Collaboration of Operators and Data Scientists Is Key
A major challenge has been to foster cooperation between two groups with such different skills and backgrounds, O&G operation and data science. Failure of many projects is due to failure of collaboration of these groups to understand one another to
Why Data Quality Matters
In a previous blog, we covered the importance of quality data across well cohorts. In this last blog of our series on data quality, we will address why data quality matters. For production, if an organization is consistently using allocated
Predictive Analysis Requires Quality Data Across a Well Cohort
A well cohort describes the group of wells that OspreyData uses to create a modeled solution for your oilfield. Quality source data among well cohorts are essential to predictive analysis. In an artificial intelligence project, it is important to understand
Consistency and Connectedness of Source Data Quality
The consistency and connectedness of source data are also important dimensions when evaluating source data. Consistency refers to the frequency of updates or new values in a time series data stream, while connectedness indicates the ability to trace a thread
Coverage and Continuity Equate to Source Data Quality
Coverage and continuity of source data are important dimensions when evaluating source data. Coverage describes the number of data sources that are available for a well. Many of the models that are used in advanced systems, such as OspreyData, are
Prediction Quality: The 4C’s of Source Data Evaluation
Prediction quality is not the same thing as data quality. Last week, we suggested that the concept of “more data is always better” must be tempered with a thoughtful assessment of how that source data provides additional information from your