How does the thin near surface of the earth produce up to 100 times more noise on land seismic data than on marine data?

SEG 2024 Distinguished Lecturer

SEG members, view the course for free!

Format: Virtual Webinar. 45 min. presentation followed by 15 min. Q&A

An optional post-lecture workshop will immediately follow each lecture for expanded Q&A and networking

Session 1, Thursday, May 23, 2024, 10 am to 11 am US Central Time

Session 2, Wednesday, June 26, 2024, 9 am to 10 am Beijing Time

Past SEG Recordings

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Two live sessions are completed. Please scroll down to watch the videos from the recordings below. SEG members, view the course for free!
Land seismic data is often dramatically noisier than marine data. Processed images and attributes from land data can be severely degraded by this noise. The acquisition effort needed to address the noise is often the biggest cost factor and the biggest uncertainty with land seismic data.

The physics behind land seismic noise is fascinating. Much of the noise is caused by the very near surface, less than 30m, which often has ultra slow velocities. This land seismic noise is often complex and irregular--much more so than simple surface waves. Even simple scattering models are insufficient. We give a physical intuition of this noise generation through wave propagation movies and synthetic data examples with realistic models.

Better understanding the physics of the complex noise generation can lead to better understanding and customization of the acquisition and processing to the noise types. We propose the following conclusions for many areas: 1) importance of micro-near surface effects, 2) much distortion of signal is more complex than the statics and SC-decon model, 3) you probably have more signal in your data than you think, 4) statistical noise removal has limits, 5) there is much value in coherent noise removal, 6) there is limited benefit to dense inline receiver spacing, 7) a better use of high channel counts may be an irregular layout, 8) limits of CSI-reconstruction approaches, 9) changes in surface moisture content can produce strong 4D noise for CCUS monitoring, 10) FWI has limited benefit in addressing the surface noise (but it has other good uses), and 11) specialized modeling of the noise in an area and testing methods to address it can be helpful.

Your Instructor

Christof Stork, PhD, SEG-DL
Christof Stork, PhD, SEG-DL

Christof Stork started as a theoretical academic with a Ph.D. in geophysics from Caltech and a post-doc from Stanford 36 years ago. He performed early leading work in Reflection Tomography, PSDM, WEM, RTM, and FWI before they became mainstream technologies. 10 years ago, he decided to take on noisy land seismic data where theory alone is not enough. Christof has been involved with 4 startup companies in his quest to avoid Houston and make theory commercially viable. He's now on his 5th and last and craziest startup company, a land seismic processing company, so he can get his hands on more land data.