural network is designed according to the special characteristics of seismic data and performs deblending with results comparable to those obtained with conventional industry deblending algorithms. To ensure authenticity, the blending was performed numerically and only field seismic data were used, including more than 20,000 training examples. After training and validating the network, seismic deblending can be performed in near real time. Experiments also indicate that the initial signal-to-noise ratio is the major factor controlling the quality of the final deblended result. The network is also demonstrated to be robust and adaptive by using the trained model to first deblend a new data set from a different geologic area with a slightly different delay time setting and second to deblend shots with blending noise in the top part of the record.

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

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