I recently had the opportunity to visit a client who was also a former colleague and friend. During our meeting, we had a productive discussion about his new position and I was excited to demonstrate the i2G platform developed by our team. When it came to making a well correlation, we had to spend quite a while to find well tops. Here is the problem, which is even more serious: he was not sure if the well tops were the latest version. For those who are not a geologist: well tops keep changing when new data are acquired or our knowledge about the reservoir increases. If wrong well tops are used, we will have an inaccurate perception about reservoir architecture but let’s leave it there for now.
This issue highlights the ongoing challenges that geoscientists face in managing data effectively. Other data management challenges are:
- New data streams, exponential increases in data volumes
- Fragmented data ownership, data duplication and data redundancy
- Loose connection between working project and related flat files
- Difficult to queries data with folder structure organizing and naming
The way we can solve these challenges are to work with a data platform which support applications running on it. These applications are supported by a comprehensive data management system and a “base” module to provide data analysis and pre-processing tools.
The key components of a data platform normally include:
Data storage
Cloud storage solutions are becoming increasingly popular in the industry. Major IOCs are adopting cloud-based solutions across their operations, from surface to subsurface departments, to streamline their processes. With scalable data storage, it is possible to unify fragmented data in a centralized database with high security. Cloud-based solutions also offer benefits such as reduced maintenance and backup costs, as well as improved collaboration.
Applications
A key feature of a data platform is its ability to enable software to run on it, such as data processing and interpretation tools or intuitive dashboards. This enables organizations to manage databases, working projects, and related flat files within a unified working environment, reducing the time spent searching for data. Structured data can be loaded directly into the working project from the database while preserving the relationships between them, providing quick and easy access to supporting documents. Imagine that you are interpreting depositional facies using Gamm Ray curve and it’s just one click away to access the supported documents such as biostratigraphic study. How cool is that!
Metadata system
Metadata is basically “data that provides information about other data” [1]. In short, it’s data about data. A strong meta system and tagging capability are required for any comprehensive database to facilitate data management and data query. The system is designed to categorize and classify data through semi-automatic tagging processes. This allows for efficient search and retrieval of data based on specific criteria, such as data type or content.
In the upstream oil and gas industry, decision-making processes often entail high costs and significant risks. Having quick access to valuable data is essential for informed and confident decision-making. The Metadata System addresses this challenge by delivering a robust, secure, and user-friendly data management solution. The system is engineered to be configurable, manageable, and cost-effective, delivering a strong return on investment within a reasonable business time frame.
Reference
[1]”Merriam Webster”. Archived from the original on 27 February 2015. Retrieved 17 October 2019.
[2] https://en.wikipedia.org/wiki/Metadata
