Automated Depth Shifting of Core Data: A Python-Based Approach

In the field of petroleum exploration and reservoir analysis, the precise correlation between core data and log data is paramount. However, the presence of broken or incomplete core data due to core crumbling, stretch of logging tools cables, and information loss on cored depths poses a significant challenge, as it can hinder the accuracy of interpretations derived from log data also Manually shifting is both demanding and time-consuming, and its precision falls short when compared to the efficiency and accuracy of an automated shifting process. This paper introduces a novel Python-based solution for automatic depth shifting of core data to log data, aimed at enhancing the alignment and integration of these two essential datasets. By adopting the issue of incomplete core recovery, this approach offers a practical and efficient method to optimize data consistency and improve the quality of geological interpretations.

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Publication Details

Journal
Journal of Petroleum Research and Studies
Published
2025-09-21
DOI
https://doi.org/10.52716/jprs.v15i3.913
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Automated Depth Shifting of Core Data: A Python-Based Approach

Journal of Petroleum Research and Studies
Prenatal Screening and Diagnostics
article

Automated Depth Shifting of Core Data: A Python-Based Approach

article en

Abstract

In the field of petroleum exploration and reservoir analysis, the precise correlation between core data and log data is paramount. However, the presence of broken or incomplete core data due to core crumbling, stretch of logging tools cables, and information loss on cored depths poses a significant challenge, as it can hinder the accuracy of interpretations derived from log data also Manually shifting is both demanding and time-consuming, and its precision falls short when compared to the efficiency and accuracy of an automated shifting process. This paper introduces a novel Python-based solution for automatic depth shifting of core data to log data, aimed at enhancing the alignment and integration of these two essential datasets. By adopting the issue of incomplete core recovery, this approach offers a practical and efficient method to optimize data consistency and improve the quality of geological interpretations.

Journal of Petroleum Research and StudiesVol. 15(3)
University of Baghdad (IQ)
Openalex Percentile: Top 32%
Prenatal Screening and Diagnostics
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