AGR Software participated in SPE Intelligent Energy presenting a paper that focussed on using available and recorded data for improving well design, resulting in improved operational performance of new projects.
SPE Intelligent Energy (IE) aims to bring together the global E&P industry to discuss innovative technical solutions that are striving for fully integrated operations during the life cycle of an oilfield.
Following the theme “New Horizons: Intelligent Energy in a Changing World” and based on the learnings from the workshops with its software users, AGR Software presented a paper as part of the three day technical programme held in Aberdeen.
The paper focussed on using available and recorded data for improving well design, resulting in improved operational performance of new projects.
The benefit of reusing available data
In recent years, the amount of downhole drilling dynamics data has increased significantly. This has led to opportunities for a much higher degree of drilling optimisation than just a decade ago.
There is a large focus on enhancing drilling progress, but based on our own drilling project management experience and behavioural trends seen from our software users, we see a great potential for improving the reuse of available data. The reason why the oil and gas industry still has improvements to make when it comes to utilisation of operational data lies partly in the volume of data, but also in the strength of habit designing wells from scratch based on non-effective “lessons learned” spreadsheets and theoretical simulations.
The paper highlighted that optimising the drilling progress during operations is only one side of improving performance. The planning phase prior to spudding a well could contribute even more to the end result.
Optimising the well design and not just drilling
The paper suggests that the well design work process should be changed for field development, meaning that instead of leaning towards sophisticated theoretical simulations, one should instead focus on placing historic data at the centre of the project by using innovative technology.
Additionally, the paper discusses that it is not enough to compare the drilling parameters and well designs, it is also important to assess what operations were successful or unsuccessful together with the relevant data. This can be achieved by comparing KPIs of various drilling operations grouped according to drilling unit, location and well depth.
From offset well information, a probabilistic approach can be used for the planned well design when looking at time and cost. This includes risk factors and expected ranges for operational timings. From this, it can easily be seen where the largest opportunities for improvement are.
Based on several occasions where such an approach has been successfully implemented, it is evident that wells become more efficient over the course of a longer campaign. The key to success being reuse of all relevant historic data in the planning phase. The teams should identify and mitigate risks and optimise performance even before the bit is run in-hole.
The paper is available in the library with SPE-181027-MS reference.
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