Reporting structure and challenges

5.3.1. Level of detail

As the discussion on each hole section performance shows it is almost impossible to identify the effect of Chen’s drilling optimization as defined in the introduction of this thesis. To do so one needs very detailed information on what measures and actions that was taken. The level of detail observed in the reports studied in this thesis was in general not high or consistent enough to make a quantification of the effect. This creates an uncertainty element related to identifying or explaining measures or performance target development. If there is a large level of detail in a report this allow for identification of the root cause of discrepancies. One can confirm if the discrepancy is due to a lower performance or a direct measure taken to mitigate a problem. If the detail level is too low one will not be able to identify reasons for potential discrepancies and may assume that no measures were taken. This may easily cause unfavorable or an incorrect picture of the drilling optimization service or where the improvement potential for the operation actually is situated. This has been the case in this study and as a result, the discussion has become more general and moves towards evaluating trends and averages.

One point worth mentioning is that this may not be a bad approach, because it reflects the total or real drilling efficiency seen from an economical point of view. For the oil company the

optimization doesn’t add real value before it actually reduced the time used to drill the well thereby reducing their costs or losses.

The Value of Drilling Optimization Page 100 5.3.2. Consistent measurements

Another challenge is the uncertainty related to the operational hours reported. As mentioned and shown in the discussion, it may occur that the end time noted is reported after the tools have been layed down on pipedeck instead of when they come out of the rotary table. This may create a difference of up to several hours that produces an incorrect picture of the operation efficiency.

A similar issue is related to measuring the BRT – Below Rotary Table hours. Some starts counting from when the bit is below/above rotary. Others start when the BHA is below/above.

Looking on one well this doesn’t have a large impact, but when comparing wells it may create inconsistencies and again an incorrect impression of the situation. This creates an inconsistency that can be seen as a different value recorded for operational and BRT hours. In some cases it shows that the operational hours are larger than the BRT hours like when comparing the first 4 wells in graph 24 and 14. In other cases the operational hours are less than the BRT hours as when comparing the first 4 wells in graph 25 and 18. It is hard to say which one is more correct but in general the fluctuations are less for BRT hours than for operational hours and is why, as also elaborated in chapter 4.6, BRT hours have been used to reflect total time usage.

A solution for both these problems would be to incorporate a note in the handling procedures and specify that BRT is to be counted from bit or BHA is below rotary table. In addition a note should be added in a comment if the tools are layed down on deck before the tool memory data is downloaded.

5.3.3. Further work

The value of drilling optimization is not easy to study. This is because one never drill the same well twice. Even if wells are very similar, like the wells in this study, the reference will be debatable. Nevertheless, it would be very interesting to be able to say more confidently something about the value of Drilling Optimization as per Chen’s definition [4]. In relation to this it seems natural to involve statistics and probability.

The Value of Drilling Optimization Page 101 If one could assure consistent reporting of the correct information, one would after a certain period of time have the possibility to use the information to generate a relation between the jobs performed by the drilling optimization specialist, time spent drilling the section and the number of drilling challenges and unfavorable events. The probability distribution of different

unfavorable events could be established based on the number of occurrences of the event in a certain period of time or number of wells. These occurrences could further be separated into categories based upon what drilling optimization services that were used. Simulations could then be made on the probability of the event occurring. The value of the drilling optimization could then be displayed in terms of the difference in the probability of occurrence for different time consuming events, with and without drilling optimization specialist. Further, the probability for an event to occur depending on what formation it was drilled through, what hole size etc. could be made to broaden the analysis.

The reporting structure would need to be set up with an easy-to-use interface and allow for easy exportation of the data into spreadsheets and simulation software. The “extra” work for the personnel required to perform the reporting should be minimized to avoid the phenomenon

“reluctance to change”.

The Value of Drilling Optimization Page 102