SE Radio 631: Abhay Paroha on Cloud Migration for Oil and Gas Operations

Temporal Data

Managing temporal data is crucial in oil and gas operations, where time-bound data like pressure and temperature readings are essential for accurate recommendations. Abhay Paroha explains the use of Datomic, a database that supports bi-temporality, capturing both valid and transaction times to store static data effectively 1. This allows asset managers to retrieve historical data accurately, such as production reports from specific dates.

Datomic is one of the databases which by default its storage engine supports the temporal feature.

--- Abhay Paroha

The use of Bigtable, a column family database, further aids in maintaining bi-temporal data by storing physical and version timestamps, enabling precise data retrieval for time series data 2.

   

Data Solutions

In cloud storage for oil and gas, different data types require specific solutions. Abhay Paroha categorizes data into structured and time series, using Datomic for immutable static data and Bigtable for scalable time series data 3. This approach ensures historical data is preserved, supporting workflows that demand data accuracy over time.

We never deleted any data point or updated anything. We are always creating immutable records of all data.

--- Abhay Paroha

Additionally, digital twins model physical equipment in the cloud, allowing for real-time monitoring and analysis of equipment behavior, which is vital for operations with extensive data volumes 4.