Oseberg's New Mexico Unitization dataset,

a comprehensive and differentiated solution that sets us apart from our competitors. 

• State and Federal Unitizations (Bi-Monthly): Our dataset includes both State and Federal Unitizations, allowing you to gain a holistic view of the entire producing reservoir or prospectively productive area. This integration streamlines operations, reduces costs, and maximizes production efficiency by eliminating the need for separate tank batteries and unnecessary offset wells.
• BLM Unitizations: We source Federal Unitization data from the BLM LR2000, providing you with detailed records that flow seamlessly into your workflow. The dataset's natural ID structure ensures easy integration with Federal Leases. Additionally, our commitment to data accuracy involves trimming superfluous trailing spaces and dropping unnecessary characters from the remarks and action tables, ensuring clean and reliable information.
  • Committed, Partially Committed, Uncommitted Tracts: Our dataset classifies tracts based on commitment levels, guiding you in making strategic decisions. It creates a "lease" or extends expiration dates for all state or fee leases to the life of the unit, reducing administrative burdens and minimizing the risk of oversight. The timeline of 6-12 months from submission to approval ensures timely decision-making, preventing delays that could impact your bottom line.
  • Parties and Interests: Gain insights into the involved parties and interests, allowing you to identify potential collaboration opportunities and negotiate more effectively. Our dataset empowers you to make informed decisions by providing detailed information on committed, partially committed, and uncommitted interests.
  • Exhibits with Decimal Precision: Our dataset's exhibits offer a granular view with precise decimal values for every interest type. This level of detail enables you to analyze opportunities with unparalleled accuracy, maximizing your potential for profit and minimizing the likelihood of oversight.