RIM Seminar- Rustam Isangulov

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Event Details
  • Date/Time:
    • Wednesday September 12, 2012 - Thursday September 13, 2012
      12:00 pm - 12:59 pm
  • Location: Manufacturing Research Center (MaRC) Auditorium | 813 Ferst Drive
  • Phone: (404) 385-3300
  • URL:
  • Email:
  • Fee(s):
    Free
  • Extras:
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Summaries

Summary Sentence: Schlumberger Presentation

Full Summary: How hard can it be to autonomously drill a hole in the ground?

How hard can it be to autonomously drill a hole in the ground?

 

There are massive challenges to cleanly, safely and economically reach and develop oil and gas energy reserves. We have to be able to hit reservoir locations that are uncertain.  They can be less than 10 ft thick and 40,000 ft from the surface. Telemetry is slow -- 10 bits/sec with high latency, and one command takes 2-4 minutes to send downhole. The downhole environment is dark in all frequencies and very hot. Our current electronics only work up to 150C, but we will need them to survive temperatures of 250C or more. The pressures and stresses are extreme--40+ kpsi and a million pounds of force may be needed to pull the drillstring out of the hole. Our measurements and actuators have to fit into tubes 4-9 inches in diameter and survive hours or days of stick-slip and shocks up to 500 g caused by the highly nonlinear dynamics.

 

Some questions we have to answer are:

  • How do get to the right place in a GPS denied zone, with uncertain low resolution maps that you have to update as you go?
  • How do you build tools, actuators and measurements systems, that will survive of thousands of hours in a hostile environments?
  • How do you control a system to give the accuracy and efficiency required when you only have sparse uncertain measurements with very low bandwidth, very high latency, and where you can never observe the actual state?
  • How do you keep the bit rotating smoothly when the pipe is more than a thousand times longer than the than its diameter?
  • How do you make autonomous systems in this environment with the capability to adapt plans and strategies depending on circumstances?

 

This is a truly multidisciplinary problem for control scientists, electrical, electronic and mechanical engineers, material scientists, geoscientist, chemists, physicist, signal processing scientists, soft matter physicists, machine learning scientists working together.

 

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Status
  • Created By: Nina White
  • Workflow Status: Review
  • Created On: Sep 10, 2012 - 1:02pm
  • Last Updated: Oct 7, 2016 - 9:59pm