Abstract
This article proposes and compares formalized criteria for the quality of automated well correlation. Three indicators are considered: the error in predicting well log values based on cross-validation; the ratio of the average intra-group variance to the total data variance; and the standard deviation of the depths of a set of stratigraphic boundaries from a reference model. A very close statistical relationship is demonstrated for the first two criteria, but due to the comparative simplicity of calculation, the second is preferable. The criterion associated with assessing the deviation from the reference model (created by an expert) can be used in machine learning for practical tasks, but is of little use because it requires the preliminary construction of a reference model.
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Publication Info
- Year
- 2025
- Type
- article
- Issue
- 2
- Pages
- 51-59
- Citations
- 0
- Access
- Closed
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Cite This
V. V. Lapkovsky,
V. I. Sheludko
(2025).
Formal quality criteria for automatic correlation of well logs.
Russian Journal of geophysical technologies
(2)
, 51-59.
https://doi.org/10.18303/2619-1563-2025-2-51
Identifiers
- DOI
- 10.18303/2619-1563-2025-2-51