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Identification and Reduction of Spiky Seismic Traces Using In-House Developed Module
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 80th EAGE Conference and Exhibition 2018, Jun 2018, Volume 2018, p.1 - 5
Abstract
Summary
In seismic data acquisition with SVSM digital sensor (Multicomponent sensor), where channels were more than 2000, a long felt need was to identify all the spiky traces and relate it with the objects on the ground within the short span of time. Number of times it was difficult to identify the source of spiky/noisy traces as the channel numbers were large and they were spread over a large, usually 30–60 sq km. To overcome this problem, modules were developed in python programming language to segregate the spiky traces along with their SVSM sensor serial number, receiver and shot locations for identifying the causes of these noisy trace. Some of the traces were noisy due to noise sources on ground and others due to faulty SVSM although they passed in instrumental tests. The Spiky traces were plotted on Google map to see the positioning of SVSM. The sensors falling in noise free areas were replaced with good sensors and those were tested in lab. Most of the times it was found that such SVSM were faulty. The module can also be used in processing to segregate spiky/noisy traces and it will be removed from the data.
In 2D-3C and 3D-3C seismic data acquisition with SVSM digital sensor (Multicomponent sensor), where channels were more than 2000, a long felt need was to identify all the spiky traces and relate it with the objects on the ground within the short span of time. Number of times it was difficult to identify the source of spiky traces as the channel numbers were large and they were spread over a large, usually 30–60 sq km. To overcome this problem, modules were developed in python programming language to segregate the spiky traces along with their SVSM sensor serial number, receiver and shot locations for identifying the SVSM.
The Spiky traces were plotted on google map to see the positioning of SVSM. The sensors falling in noise free areas were replaced with good sensors and those were tested in lab. Most of the times it was found that such SVSM were faulty.
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