Speeding Up Oil & Gas Acquisitions
Procedures with AI-Based Data Management Solutions

Our Client

Odyssey Analytics client is a large-cap independent oil & gas producer headquartered in Houston, Texas. Our client has operations across one of the USA’s key oil fields in the southeastern region and is an important driver for the region’s domestic production growth.

Challenge

After acquiring multiple oil & gas companies in the region over the span of 10 years, our client faced documentation management issues that were previously dependent on paper-based operations that required time, manpower, and resources. Similar to most oil and gas producers of the industry, our client’s accounting and land acquisition department was dealing with multiple challenges while managing land record data and legal documents essential for leasing and acquisition procedures. Due to massive drilling and production activities in the region, the leasing and acquisition procedures have become more complex than before. And our client was dealing with a data recording and management system while using the old paper-based approach after making several acquisitions leaving a backlog of 400,000+ lease document pages.

Solution

Our client was working with a third-party document scanning consultant for turning paper-based data into digital information but the key issue was the document was not classified as per the corporate data standards that leaves the leasing analysts with no other choice than adding metadata such as the title opinions, assignments, deeds, memorandums and more, manually. And doing this all manually makes the whole process time & resource intensive which delays the procedure’s completion. Odyssey Analytics worked closely with the client’s team for building a document taxonomy and lease model during the data extraction phase. We helped our client in devising an automated document processing technology that uses our client’s specific document taxonomy and quickly classifies each document as per the client’s asset structure. Not only this, our solution helped the client intelligently extract key metadata, such as payee information, company name, and interest decimals.

Result

Our client reported that it takes about one day to process around 16 documents with the old method. And after applying our solution, they saw a huge difference in lease documentations procedure completion with 200+ documents a day on average. This not only helped our client add efficiency and acceleration in their documentation digitalization but also saved them 90% time in comparison to the old method. Our client’s accounting team was able to rapidly onboard division orders and other data required to process monthly revenue. And their land department was able to rapidly analyze lease information, provisions, and ownership. After looking at the success of this solution, the client is now expanding the application of our solution to other areas of the company which are document intensive such as legal documentation and contract management.

Technology Used

  • Kinesis
  • Lambda Functions
  • S3
  • MOngoDB