A Multi-Physics Hook-Load Correction Framework for Effective Drill-String–Wellbore Friction Identification

Reliable identification of drill-string–wellbore friction is important for evaluating mechanical load transfer and contact behavior during drilling. However, friction estimation from surface hook-load measurements can be affected by non-frictional contributions from the hoisting system and drilling-fluid-induced forces. This study develops a multi-physics hook-load correction framework incorporating sheave efficiency, traveling-block and hook weight, mud-hose catenary force, drilling-line weight, annular and internal viscous forces, swab/surge effects, and pump-on hydraulic lift. Field data from a 3500 m directional well were analyzed using a yield-power-law (YPL)/Herschel–Bulkley fluid model. For representative slide- and rotary-drilling intervals, measured average hook loads of 442.21 and 481.01 kN were corrected to 294.92 and 332.89 kN, corresponding to correction ratios of 33.31% and 30.79%. Corrected off-bottom hook loads were then used to identify state-dependent effective drill-string–wellbore friction factors of 0.180, 0.154, and 0.104 at three calibration states. These factors were transferred to subsequent drilling intervals for surface-torque reconstruction. After one-point baseline alignment, the remaining torque samples yielded mean relative reconstruction errors of 2.28%, 4.22%, and 3.21%, respectively. Removing these non-frictional contributions allows the effective drill-string–wellbore friction factor to be identified from a corrected surface load and subsequently compared with the measured torque response.

Authors

Institutions

Publication Details

Journal
Lubricants
Published
2026-11-03
DOI
https://doi.org/10.3390/lubricants14110420
Primary Topic
Drilling and Well Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Multi-Physics Hook-Load Correction Framework for Effective Drill-String–Wellbore Friction Identification

Zebing Wu, Shun Wang
Lubricants
Drilling and Well Engineering
article

A Multi-Physics Hook-Load Correction Framework for Effective Drill-String–Wellbore Friction Identification

Zebing Wu, Shun Wang
article en

Abstract

Reliable identification of drill-string–wellbore friction is important for evaluating mechanical load transfer and contact behavior during drilling. However, friction estimation from surface hook-load measurements can be affected by non-frictional contributions from the hoisting system and drilling-fluid-induced forces. This study develops a multi-physics hook-load correction framework incorporating sheave efficiency, traveling-block and hook weight, mud-hose catenary force, drilling-line weight, annular and internal viscous forces, swab/surge effects, and pump-on hydraulic lift. Field data from a 3500 m directional well were analyzed using a yield-power-law (YPL)/Herschel–Bulkley fluid model. For representative slide- and rotary-drilling intervals, measured average hook loads of 442.21 and 481.01 kN were corrected to 294.92 and 332.89 kN, corresponding to correction ratios of 33.31% and 30.79%. Corrected off-bottom hook loads were then used to identify state-dependent effective drill-string–wellbore friction factors of 0.180, 0.154, and 0.104 at three calibration states. These factors were transferred to subsequent drilling intervals for surface-torque reconstruction. After one-point baseline alignment, the remaining torque samples yielded mean relative reconstruction errors of 2.28%, 4.22%, and 3.21%, respectively. Removing these non-frictional contributions allows the effective drill-string–wellbore friction factor to be identified from a corrected surface load and subsequently compared with the measured torque response.

LubricantsVol. 14(11)
Xi'an Shiyou University (CN)
Openalex Percentile: Top 20%
Drilling and Well Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon