05/01/25

Automated Correction of Drillstring Data for Improved Reliability and Trust in Use of Physics-Based Models in Drilling Advisory Systems

written by: D. Yoon; M. Yi; J. Cortez; M. Behounek; P. Ashok

Paper presented at the SPE/IADC International Drilling Conference and Exhibition, Stavanger, Norway, March 2025. Paper Number: SPE-223786-MS A major challenge in utilizing physics-based models such as torque and drag (T&D), hydraulics, cutting transport, drillstring dynamics, etc., in real-time, and with high reliability and confidence has been the lack of accuracy in drillstring data available as input…

05/01/25

Enhancing Offshore Drilling Safety: Identification and Integration of Leading Indicators for Loss of Offshore Well Control

written by: Chen Wei; Yuanhang Chen; Oscar Gabaldon; Omar Montes; Pradeep Ashok; Michael Yi; Jyotsna Sharma

Paper presented at the Offshore Technology Conference, Houston, Texas, USA, May 2025. Paper Number: OTC-35818-MS In an effort to enhance safety and efficiency in offshore drilling operations, this research addresses critical gaps in the current understanding and application of leading indicators for Loss of Well Control (LOWC) events. Existing indicators often fall short in predicting LOWC…

06/08/24

Applications of Large Language Models in Well Construction Planning and Real-Time Operation

written by: Michael Yi; Kamil Ceglinski; Pradeepkumar Ashok; Michael Behounek; Spencer White; Trey Peroyea; Taylor Thetford

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, Galveston, Texas, USA, March 2024. In today’s well construction operations, a substantial volume of data is generated and stored across multiple databases. The primary objective being to use them as a guide for future well construction optimization. However, much of this data gets lost in…

06/08/24

Prevention of Stuck Pipe Events and Robust Real-Time Identification of Root Cause Using Physics Based Models in Combination with Bayesian Network Models

written by: Michael Yi; Pradeepkumar Ashok; Michael Behounek; Spencer White; Trey Peroyea; Taylor Thetford; Gary Hickin; Julie Pearce

Paper presented at the International Petroleum Technology Conference, Dhahran, Saudi Arabia, February 2024. Paper Number: IPTC-24141-MS When stuck pipe incidents happen, they can drastically increase the cost of a well. Although much progress has been made in stuck pipe prevention it has not been eliminated. Therefore, there is an ever increasing need to be able to…

10/10/23

The Secrets to Successful Deployment of AI Drilling Advisory Systems at a Rig Site: A Case Study

written by: Michael Behounek; Pradeepkumar Ashok

Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, October 2023. Paper Number: SPE-215132-MS Developing artificial intelligence (AI)-based drilling advisory software is generally straightforward when good quality labeled data are available. However, deploying such systems in the field for use by a rig crew requires careful planning and execution and…

05/14/23

An Integrated Data and Physics-based Temperature Model for the Real-Time Estimation of Bottomhole Temperature for Downhole Tool Failure Prevention

written by: Sadjad Naderi, Naveen Velmurugan, Pragna Nannapaneni, Michael Yi, Pradeepkumar Ashok

Stanford Geothermal Workshop, 2024. Efficient drilling of geothermal wells hinges on a thorough comprehension of temperature distribution along the wellbore, vital for preventing tool failures and reducing non-productive time (NPT). This involves ascertaining the requisite mud cooling at the surface and optimizing circulation flow rates to extract heat effectively. While extensive theoretical work exists in…

05/09/23

Deployment of a Hybrid Machine Learning and Physics Based Drilling Advisory System at the Rig Site for ROP Optimization

written by: Michael Behounek; Kirt McKenna; Taylor Thetford; Trey Peroyea; Michael Roberts; Julie Pearce; Gary Hickin; Pradeepkumar Ashok; Michael Yi; Dawson Ramos.

During well construction, automatic monitoring of the sensor signals for drilling dysfunction detection through pattern recognition algorithms is key to improving rate of penetration (ROP) and preventing tool failure. The addition of physics-based models can enable further improvement, but often one is limited by the contextual data needed by these models, as well as the…

03/18/22

Automated Merging of Time Series and Textual Operations Data to Extract Technical Limiter Re-Design Recommendations

written by: Michael Yi; Pradeepkumar Ashok; Dawson Ramos; Spencer Bohlander; Taylor Thetford; Mojtaba Shahri; Mickey Noworyta; Trey Peroyea; Michael Behounek.

Paper presented at the IADC/SPE International Drilling Conference and Exhibition, Galveston, Texas, USA, March 2022. Paper Number: SPE-208745-MS. Published: March 01 2022. During the construction planning phase of any new well, drilling engineers often look at offset well data to identify information that could be used to drill the new well more efficiently. This is generally a…

09/15/21

A Real-Time Probabilistic Slide Drilling Dysfunction Advisory to Assist Remote Directional Drilling Operations

written by: Dawson Ramos; Pradeepkumar Ashok; Michael Yi; John D’ Angelo; Ian Rostagno; Spencer Bohlander; Taylor Thetford; James Moisan; Michael Behounek; Mickey Noworyta; Jason Beasley; Joshua Wilson.

Paper presented at the SPE Annual Technical Conference and Exhibition, Dubai, UAE, September 2021. Paper Number: SPE-205984-MS. Published: September 15 2021. Current slide drilling practices rely heavily on the intuition of the directional drillers to identify and correct drilling dysfunctions. Monitoring numerous dysfunctions simultaneously requires more complex analysis than can be done manually in real-time. There is…