Well Seismic Data Extraction Method Based on Euclidean Distance Approximate Matching

Abstract

The present invention provides a method for extracting well seismic data based on Euclidean distance approximate matching, which includes: performing approximate seismic attribute matching, finding the coordinate point position closest to the target well, and extracting the seismic attribute value corresponding to the position approximately as the corresponding value of the target well position Seismic attribute values, and integrate all seismic attribute values ​​into an attribute set; carry out approximate matching of lithological data, through the start and end time range of the time window, and use time-depth conversion to convert the time range to the depth range corresponding to the target well, and then Calculate the lithology ratio within the depth range corresponding to the target well sample; match the extracted seismic attribute set with the lithology type to obtain a seismic attribute set with category labels. This method realizes the approximation of the target well position to the nearest grid position in the adjacent distance and the extraction of the seismic data of the target well. The numerical category labels and seismic attribute values ​​can provide sample point support for the training of the machine learning classification model.

Description

technical field [0001] The invention relates to the field of geophysical exploration and the field of machine learning technology, in particular to a method for extracting well seismic data based on Euclidean distance approximate matching. Background technique [0002] In field observation operations, multiple geophones are generally arranged at equal intervals along the seismic survey line to receive seismic wave signals, and seismic data are stored in the form of seismic traces. The entire seismic volume data can be regarded as a grid cuboid divided according to CDP and Inline, and only the horizon data and seismic attribute data at the corresponding positions on the grid points are stored. Because the target well is not necessarily located at the grid point of the seismic volume, the well seismic data corresponding to the target well cannot be obtained accurately. For this reason, we invented a new well seismic data extraction method based on Euclidean distance approxima...

AI Technical Summary

Problems solved by technology

Because the target well is not necessarily located at the grid point of the seismic volume, the well seismic data corresponding to the target well cannot be obtained accurately

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