The oil and gas industry has a rich history and one that is deeply intertwined with regulation — with Federal and State rules that regulate everything from exploration to production and transportation to workplace safety. As a result, our latest customer had amassed millions of paper documents to ensure its ability to prove compliance. It also maintained files with vast amounts of geological data, that served as the backbone of its intellectual property.
With over seven million physical documents saved and filed in deep storage, this oil and gas industry leader called the AWS consulting services team at Flux7 for its help digitizing its vast document library. In the process, it also wanted to make it easy to archive documents moving forward, and ensure that its operators could easily search for and find data.
Read the full AWS Case Study here.
Working with AWS Consulting Partner Flux7, the company created a working plan to digitize and catalog its vast document library. AWS had recently announced at re:Invent a new tool, Amazon Textract, which although still in preview mode, was the ideal tool for the task.
What is Textract?
For those of you unfamiliar with Amazon Textract, it is a new service that uses machine learning to automatically extract text and data from scanned documents. Unlike Optical Character Recognition (OCR) solutions, it also identifies the contents of fields in forms and information stored in tables, which allows users to conduct full data analytics on documents once they are digitized.
The Textract Proof of Concept
The proof of concept included several dozen physical documents that were scanned and uploaded to S3. From here, Lambda functions were triggered which launched Textract. In addition to the data being presented to Kibana, URLs for specific documents are presented to users.
As Amazon Textract automatically detects the key elements in a document or data relationships in forms and tables, it is able to extract data within the context it was originally created. With a core set of key parameters, such as revision date, extracted by Textract, operators will be able to search by key business parameters.
Analytics and Compliance
Interfacing with the data via Kibana, end users can now create smart search indexes which allow them to quickly and easily find key business data. Moreover, operators can build automated approval workflows and better meet document archival rules for regulatory compliance. Moreover, no longer does the company need to send an employee in their car to retrieve files from the warehouse, saving time from a labor-intensive task.
At Flux7, we relish the ability to help organizations apply automation and free their employees from manual tasks, replacing it with time to focus on strategic, business-impacting work. Read more Energy industry AWS case studies for best practices in cloud-based DevOps automation for enterprise agility.
For five tips on how to apply DevOps in your Oil, Gas or Energy enterprise, check out this article our CEO, Dr. Suleman, recently wrote for Oilman magazine. (Note that a free subscription is required.) Or, download the full case study here today.
from Flux7 DevOps Blog