ospreydata predictive analysis 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 combining sensor based machine learning models with physics based models.
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 well.  This speaks to a position of not more data,
The impact of Artificial Intelligence on an organization is an important topic when considering machine learning.  In a previous blog entitled, What Artificial Intelligence in Oil and Gas Brings to Production, we discussed a summary of key solutions that AI can target for problems facing most oil and gas organizations
When we consider the good source data required to power machine learning,
we must consider the full life-cycle of the well. Most use-cases that OspreyData is building have moved beyond utilizing just a set of time-series sensor values. Well designs and completion reports provide insight to the physical aspects of the
Artificial Intelligence in Oil and Gas is becoming a very popular topic. MIT’s Sloan School of Management’s article, “Reshaping Business with Artificial Intelligence,” recently found that that 85% of corporate executives surveyed believe that AI will help their businesses gain or sustain competitive advantages. What might that look like for