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AWS Solutions Library

Guidance for Refinery Monitoring & Surveillance on AWS

Overview

This Guidance helps downstream energy operators deploy a secure and modernized industrial data environment. It uses independent software vendor (ISV) partner products and AWS services to ingest plant sensor data, then route, store, and analyze the data for visualization and reporting. Data from disparate sources, such as refining and petrochemical industrial data, can be brought into a centralized repository in near real-time to help refineries with predictive equipment maintenance, process planning, and greenhouse gas (GHG) emissions management.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

Amazon SNS allows refineries to safely operate this Guidance and respond to incidents and events. This service notifies the operator with near real-time insights into technical and functional anomalies. It also notifies them of key milestones during the monitoring processes. 

Read the Operational Excellence whitepaper

To protect data in this Guidance, data at rest in Amazon S3, Aurora, and Timestream are encrypted using AWS Key Management Service (AWS KMS), and transferred over a secure network connection. We recommend using AWS CloudTrail to access and investigate logs. 

Read the Security whitepaper

Event-driven prompts in AWS IoT Core and Amazon S3 operate on both new and changed data simultaneously, allowing faultless retries for data ingestion, contextualization, and preparation for data science workloads. 

Read the Reliability whitepaper

AWS managed services such as Lambda, Amazon Textract, AWS Glue, and Athena provide built-in elasticity and monitoring of workloads, so that the services scale for optimal performance and align with the workload demand.  

Read the Performance Efficiency whitepaper

Serverless managed services are used in this Guidance, including Amazon S3, for general data savings on storage costs. Serverless technologies provide true consumption-based pricing that puts the customer in control. 

Read the Cost Optimization whitepaper

Amazon S3 provides multiple storage classes, including the Amazon S3 Intelligent-Tiering storage class, that automates storage cost savings by moving data when access patterns change, maximizing sustainability and minimizing resource usage.   

Read the Sustainability whitepaper

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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