Drilling Safely in the Arctic Ocean

Liptak Shows Why Full Automation Could Improve the Safety of Offshore Drilling in and Transportation from the Arctic Ocean

By Bela Liptak

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The controlled process is the ship, and the load is the wind force. The dynamics of the process are a function of the ship's inertia, response time and speed of response (process gain = GP). The rode tension sensor has its own gain (GTS), and so does the manipulated variable, the winch (GW). Therefore, in order to properly control this loop, we must correctly "size the valve" (make the winch powerful enough). We also have to select the right winch gain (GW). It has to provide a fast enough response, and has to have a variable speed to compensate for the variable gain (GP) due to the changing load (the changing force and direction of the wind). Knowing these gains, we can "tune the loop" by adjusting the gain of the rode position controller (GPC), so that the loop gain (GL) will be about 0.5. {GL = (GP)(GTS)(GW)(GPC)}.

Adding Feedforward to the Control Envelope

Figure 4
CLICK ON IMAGE TO ENLARGE
Stable operations

Figure 4: The control algorithm that sends the individual
setpoints to the winches keeps the ship inside a
3-dimensional safe operating envelope which is
"feedforward adjusted" as a function of wind strength
and direction.
Courtesy of Roy E. Floysvik/Norwegian Petroleum Museum

The strength and the direction of the force generated by the wind is constantly changing. Therefore, to stabilize the ship, the previously described PID tuning by itself is insufficient. "Anticipation" (feedforward) must be added to it. This means that we must continuously measure the dynamics of the wind (the load) and as soon as it changes, we must start responding to it (Figure 4).

Naturally, this requires a sophisticated computer model, which could theoretically be prepared by scientists (weather scientists, naval architects, etc.), but I would not do that. I trust Murphy's Law more than science. I would simply install a self-teaching artificial neural network (ANN) algorithm model (Chapter 2.16 in Volume 2 of The Instrument Engineeer's Handbook) and let it develop the process model automatically just by watching what is happening in the real world.
Just as in case of all other new industries, here too we have to overcome the hurdles of secrecy and ego. In some corporations there is a policy of not letting outsiders "stick their nose" into what they are doing, and there is also a sense of pride that they "know better." These emotional and public relations hurdles can only be overcome if our profession proves that it can offer real benefit to the off-shore drilling industry. If we could show them that applying the know-how, we have accumulated by automating the traditional industrial processes for a century is practical, we could prevent accidents such as Deepwater Horizon or Sakhalin.

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