Petrosys and Interica have recently co-authored a technical article for First Break – the EAGE online magazine’s December Data Management issue. The article entitled ‘Total Recall: Obtaining value on demand from unstructured and structured data’ utilizes the extensive experience of both companies in dealing with the challenges that face data managers when it comes to categorizing and classifying millions of files and interpretation projects.
Below is an extract describing the challenges faced by E&P companies and data managers. The full article can be read here in the First Break – EAGE online magazine
An extract from: ‘Total Recall: Obtaining value on demand from unstructured and structured data’
Authors: Paul Gibb, Jonathan Patrick Smith, Brad Rymer, and Kevin Ward
Assessing the challenge
The challenge itself is two-fold:
- It comprises unstructured data, such as: well reports, seismic data acquisition and processing documentation, in-house or external evaluations and analysis, commercial reports, presentations, and more.
- It also comprises structured data, such as: project data associated with interpretation packages from many different vendors. This includes the live projects but also the many back-up copies, off-line copies [stored on external drives], and archive projects on both PC and Linux systems.
In many companies the unstructured and structured data can present a sizeable challenge; exploration and development teams can hold many tens of millions of files in various formats, across many different folders, where ownership and access is complex, and, for a significant proportion of the data, the creator – the owner of the data – may have long since left the company; so there’s no one to ask about the relevance, quality or value of the information.
Linking the unstructured data to structured data
There is considerable value in analysing, cataloguing, and classifying the unstructured data or structured data on their own, however, there is further value to be gained for companies when linking structured data with the unstructured data.
The assimilation of both data records into a single system for analysis supports greater effectiveness, in terms of the data manager being able to manage the company’s entire corporate knowledge, and for the end users who can now – using a single interface – assess what information is available, its quality, where it might reside, and who has determined it is suitable and thus whether it could support any future work being planned.
The assimilation of both the unstructured and structured data in a master data management solution.
