By Magnus Tvedt
Fly with me in time. I work on a farm where the horse is used to plow the fields. Me and my workmates feed the horse and walk it up and down the acreage to create good growing conditions for the next harvest. We give the horse the rests, medicine and care it needs. We’re good at treating the horse, so we get good crops. But there are rumors of a cocky partner from the neighbor village harvesting the fields all by himself and his new steel horse, his tractor. How should I prepare for the new technology the tractor represents?
Enough potatoes, beam me back to the modern drill floors.
By clinging to a drilling process that is largely run by people, we are losing the benefits of automated systems. We have drilling competence, rig machinery competence, and we have IT competence in our business, but the link between them is not strong enough. A change towards automatic drilling operations is challenging, needed, and inevitably coming.
Drillers, engineers, and geologists all have important jobs, and perform skillfully in the hunt for oil. Years of education and experience are needed to operate successfully. But the repetitive operations and data analysis should be done by computers, not people. People are good at being creative; software does not forget or have a bad day.
Software can contain enormous amounts of solutions. Not limited by the current driller, drill crew or managements experience, but by background data and algorithms implemented into the software. By creating algorithms in software, changes in geology, borehole cleaning, kicks, and safety parameters can be monitored and predicted, and actions taken immediately. We can avoid expensive stuck situations, improve our geologic understanding, and drill faster based on stronger decisions.
The drillers on the drilling rig today operate cranes and instruct the drill crew how to handle the drill tools in a safe manner. The drillers get feedback from the crew and sensors on how the drilling is progressing. To run the machinery, the drillers have joysticks and screens connected to the control system. Based on the feedback, the driller controls the active safety systems, and optimizes the three main variables on the rig:
- Increases or decreases the pump rate of mud entering the well
- lowers or hoists the crane with the drill string attached
- adjusts rotation of the drill string
Some companies around the world are making software that takes data from the control systems, interprets these, and recommends actions for the drilling operation – essentially what the driller does – manually. The level of detail their software can interpret is far superior to their human counterpart. The drilling data shows trends on borehole stability, on mud condition, and on drilling progress. The result of these frontier companies is proving to be a step change in drilling performance and precision.
But a change in one technology always affects a whole system. Having advanced technical machinery on the rigs, require more advanced planning systems in the office. A written procedure explaining how to safely drill a well may be good enough for an experienced driller, but a computer must be fed with if(), while(), and then(), and precise input. You do not want to be responsible for a million-USD-a-day-rig waiting on an eternal do-loop to finish.
So how do we get there? The touch of the drillers, the experience of the engineers, the decisions of managers all have to be put down in software. The software has to reliable and useful for the operators, detailed enough to operate precision machinery, and easily accommodate new equipment or downhole challenges. Software is more vulnerable to mistakes or lack of detailed input than people are, so the precision in creating it is detrimental for the product.
But wait a minute; has this evolution from man-labor to machines already happen elsewhere? This reminds me of the industrial revolution which started when the tractors arrived; and how car manufactories went from people assembling cars to people watching machines assembling cars.
See you in the future.