A Python‑based modeling enabling lithology‑driven friction factor calibration

Gullu Jabbarova¹, Vusal Iskandarov¹, Yelena Shmoncheva¹

¹Azerbaijan State Oil and Industry University, Baku, Azerbaijan

Min. miner. depos. 2026, 20(2):22-30

https://doi.org/10.33271/mining20.02.022

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ABSTRACT

Purpose. The purpose of this paper is to develop and validate a Python-based workflow for processing continuous hook-load data and applying it to lithology-driven friction-factor calibration in torque-and-drag analysis during casing-running operations in deep, high-pressure wells.

Methods. The proposed workflow is based on the automated processing of continuous mud-logging hook-load data recorded during casing deployment. The procedure includes data cleaning, threshold-based segmentation, rolling filtering, outlier removal, and extraction of representative tripping-in and tripping-out load trends. The processed trends are then compared with field measurements and used to calibrate interval-specific friction factors in torque and drag simulations for two offshore wells.

Findings. The results show that the developed workflow converts noisy continuous hook-load records into stable load trends suitable for calibration. In both analyzed wells, a single constant friction factor was insufficient to reproduce the full mechanical response of the casing run. Better agreement was achieved when friction factors were calibrated for individual depth intervals. The calibrated profiles also showed that changes in friction behavior were generally consistent with lithological transitions and heterogeneous wellbore conditions.

Originality. The study’s originality lies in combining continuous mud-logging hook-load data, automated Python-based processing, and interval-specific torque- and drag-calibration into a single workflow for lithology-sensitive interpretation of casing-running behavior.

Practical implications. The proposed approach reduces reliance on manual point selection, improves the consistency of post-run torque-and-drag calibration, and can serve as a practical engineering tool for analyzing casing-running performance in geologically complex wells.

Keywords: torque and drag analysis; friction factor calibration; casing-running operations; mud-logging data; lithology; Python workflow; wellbore mechanics

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