Insights Into the Physical Phenomena That Influence Automatic Gain/Loss Detection During Drilling Operations
- Eric Cayeux (International Research Institute of Stavanger) | Benoit Daireaux (International Research Institute of Stavanger)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- March 2016
- Document Type
- Journal Paper
- 13 - 24
- 2016.Society of Petroleum Engineers
- Kick detection, Real-time monitoring, Transient hydraulic
- 3 in the last 30 days
- 403 since 2007
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Abnormal variations of the pit volume are a prime indicator of mud losses and formation-fluid influxes. However, the detection of gain and loss at the pit level can be difficult because of the transient behavior of several components in the hydraulic loop. For instance, while circulating, the increased pressure inside the drillstring and the annulus results in a larger amount of mud taken by the well compared with static conditions because of the compressibility of the drilling fluid. Furthermore, the transport and separation of cuttings also influence volume variations in the pit. Finally, the retention capacity of some of the mud-transport and -treatment equipment (e.g., return flowline, shakers, sand trap, degasser, transfer pit) has a direct impact on the active-pit level. All these effects are transient and can cause substantial variations of the active-pit volume that may interfere with any solutions attempting to automatically detect gains or losses.
Most of these effects are well-known and are dealt with in a pragmatic way with fingerprinting between the current pit-volume variation and a reference pattern obtained under similar drilling conditions. Nevertheless, the fingerprinting method has its limitations when the current drilling-parameter sequence does not have an obvious reference pattern. Consequently, automatic gain/loss detection algorithms using pattern matching with previously observed transient periods may have difficulties reducing the number of false alarms to an acceptable level.
Measurement of the flow rate out close to the outlet of the well is another way to detect gains and losses. It has the advantage of not being influenced by the side effects of mud-treatment equipment. However, it is an instantaneous value instead of being cumulative as is the pit volume, and therefore requires precise measurements to be reliable. The limitations of the two mostly used flow-rate-out sensors, the flow paddle and the Coriolis flowmeter, are discussed in Cayeux and Daireaux (2013).
We present in this paper an analysis of the transient phenomena that limit the existing detection techniques, and explain how those effects can be accounted for with proper modeling. This leads to a significant extension of the domain of applicability of the traditional approaches.
|File Size||1 MB||Number of Pages||12|
Aldred,W., Hutin, R., Luppens, J. et al. 2008. Development and Testing of a Rig-Based Quick Event Detection Systemto Mitigate Drilling Risks. Presented at the IADC/SPE Drilling Conference, Orlando, Florida, USA, 4–6March. SPE-111757-MS. http://dx.doi.org/10.2118/111757-MS.
Anfinsen, B. T. and Rommetveit, R. 1992. Sensitivity of Early Kick Detection Parameters in Full-Scale Gas Kick Experiments With Oil and Water-Based Drilling Muds. Presented at the IADC/SPE Drilling Conference, New Orleans, 18–21 February. SPE-23934-MS. http://dx.doi.org/10.2118/23934-MS.
ASME Shale Shaker Committee. 2005. Drilling Fluid Processing Handbook. Elsevier.
Brakel, J., Tarr, B., Cox, W. et al. 2015. SMART Kick Detection: First Step on the Well-Control Automation Journey. SPE Drill & Compl 30 (3): 233–242. SPE-173052-PA. http://dx.doi.org/10.2118/173052-PA.
Cayeux, E. 2012. Safe Mud Pump Management While Conditioning Mud. Presented at the 2012 IFAC Workshop on Automatic Control in Offshore Oil and Gas Production, Trondheim, Norway, 31 May–1 June. http://dx.doi.org/10.3182/20120531-2-NO-4020.00018.
Cayeux, E. and Daireaux, B. 2013. Precise Gain and Loss Detection Using a Transient Hydraulic Model of the Return Flow to the Pit. Presented at the SPE/IADC Middle East Drilling Technology Conference & Exhibition, Dubai, 7–9 October. SPE-166801-MS. http://dx.doi.org/10.2118/166801-MS.
Cayeux, E., Mesagan, T., Tanripada, S. et al. 2014. Real-Time Evaluation of Hole Cleaning Conditions Using a Transient Cuttings Transport Model. SPE Drill & Compl 29 (1): 5–21. SPE-163492-PA. http://dx.doi.org/10.2118/163492-PA.
Clark, R. K. and Bickham, K. L. 1994. A Mechanistic Model for Cuttings Transport. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 25–28 September. SPE-28306-MS. http://dx.doi.org/10.2118/28306-MS.
Fraser, D., Lindley, R., Moore, D. D. et al. 2014. Early Kick Detection Methods and Technologies. Presented at the SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. SPE-170756-MS. http://dx.doi.org/10.2118/170756-MS.
Hargreaves, D., Jardine, S., and Jeffryes, B. 2001. Early Kick Detection for Deepwater Drilling: New Probabilistic Methods Applied in the Field. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 30 September–3 October. SPE-71369-MS. http://dx.doi.org/10.2118/71369-MS.
