Challenges and Lessons of Implementing a Real-Time Drilling Advisory System
- Adam Wilson (JPT Special Publications Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- February 2018
- Document Type
- Journal Paper
- 49 - 51
- 2017. Society of Petroleum Engineers
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- 110 since 2007
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This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 187447, “Challenges and Lessons From Implementing a Real-Time Drilling Advisory System,” by Benjamin J. Spivey, SPE, Gregory S. Payette, SPE, and Lei Wang, SPE, ExxonMobil Upstream Research Company; Jeffrey R. Bailey, SPE, ExxonMobil Development Company; Derek Sanderson, XTO Energy; and Stephen W. Lai, SPE, Behtash Charkhand, SPE, and Aaron Eddy, SPE, Pason Systems, prepared for the 2017 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 9–11 October. The paper has not been peer reviewed.
This paper discusses the technical challenges related to implementing a rigsite, real-time drilling advisory system and current solutions to these challenges. The system uses a data-driven response-surface model based on physics-based calculations to optimize rate of penetration (ROP) while minimizing drilling-vibration dysfunction with regard to lateral (whirl) and torsional (stick/slip) vibrational modes. Minimizing these vibrations is important to mitigate bit damage that can lead to reduced ROP and increased bit trips.
The system is a rigsite software application that should be deployed in view of the driller. Fig. 1 shows a driller-cabin deployment.
The software contains capabilities for real-time surface drilling-data acquisition, drilling-performance estimation, vibration analysis, surface trends for drilling performance, and drill- off-test guidance for drilling optimization. The system primarily serves as an open-loop advisory tool but retains capabilities for closed-loop autodriller and topdrive control. The user interface provides the rigsite personnel with drilling-performance surface trends (e.g., ROP, drilling efficiency, and stick/slip vibration), bit aggressiveness and depth-of-cut (DOC) calculations, and drilling-parameter set-point recommendations on the basis of the surface trends.
Data Input and Output. The system operates on 1-second data provided from the electronic data-recording equipment. Input data consist of data channels included among standard or spare Well Information Transfer Specification (WITS) Record 1 items—block height, weight on bit (WOB), rotary speed, mud-flow rate, hole depth, bit depth, torque, and differential pressure.
Drilling-Performance Estimation. The system filters and preprocesses the raw WITS Record 1 data to calculate the drilling performance variables: ROP, surface mechanical specific energy (MSE), motor MSE, DOC divided by WOB, torsional-severity estimate (TSE), bit aggressiveness, and DOC.
Performance Averaging and Modeling. The measures of drilling performance, primarily the ROP, drilling efficiency, and stick/slip indicator, are averaged over depth drilled to produce a mean or median value referred to as a “response point.” A clustering algorithm groups these response points in the 2D drilling-parameter space. The response-point groups, or “calibration points,” serve as estimates of the drilling set points to measure whether the drilling-parameter space is explored sufficiently to produce an accurate response-surface model.
Optimization. An objective function merges the response surfaces of multiple performance objectives into a single objective surface. This objective function makes a tradeoff between the ROP, drilling efficiency, and stick/slip terms.
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