Autonomous Directional Drilling Delivers Faster and Less Tortuous Wells

Abstract Wellbore trajectory control in directional well drilling activity is done via directional drilling methods. Directional drilling is a technique that traditionally involved considerable human skill and intervention to steer the well, measure responses, project wellbore position, and react to results. Achieving a required well directional profile required experienced personnel to continuously respond to well requirements. Improved efficiencies were needed to be introduced to this field to benefit from the digital capabilities available for the industry. Industry has strived to introduce a means of automating the directional drilling cycle where minimum human intervention would be needed. A system has been deployed in Middle East fields to automate the directional drilling workflow. The system uses advanced cloud-based software and connected intelligent systems to create a continuous feedback loop between the surface and downhole. The system reads the well trajectory data sent from downhole equipment and processes the trajectory compared to required target objectives, evaluates multiple projection options before selecting an optimized projection and sends surface communications to downhole equipment to follow the needed path with no human intervention. A major operator focused on evaluating this system on multiple wells. Three candidate wells were selected to evaluate their directional responses compared to similar ones in the same basin. Detailed comparison for the three wells focused on achieving the required trajectories, rate of penetration (ROP) gains, reduction in the number of surface downlink commands compared to offsets to demonstrate better directional control and reduction in tortuosity levels compared to offsets. On these three wells, a total footage of 6,473-ft was drilled fully autonomously with no human intervention on directional drilling requirements. All profiles were successfully executed where computations, projections and commands were done through the automation system. Average ROP showed improvement reaching 24% compared to offsets. The number of surface downlink commands showed reduction up to 39% compared to offsets. Well tortuosity showed reduction up to 22% compared to offsets allowing for easier bottom-hole assembly tripping and tubular running. The implemented autonomous directional drilling system has proven to deliver multiple directional profiles with no human intervention. The system demonstrated that digital capabilities can be utilized to improve directional drilling efficiency and to deliver further performance gains and smoother wells.

Authors

Institutions

Publication Details

Published
2024-11-04
DOI
https://doi.org/10.2118/222572-ms
Citations
1
Primary Topic
Drilling and Well Engineering
Type
article
Field-Weighted Citation Impact
0.34
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Autonomous Directional Drilling Delivers Faster and Less Tortuous Wells

Muhammad Ibrahim, Abdullah M. Al Dossary, Viviane Maia Barreto de Oliveira, Ahmed Osman
1 citations
Drilling and Well Engineering
0.34
article

Autonomous Directional Drilling Delivers Faster and Less Tortuous Wells

Muhammad Ibrahim, Abdullah M. Al Dossary, Viviane Maia Barreto de Oliveira, Ahmed Osman
article en
1 citations

Abstract

Abstract Wellbore trajectory control in directional well drilling activity is done via directional drilling methods. Directional drilling is a technique that traditionally involved considerable human skill and intervention to steer the well, measure responses, project wellbore position, and react to results. Achieving a required well directional profile required experienced personnel to continuously respond to well requirements. Improved efficiencies were needed to be introduced to this field to benefit from the digital capabilities available for the industry. Industry has strived to introduce a means of automating the directional drilling cycle where minimum human intervention would be needed. A system has been deployed in Middle East fields to automate the directional drilling workflow. The system uses advanced cloud-based software and connected intelligent systems to create a continuous feedback loop between the surface and downhole. The system reads the well trajectory data sent from downhole equipment and processes the trajectory compared to required target objectives, evaluates multiple projection options before selecting an optimized projection and sends surface communications to downhole equipment to follow the needed path with no human intervention. A major operator focused on evaluating this system on multiple wells. Three candidate wells were selected to evaluate their directional responses compared to similar ones in the same basin. Detailed comparison for the three wells focused on achieving the required trajectories, rate of penetration (ROP) gains, reduction in the number of surface downlink commands compared to offsets to demonstrate better directional control and reduction in tortuosity levels compared to offsets. On these three wells, a total footage of 6,473-ft was drilled fully autonomously with no human intervention on directional drilling requirements. All profiles were successfully executed where computations, projections and commands were done through the automation system. Average ROP showed improvement reaching 24% compared to offsets. The number of surface downlink commands showed reduction up to 39% compared to offsets. Well tortuosity showed reduction up to 22% compared to offsets allowing for easier bottom-hole assembly tripping and tubular running. The implemented autonomous directional drilling system has proven to deliver multiple directional profiles with no human intervention. The system demonstrated that digital capabilities can be utilized to improve directional drilling efficiency and to deliver further performance gains and smoother wells.

Saudi Aramco (Saudi Arabia) (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Drilling and Well Engineering
0.34
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.