On the Benefits of Automation in Improving the Drilling Efficiency in Offshore Activities | SLB

On the Benefits of Automation in Improving the Drilling Efficiency in Offshore Activities

已发表: 03/04/2014

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Schlumberger Oilfield Services

This paper discusses the results of a study on the benefits of automation in general, and improved instrumentation and control capabilities in particular, to the drilling efficiency in the presalt.

The industry is facing certain obstacles in improving the drilling efficiency in several offshore operations, including the high cost deepwater jobs. Those include, amongst others, limited or low-quality data measurements, and non-systematic practices in controlling the operating parameters. The end result is sub-optimal control of the operating parameters (rotary speed, weight-on-bit, and flow), which can directly affect the rate of penetration (ROP).

The first phase of a joint project between Petrobras and Schlumberger had the objective of producing a software simulator of the drilling process, and capture the dynamics of the bit-rock interaction, the axial and torsional dynamics of the bottom-hole assemble (BHA) and the drill-string, as well as the dynamics of the rig equipment (pumps, top-drive, draw-works). The objective of this simulator was to study the transient behavior of drilling parameters (WOB, pressures, RPM, etc.) both at the surface as well as downhole, as a result of formation changes, or changes in the surface operating parameters.

The objective of this study was to see how an improved (automatic) control of the surface operating parameters can result in better, more accurate control of all the variables that affect the drilling process / efficiency. The parameters studied were hole cleaning, ECD, pressure transients (surge/swab), stick/slip, and others. One aspect of this study was the effect that the availability of downhole measurements can have on the calibration of the models used in this simulator, so it can more accurately capture the true dynamics of the drilling process.

Once the simulator is calibrated (with or without downhole data), the next step is to use it in real-time to evaluate various control strategies, and ultimately decide what is the right set of operating parameters that will optimize a composite cost function: a linear combination of ROP, drilling efficiency, hole cleaning, or any other metric that is important in optimizing the drilling process.

A trade-off that had to be made early on in this project was between the real-time capability of this simulator, and the computational complexity of the underlying models. The models created were specifically built in order to run fast, allowing this real-time calibration and evaluation of the various control strategies. After this concept has been validated running remotely, in parallel with actual drilling operations, the objective is to develop a product that can be deployed and act as an "advisor" to drilling personnel to help support their decision making process.

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