Acquisition Diligence
Ownership verification, chain of title, runsheets, lease and burden analysis, curative identification, division order review. The conventional work, done conventionally well — but supported by document extraction pipelines that make full-set review realistic instead of aspirational.
The practical difference: when a diligence set runs to eight hundred instruments, most shops will price a sample. I'll price the whole thing, because I'm not reading them one at a time by hand.
Typical deliverables: structured runsheet workbook · ownership and burden summary · red-flag memo with recommended curative · source citation to every instrument.
Three kinds of work, though most engagements borrow from all three. Every project is scoped under a written SOW with a defined deliverable.
Data & Systems
Getting your data to talk to itself. Regulatory feeds from the Texas Railroad Commission, New Mexico OCD, and BLM; Enverus and other subscription data; county clerk records; your own historical files, spreadsheets, and shapefiles — pulled into one place, cleaned, spatially joined, and made queryable.
That work usually ends in something you can actually use: a screening model, a Power BI report your whole team reads, an extraction pipeline that turns scanned records into structured rows.
Typical deliverables: working application or report, deployed for your team · documented data connections · handoff so your people can run it without me.
On ownership: what I build for you is yours. My reusable methods stay mine. That's spelled out plainly in the MSA before we start.
Feasibility & Opportunity Studies
Before you raise a fund or commit to an AMI, the question is usually simple and unglamorous: is there anything here? Open interest sweeps, unleased and expired-lease analysis, ownership fragmentation, operator development trajectory, and — where it's relevant — non-hydrocarbon mineral potential that a conventional oil and gas screen would miss entirely.
A well-supported "no" is worth as much as a "yes." It's cheaper than finding out after the capital call.
Typical deliverables: written findings with methodology and confidence caveats · supporting dataset · go/no-go recommendation with the assumptions exposed.