Find the hidden cost in legacy land data.
Magnus Solutions helps oil and gas operators clean up legacy land, asset, and regulatory data before it becomes a cost, liability, transaction, closure, or compliance problem. Using GIS analysis, imagery review, record matching, disposition relationship checks, and internal data reconciliation, we identify unused dispositions, no-entry cancellation candidates, stale approvals, stranded infrastructure risks, missing evidence, and mismatches between field reality and regulatory records.
The result is a prioritized action plan: cancel, correct, verify, package, or escalate for regulatory review.
Identify. Verify. Package. Resolve.
No-Entry Candidate Screening
Identify dispositions or assets that appear unused, undeveloped, or potentially eligible for no-entry review.
Legacy Disposition Cleanup
Review old LOCs, MSLs, PLAs, PILs, MLLs, and related records for stale, duplicate, inactive, or mismatched entries.
GIS & Imagery Disturbance Review
Use aerial imagery, satellite imagery, GIS overlays, and disposition boundaries to assess whether field disturbance appears present or absent.
Associated Asset / Dead-End Analysis
Check whether cancelling or changing one disposition could strand access, pipeline, wellsite, or related infrastructure records.
Asset Transfer / Due Diligence Data Review
Assess land, regulatory, and asset data before acquisitions, divestitures, transfers, or portfolio rationalization.
Cleanup Action Planning
Turn messy records into a prioritized action list: cancel, correct, verify, package, monitor, or escalate for specialist review.
Relevant experience.
| Project | Relevance |
|---|---|
| Crown Disposition Utilization / No-Entry Analysis | The strongest fit — directly supports unused disposition screening, no-entry candidate identification, record mismatch review, and cost-recovery / liability cleanup. |
| Regulatory data & liability cleanup model | GIS analysis, imagery review, record matching, and prioritized action plans — the core narrative for this pillar. |
| SiteDocs ETL & Latitude connectivity | Proof we can clean, structure, reconcile, and operationalize messy source-system data — extracting field data into Azure PostgreSQL with stable API feeds. |
Presented as relevant experience. Detailed, client-approved case studies available on request.
Works best alongside
Send us a messy dataset.
Send Magnus a land, disposition, or asset dataset. We'll identify cleanup opportunities and turn it into a prioritized action plan.
No transformation program · No system replacement · One useful deliverable