Le Blay, F., Villard, E., Hilliard, S. et al. 2012. A New Generation of Well Surveillance for Early Detection of Gains and Losses When Drilling Very High Profile Ultradeepwater Wells, Improving Safety, and Optimizing Operating Procedures. Presented at the SPETT 2012 Energy Conference and Exhibition, Port of Spain, Trinidad, 11–13 June. SPE-158374-MS. http://dx.doi.org/10.2118/158374-MS.
Lorentzen, R. J., Fjelde, K. K., Frøyen, J. et al. 2001a. Underbalanced Drilling: Real Time Data Interpretation and Decision Support. Presented at the SPE/IADC Drilling Conference, Amsterdam, 27 February–1 March. SPE-67693-MS. http://dx.doi.org/10.2118/67693-MS.
Lorentzen, R. J., Fjelde, K. K., Frøyen, J. et al. 2001b. Underbalanced and Low-head Drilling Operations: Real-Time Interpretation of Measured Data and Operational Support. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 30 September–3 October. SPE-71384-MS. http://dx.doi.org/10.2118/71384-MS.
Maus, L. D., Tannich, J. D., and Ilfrey, W. T. 1979. Instrumentation Requirements for Kick Detection in Deep Water. J Pet Technol 31 (8): 1029–1034. SPE-7338-PA. http://dx.doi.org/10.2118/7338-PA.
McCann, D. P., White, D. B., Marais, L. et al. 1991. Improved Rig Safety by Rapid and Automated Kick Detection. Presented at the SPE/IADC Drilling Conference, Amsterdam, 11–14 March. SPE-21995-MS. http://dx.doi.org/10.2118/21995-MS.
Mills, I., Reitsma, D., Hardt, J. et al. 2012. Simulator and the First Field Test Results of an Automated Early Kick Detection System That Uses Standpipe Pressure and Annular Discharge Pressure. Presented at the SPE/IADC Managed Pressure Drilling and Underbalanced Operations Conference and Exhibition, Milan, Italy, 20–21 March. SPE-156902-MS. http://dx.doi.org/10.2118/156902-MS.
Nygaard, G., Tennøy, S. M., Carlsen, L.A. et al. 2012. AWCS M2: Influx Detection for MPD in Virtual Rig. International Research Institute of Stavanger, Research Report 2012/032.
Orban, J. J., Zanker, K. J., and Orban, A. E. 1987. New Flowmeters for Kick and Loss Detection During Drilling. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 27–30 September. SPE-16665-MS. http://dx.doi.org/10.2118/16665-MS.
Orban, J. J. and Zanker, K. J. 1988. Accurate Flow-out Measurements for Kick Detection, Actual Response to Controlled Gas Influxes. Presented at the IADC/SPE Drilling Conference, Dallas, 28 February–2 March. SPE-17229-MS. http://dx.doi.org/10.2118/17229-MS.
Reitsma, D. 2010. A Simplified and Highly Effective Method to Identify Influx and Losses During Managed Pressure Drilling Without the Use of a Coriolis Flowmeter. Presented at the SPE/IADC Managed Pressure Drilling and Underbalanced Operations Conference and Exhibition, Kuala Lumpur, 24–25 February. SPE-130312-MS. http://dx.doi.org/10.2118/130312-MS.
Reitsma, D. 2011. Development of an Automated System for the Rapid Detection of Drilling Anomalies Using Standpipe and Discharge Pressure. Presented at the SPE/IADC Drilling Conference and Exhibition, Amsterdam, 1–3 March. SPE-140255-MS. http://dx.doi.org/10.2118/140255-MS.
Shafer, D. M., Loeppke, G. E., Glowka, D. A. et al. 1992. An Evaluation of Flowmeters for the Detection of Kicks and Lost Circulation During Drilling. Presented at the IADC/SPE Drilling Conference, New Orleans, 18–21 February. SPE-23935-MS. http://dx.doi.org/10.2118/23935-MS.
Speers, J. M. and Gehrig, G. F. 1987. Delta Flow: An Accurate, Reliable System for Detecting Kicks and Loss of Circulation During Drilling. SPE Drill Eng 2 (4): 359–363. SPE-13496-PA. http://dx.doi.org/10.2118/13496-PA.
Tarab, H. A., Haberer, S. M., Says, I. P. et al. 2013. Automated Alarms for Smart Flowback Fingerprinting and Early Kick Detection. Presented at the SPE/IADC Drilling Conference and Exhibition, Amsterdam, 5–7 March. SPE-163474-MS. http://dx.doi.org/10.2118/163474-MS.
Zamora, M., Roy, S., Slater, K. S. et al. 2013. Study on the Volumetric Behavior of Base Oils, Brines, and Drilling Fluids Under Extreme Temperatures and Pressures. SPE Drill & Compl 28 (3): 278–288. SPE-160029-PA. http://dx.doi.org/10.2118/160029-PA.
Zhou, J., Nygaard, G., Godhavn, J. M. et al. 2010. Adaptive Observer for Kick Detection and Switched Control for Bottomhole Pressure Regulation and Kick Attenuation During Managed Pressure Drilling. In Proc., American Control Conference, Baltimore, Maryland, USA, 30 June–2 July, 3765–3770.