I was doing on-site support to a client who was actually my friend and colleague before. We had a nice chat about his new position and I was so excited to show him 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 is one of the problems related to data management that are facing by geoscientist every day. 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

The cloud storage is more popular than ever. Big IOCs are adapting cloud solution across their assets from surface to subsurface departments to streamline its operation. With a scalable data storage, we can now unify all fragmented data in a centralized database with high security. Cloud deploy means less efforts for database backup and maintenance which can occupy a considerable proportion of operation costs. Effective collaboration is also an important benefit when using cloud solution.

Applications

One key feature of a data platform that distinguishes it from a classical database is the ability to enable software running on it. These can be data processing and interpretation tools or basically intuitive dashboards. This can be viewed as an innovative solution which make it much easier for managing database, working project and their relations. Within one unified working environment, the relationship between working projects and the related flat files can be properly captured so that the time spent for data finding is significantly reduced. This hand-in-hand solution maximizes the actual time working on the data. The user is also able to load structured data directly to the working project from the database and still preserve the relations between them. 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. All data uploaded to the system will be tagged and classified manually using the available framework. It allows us to quickly search for needed data by data type or by contents.

 

In summary, the foundation for all decision making is data. In upstream oil and gas, many of the decisions that are made are naturally expensive and can be very risky. As a result, easy access to all of your organizations valuable data to support that decision making is a vital core business function. The key challenge is how to build a data management system that is robust, secure, and easy to configure, use and manage, whilst being at a price point that delivers a strong return on investment in a reasonable business time frame.


About the author

Anh Nguyen is a reservoir geoscientist who is passionate about every aspect of digital transformation. He has been spending most of his professional career so far to study applications of machine learning and AI in geoscience along with joining the development team to build a cloud-based data platform called i2G (https://www.i2g.cloud/). During his consulting work, he has successfully applied state-of-the-art technologies offered by i2G including effective collaboration, comprehensive data management, machine learning and AI. 

You can connect with him directly or reach him via email: anh.nguyen@esstar.com.vn

Reference

[1]”Merriam Webster”. Archived from the original on 27 February 2015. Retrieved 17 October 2019.

[2] https://en.wikipedia.org/wiki/Metadata

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