Predictive Action Planning for Hole Cleaning Optimization and Stuck Pipe Prevention Using Digital Twinning and Reinforcement Learning
- Gurtej Singh Saini (The University of Texas at Austin) | Pradeepkumar Ashok (The University of Texas at Austin) | Eric van Oort (The University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- IADC/SPE International Drilling Conference and Exhibition, 3-5 March, Galveston, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2020. IADC/SPE International Drilling Conference and Exhibition
- 1.11.7 Cuttings Transport, 4 Facilities Design, Construction and Operation, 4.1 Processing Systems and Design, 1.11 Drilling Fluids and Materials, 4.1.1 Process Simulation, 1.6 Drilling Operations
- Decision Making, Hole Cleaning, Stuck Pipe, Reinforcement Learning, Digital Twinning
- 8 in the last 30 days
- 195 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
Poor hole cleaning leads to problems such as pack-offs, stuck pipe incidents, and lost circulation events due to increased equivalent circulating density (ECD). Hole cleaning issues can be mitigated by using a digital twinning system that constantly monitors borehole condition with real-time data and process models, and suggests optimal actions. The solution space of possible actions, however, is very large causing computational hurdles for real time implementation. This paper describes a time-efficient digital twinning approach that uses reinforcement learning (RL) to simulate scenarios corresponding to multiple hole cleaning actions.
Digital twinning of cuttings transport in a wellbore requires the development of a system with multiple integrated physics and data-based models to quantitatively detect symptoms of impending issues early, and to take actions to mitigate these problems. First, the state of the borehole is quantified in terms of ECD, concentration of cuttings in flow, and cuttings bed height. Next, a solution space of all legal and feasible actions based on the current system state is obtained. Finally, the alternate action sequences are evaluated to suggest the most suitable path forward.
To classify the state of the borehole in terms of ECD, cuttings bed height and cuttings concentration in the flow stream, hydraulics and cuttings transport models were implemented, tested and validated against real field and experimental data. Based on the state of the system, allowable actions were evaluated in terms of some combination of hole cleaning parameters that can be controlled in near real-time, such as flow rate, rotary speed, mud density, mud rheology and the weight on bit for rate of penetration (ROP) control. To limit the size of the solution space, those actions that were unrealistic for implementation in real-time were discarded. Also, any actions that violated the limits of the available drilling margin were discarded. Finally, by defining immediate rewards associated with different states-action pairs based on their effect on the wellbore stability and hole condition, the concepts of Markov reward process (MRP) and scenario realizations were used to suggest the optimal action for a given state.
The predicted output of the algorithm for multiple operational scenarios was validated by comparing it with actions that a hole cleaning / extended reach drilling (ERD) expert would have taken when given similar scenarios. The automated process of identifying hole cleaning system states, generating multiple viable hole cleaning action sequences, and finally evaluating the probability of successful hole cleaning for multiple actions in real-time and deciding the best course of action, is a novel contribution of this work. It will benefit practitioners who struggle with hole cleaning / stuck pipe-related non-productive time and pave the way for hole cleaning automation.
|File Size||5 MB||Number of Pages||18|
Aadnoy, B. S., Fazaelizadeh, M., & Hareland, G. (2010, October 1). A 3D Analytical Model for Wellbore Friction. Society of Petroleum Engineers. doi: 10.2118/141515-PA
Cayeux, E., Daireaux, B., Dvergsnes, E. W., Saelevik, G., & Zidan, M. (2012, January 1). An Early Warning System for Identifying Drilling Problems: An Example From a Problematic Drill-Out Cement Operation in the North-Sea. Society of Petroleum Engineers. doi: 10.2118/150942-MS.
Cayeux, E., Mesagan, T., Tanripada, S., Zidan, M., & Fjelde, K. K. (2014, March 1). Real-Time Evaluation of Hole-Cleaning Conditions With a Transient Cuttings-Transport Model. Society of Petroleum Engineers. doi: 10.2118/163492-PA.
