Learning from mistakes: Creating value from understanding the reasons we fail

Written by
Katya (Ekaterina) Casey
Learning from mistakes: Creating value from understanding the reasons we fail

It is overall our view that creaming curve analysis is most valuable when it discriminates between the plays and playtests, when it may indeed identify missed opportunities or even new plays when combined with as thorough an understanding of the history of the basin as possible. "Lumping" the statistics together appears not to serve this purpose, at least in predictive mode, when trying to build a new portfolio and incorporate the potential value of speculative or conceptual plays.

Corporate growth and continuous improvement involve the search for new knowledge and should be augmented by in-depth reviews of failures to design strategies and action plans based on innovative insights.  This forms the basis of a learning organizational culture.  On a personal level, we know that errors are somewhat inevitable and should not discourage experimentation. Owning one’s errors and learning from them invaluable lessons is the precursor to many successes and breakthroughs.

Corporations,despite often having stringent protocols in areas like HSE or business ethics,often prove to be vulnerable to error repetition.  In the oil and gas industry, this is most likely to be manifested in the technical arena, with "mistakes" made when drilling and the target prospect fails or where the results fall outside the predicted range or fail for reasons we have not previously prognosed. These cases are not rigorously examined post-mortem in the context of the business objectives, or play, or basin understanding. Frequently,as a result, a similar lead or prospect concept in the same play, sharing dependent risks, is drilled multiple times despite previous technical failures.This is not, of course, a universal truth, but more often than we would like,companies rush to move on, and the well becomes a mute data point on the basin's creaming curve.

 

In our two recent virtual round-table meetings, we examined:

1-"The Use and Usefulness of creaming curves, field size distributions and base rates in petroleum exploration," where we discussed the analysis of publicly-available basin discovery statistics to gain insights into how they may be used to predict the potential success statistics for a portfolio of wells or analyze exploration portfolios on a play-by-play basis.

2-"The absence of evidence is not necessarily evidence for absence – exploration beyond first-order basin statistics" where we reviewed the possible usefulness of creaming curve as a predictive tool in petroleum exploration and how a company may make a basin entry decision based on an essentially "flat" creaming curve(i.e., one dominated by failed wells).

 

We share some of our takeaways from these conversations in these"follow-up" notes to invite further discussion and to broaden the feedback on the topics we have selected and keep you (our audience) engaged in the follow-up discussions. 

Our presentations are limited to small registration numbers to ensure candid conversations and have sparked very lively discussions among the participants that have highlighted some common views among the participants and some inconsistencies in the way basin history analysis is performed.

One clear consensus is that before diving into the topic of lumping or splitting the data for statistical analysis, the care should be taken to ensure the clear geologic definitions of the basin and plays, whether the wells have tested particular plays or were declared dry for commercial or technical reasons.

As an example, in our conversations we found at least four different definitions of "the play" used to identify the drilled wells as a play test: 

  • the age of the reservoir; 
  • reservoir/seal pairs; 
  • source/reservoir pair; 
  • reservoir/trap style pair.  

Unless there is an agreed definition (or sufficient information for the analysts to make their own conclusions), any findings of the evaluation of the plays in thebasin will be incorrect, and digging out under-exploited or bypassed plays rendered challenging.

 

It is overall our view that creaming curve analysis is most valuable when it discriminates between the plays and play tests, when it may indeed identify missed opportunities or even new plays when combined with as thorough an understanding of the history of the basin as possible. "Lumping" the statistics together appears not to serve this purpose, at least in predictive mode, when trying to build a new portfolio and incorporate the potential value of speculative or conceptual plays.

 

All participants agree that for predicting the YTF volumes and future successful plays in the basin, one needs to learn how to gain insights from essentially flat creaming curves and intelligently leverage regional knowledge from plate tectonic to individual play-scale.

 

We continue sharing our experiences in the industry in these private virtual meetings and hope to see you at our next discussion.

Planned topics for the virtual round table events
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