Time to Improve, Time for Creativity

Posted 28.05.2019 09:05 by Eirik Lyngvi

Time to Improve, Time for Creativity

Revisit the Preliminary Well Designs

Preliminary well designs are often stored in documents with titles like "Basis of Design", which outline geology, casing design, drilling practices, pressures, fluid systems, and more. These documents create an outer perimeter of the well design: Stay within these boundaries, and you should be ok.

However, Data Science tools now enable engineers to analyse large amounts of wells up front, and use large data sets of historic wells and events to find problems and opportunities. Rather than building a static document, the engineer can create a dynamic model based on the context of the well or field she is planning. New work processes in Preliminary Well Designs allow the engineers to analyze more and type less.

But it's not enough to find more offset wells in the data set, you also need to verify that your Preliminary Well Design is viable. Modern API solutions let you trigger the calculations you want, so that you can get quick thumbs up for all your Preliminary Well Designs.

Improve Safety, Cost and Risk

Making the Preliminary Well Designs dynamic, and connected to data and integrated technical calculations, opens the door for creativity in well design. More creativity improves cost and risk margins, which in turn set the table for early improvements and more precise planning. Data Driven Preliminary Well Designs let you prototype and analyze different ideas, and provide instant feedback on risk and complexity of the different scenarios.

It's not that we haven't been able to calculate steel- and fluid properties before, the clue with the Data Driven Preliminary Well Designs is to give just the right information at the right time, using experience data to populate input parameters, and provide the engineers with a default setup of their scenario.

Our experience with well planning is that in more than 75% of the time technical calculations are done, the outcome is known to the engineer, but they are still required to spend the weeks necessary to complete them. Why not spend that time improving and looking for savings or risk reductions?

Let's Explore an Example

An engineer spends 2-4 weeks in high concentration, gathering information, assuming input for calculations and simulating well operations and load cases in detail. In addition she is troubleshooting possible well related problems in search for a minimum viable well design, given the uncertainty she can see. Not a simple task.

She wouldn't risk having to do this more than once per project, that would be a waste of time. So she will make sure this is the last task on the agenda before writing the well program, the last 2-4 weeks of a 3-6 month project, to avoid changes and reruns.

But while she is going through the technical calculations and simulations, she stops and wonders if not that new screen technology could have simplified the lower completion design, or if a slightly different mud system could have reduced the fluid friction in one of the sections. And a lot of other questions. But there is no time for innovation and creativity, the operations won't wait for her to finish. So she paces on to get through to a viable minimum design, and moves on to order equipment and prepare logistics.

In a world of Data Driven Preliminary Well Designs, the engineer would start out with an offset review consisting of not only nearby wells, but a large number of wells with similar traits from all over her database. From their collective experience, she can sketch out 10-15 well designs in a day and get instant results from the automatically triggered calculations and risk analyses.

She can see that the running loads for tubulars have plenty of collapse margins in 10 of her designs, but 5 will require more detailed reviews. The ECD calculations are good in most cases, but above or close to critical levels in 3 of the designs.

Now she knows where to dig into the details, and can focus her efforts on value adding planning.

Stay tuned for the next writeup on how to make Data Driven Preliminary Well Designs with ProWellPlan.

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The Team

Pro Well Plan AS is based in Bergen, Oslo and
Magnus Tvedt
CEO Magnus Tvedt magnus.tvedt@prowellplan.com
Nicholas Mowatt Larssen
CTO Nicholas Mowatt Larssen nimola@prowellplan.com
Cathrine Tangerås Eide
Project Manager Cathrine Tangerås Eide cathrine.eide@prowellplan.com
Khushal Adlakha
Data Scientist Khushal Adlakha khushal.adlakha@prowellplan.com
Torgeir Lassen
CFO Torgeir Lassen torgeir.lassen@prowellplan.com
Eirik Lyngvi
Software Developer Eirik Lyngvi eirik.lyngvi@prowellplan.com

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