Mipac

Mipac’s neural network reads flow in partially submerged pipe

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Mipac has developed a neural network to enhance drilling technology that measures flow in a partially submerged pipe on an oil rig.

There was no accurate measure of oil flow on the rig, located in the Gulf of Thailand, so Mipac suggested to its client that a neural network – a mathematical model of a non-linear system – would help create a clearer picture of what was happening at the sea bed and what quantities of oil were passing through the pipe.

“The overall aim is to improve safety and drilling performance and thereby optimise productivity,” Mipac Senior Systems Engineer Dr Simon Willis says.“Because the technology accurately reads what is going on at the drill hole and the flow, it reduces drilling costs and time and optimises productivity.”

It is also able to instantly assess a drill hole’s stability and have it cleaned if necessary.

“A drilling hole can collapse with a drill stuck in it and sometimes it is easier to let go of a hole, cut the drill off and move on,” Simon says.

“Because we have a much better idea of what is going on at the sea bed, we can predict what is going to happen and there is less chance of losing the hole.”

Mipac researched and developed the neural network, conducting testing at the client’s dedicated research and development plant. After a trial, the network was installed on the rig in January this year and Mipac engineers are currently ‘training’ the network.

“This involves a massive amount of data analysis, involving more than one million samples.” Simon says.

“We are reviewing one sample every second from three instruments via remote satellite. It is the first time data analysis of the neural network has been conducted at this level.

“We are confident the data is accurate because it is now standard operating procedure on the rig to monitor this data.

“And an audible alarm will soon be installed which will sound if data triggers safety concerns.”

Mipac’s client is happy to invest considerable time and money in this cutting-edge technology because, when proven, it will have application at any drilling site around the world.

Dr Simon Willis and Senior Design Engineer Gary Thompson, who wrote most of the PLC and training software, discuss neural network training.

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