Automating Document Processing for a Century of Records in Oil & Gas
Indexing and Intelligent Data Extraction
Solution
The project had an implementation deadline of 1 week to achieve the following:
- scan and index 4,000 boxes of 7 million pages spanning 100 years
- extract up to 5 critical fields from each document
An oil and gas company undergoing a major acquisition needed to scan and index nearly 4,000 boxes of records that spanned over 100 years. Manual separation and indexing would have required approximately 20 man-years of work. The variety of documents—82 distinct types—and the diversity of formats within each type due to the long document retention period made automated solutions challenging. Other automation systems couldn't separate documents without target sheets, leading to delays and inefficiencies in processing.
Aluma designed and deployed an automated scanning and indexing system that could process the backfile of 7 million pages without using target sheets for document separation.
This innovative approach leveraged advanced machine learning and artificial intelligence to automatically detect and separate different document types. The system was configured to automatically identify and extract 4-5 critical fields from each document with a high degree of precision, achieving 90% accuracy. This not only reduced the requirement for manual labor but also sped up the scanning, separation, and indexing process, delivering a cost-effective and efficient solution to the client.
The flexibility of this automated system made it adaptable to future projects with similar requirements, showcasing its potential for widespread adoption in the industry.This solution drastically reduced the required manual labor and enabled efficient scanning, separating, and indexing of the documents.
Impact
Significant Labor and Time Savings
The automated solution replaced what would have taken 20 man-years of manual labor with a streamlined process. This efficiency allowed the project to be completed within the acquisition's tight timeline, supporting the company's broader business objectives.
High Accuracy in Document Separation and Indexing
The automated system achieved 90% accuracy in separating different document types without using target sheets. This high level of precision ensured that the records were properly organized, enabling easy access and retrieval of specific documents.
Cost-Effective Solution
The cost savings made the project economically viable and allowed the company to allocate resources to other important areas, such as integration and operational improvements after the acquisition.