Cordoso, J. V., Maidla, E. E., & Idagawa, L. S. (1995, June 1). Problem Detection During Tripping Operations in Horizontal and Directional Wells. Society of Petroleum Engineers. doi: 10.2118/26330-PA.
Duan, M., Miska, S. Z., Yu, M., Takach, N. E., Ahmed, R. M., & Zettner, C. M. (2009, June 1). Critical Conditions for Effective Sand-Sized Solids Transport in Horizontal and High-Angle Wells. Society of Petroleum Engineers. doi: 10.2118/106707-PA
Erge, O., Ozbayoglu, E. M., Miska, S. Z., Yu, M., Takach, N., Saasen, A., & May, R. (2014, March 4). The Effects of Drillstring Eccentricity, Rotation, and Buckling Configurations on Annular Frictional Pressure Losses While Circulating Yield Power Law Fluids. Society of Petroleum Engineers. doi: 10.2118/167950-MS.
Karstad, E., & Aadnoy, B. S. (1997, January 1). Analysis of Temperature Measurements during Drilling. Society of Petroleum Engineers. doi: 10.2118/38603-MS
Kelly, A. (2003). Decision Making Using Game Theory: An Introduction for Managers. Cambridge: Cambridge University Press. doi: 10.1017/CBO9780511609992.
Larsen, T. I., Pilehvari, A. A., & Azar, J. J. (1997, June 1). Development of a New Cuttings-Transport Model for High-Angle Wellbores Including Horizontal Wells. Society of Petroleum Engineers. doi: 10.2118/25872-PA.
Naganawa, S., & Nomura, T. (2006, January 1). Simulating Transient Behavior of Cuttings Transport over Whole Trajectory of Extended Reach Well. Society of Petroleum Engineers. doi: 10.2118/103923-MS
Nazari, T., Hareland, G., & Azar, J. J. (2010, January 1). Review of Cuttings Transport in Directional Well Drilling: Systematic Approach. Society of Petroleum Engineers. doi: 10.2118/132372-MS.
Ozbayoglu, M. E., Saasen, A., Sorgun, M., & Svanes, K. (2008, January 1). Effect of Pipe Rotation on Hole Cleaning for Water-Based Drilling Fluids in Horizontal and Deviated Wells. Society of Petroleum Engineers. doi: 10.2118/114965-MS.
Rubiandini R.S., R. (1999, January 1). Equation for Estimating Mud Minimum Rate for Cuttings Transport in an Inclined-Until-Horizontal Well. Society of Petroleum Engineers. doi: 10.2118/57541-MS
Saasen, A., & Løklingholm, G. (2002, January 1). The Effect of Drilling Fluid Rheological Properties on Hole Cleaning. Society of Petroleum Engineers. doi: 10.2118/74558-MS.
Saini, G., Ashok, P., van Oort, E., & Isbell, M. R. (2018, August 9). Accelerating Well Construction Using a Digital Twin Demonstrated on Unconventional Well Data in North America. Unconventional Resources Technology Conference. doi: 10.15530/URTEC-2018-2902186.
Sanchez, R. A., Azar, J. J., Bassal, A. A., & Martins, A. L. (1997, January 1). The Effect of Drillpipe Rotation on Hole Cleaning During Directional Well Drilling. Society of Petroleum Engineers. doi: 10.2118/37626-MS.
Sifferman, T. R., & Becker, T. E. (1992, June 1). Hole Cleaning in Full-Scale Inclined Wellbores. Society of Petroleum Engineers. doi: 10.2118/20422-PA.
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., Lillicrap, T., Simonyan, K., Hassabis, D. (2017, December 5). Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. https://arxiv.org/pdf/1712.01815.
Zhang, F., Miska, S., Yu, M., Ozbayoglu, E., Takach, N., & Osgouei, R. E. (2015, March 24). Is Well Clean Enough? A Fast Approach to Estimate Hole Cleaning for Directional Drilling. Society of Petroleum Engineers. doi: 10.2118/173681-MS.