Logging curve abnormal value labeling method and device, computer equipment and storage medium

Abstract

The invention relates to a logging curve abnormal value marking method and device, computer equipment and a storage medium, and the method comprises the steps: reading a preset trained machine learning model set, selecting an optimal trained machine learning model under a current tuning standard from the set, and marking the selected trained machine learning model according to the current tuning standard; and inputting the to-be-labeled logging curve into the selected trained machine learning model to obtain a logging curve abnormal value labeling result. In the whole process, the optimal trained machine learning model under the current tuning standard is selected, abnormal value labeling of the to-be-labeled logging curve is completed through the selected trained machine learning model, manual abnormal value labeling is not needed, and logging curve abnormal value labeling can be efficiently and accurately achieved.

Description

technical field [0001] The present application relates to the technical field of automation, in particular to a logging curve abnormal value labeling method, device, computer equipment and storage medium. Background technique [0002] Well logging is a branch of geophysical prospecting and a general term for geophysical prospecting methods used in drilling. According to the different physical properties of the rocks used, it can be divided into electrical logging, radioactive logging, magnetic logging, acoustic logging, thermal logging, and gravity logging. The parameters of the formation can be known through the logging curve, which is beneficial to the exploration and development of oil. However, the logging curve is affected by various factors such as the environment during the measurement process, and some abnormal values ​​will be generated. These values ​​are not a true reflection of formation properties, and if these outliers are not dealt with in the early preproce...

AI Technical Summary

Problems solved by technology

[0004] Although the above method can realize the abnormal value labeling of well logging curves, due to the large depth of well logging, a large amount of data needs to be processed, and it takes a lot of time to complete this part of data processing and identification manually, and the processing process is different. There are deviations in people's cognition and experience, resulting in inaccurate labeling of some outliers

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