Teamlead technology & solutions
Tools and solutions
What is the business value of your operations data if you do not unlock the learnings and
apply those learnings for future operations?
Operations data contains critically important information for decision-making and many learnings can be
retrieved from historic data. Risk mitigation and avoiding mistakes by learning from the past should be an
integral part of the day to day well delivery process. Still, we found that rigorous data analysis is often
sacrificed in order to meet dead-lines.
Oil & Gas
As mentioned before, data analysis has negative value, if you cannot trust your data. Data cleansing is an absolute
prerequisite for doing data analysis and it is an expensive mistake to sacrifice data cleansing for reasons of cost savings
or meeting dead-lines. Hence, cleansing first.
When your data is clean, it does not yet mean that you are able to extract learnings and risk mitigating actions from the
data. Causal relationships need to be understood and are often hidden, rather than explicitly labeled within your dataset.
Exploring the data on its causal relationships is extremely difficult and time-consuming. We therefore deploy a decision
model that extracts learnings from the past and present this intelligence to the well planner. As a direct results, learnings
can be integrated into the well plan in order to mitigate risk. The decision models form an integral part of our proprietary
framework that integrates commerce, engineering and cost management.
Since drilling engineering resources are scarce and
dead-lines need to be met, important planning activities
within the well delivery process may be sacrificed.
Nowadays, data is often stored in a structured and clean
format in databases. Historic data is often stored in an
unstructured way or even in hard copies. Yet, these historic
wells contain a wealth of information.
Working together with drilling engineers, managers and
drilling supervisors we developed and automated an
intelligent system that cleanses this historic data for you.
The result is both extreme valuable learnings to avoid and
risk mitigate your well. The business value is apparent.
How much do you trust your own historic data?
Sacrificing data cleansing for reasons of cost saving or
meeting dead-lines can have huge impact on your risk
Data analysis without data cleansing has no value if
you cannot trust your historic data.
Is it cumbersome and time consuming to cleanse
drilling data? A definite yes, but that is no reason not
to cleanse. Our intelligent cleansing systems ensure
that you get more value from data.
If you trust your historic data, what is the business value for you?