A concrete example of local control with cloud learning. Ask how the baseline accounts for unloading cycles and decline, what safety permissions apply, and whether gains persist through a full operating year.
Company
Expand Energy
Department
Production & field operations
Record type
company_adoption
Disclosed stage
Operating field test on nine wells across eight pads; 63–83-day results
Source date
2026-07-01
Source-date precision
day
Source provenance
C · Supplier-reported
Review disposition
Source-attributed; not an independent validation
Reported result
SLB’s JPT account reports 70–139% cumulative gas-production gains over 63–83 days on nine wells across eight pads, with daily gains up to 350 Mscf/d. More than 80 MMscf additional gas per well-year is an estimate, not a year of observed production.
What this does not establish
Short field-test results do not establish a year-long or fleet-wide outcome. More than 80 MMscf per well-year is explicitly estimated. The conference abstract and SLB-authored JPT account describe the same deployment. The reviewed primary passages do not disclose full hardware, software, integration or ongoing support costs or net ROI. Annual financial figures from an author-uploaded manuscript are held pending publisher-source access. The conference source is dated 2026; its exact publication day is not established.
A concrete example of local control with cloud learning. Ask how the baseline accounts for unloading cycles and decline, what safety permissions apply, and whether gains persist through a full operating year.
Autonomous liquid unloading on nine Haynesville gas wells
An edge IIoT gateway uses surface pressure, temperature and flow data with physics-based critical-velocity logic. It decides shut-in timing and actuates the choke locally. Cloud machine learning predicts shut-in duration; local control does not require continuous cloud connectivity or operator oversight.
Short field-test results do not establish a year-long or fleet-wide outcome. More than 80 MMscf per well-year is explicitly estimated. The conference abstract and SLB-authored JPT account describe the same deployment. The reviewed primary passages do not disclose full hardware, software, integration or ongoing support costs or net ROI. Annual financial figures from an author-uploaded manuscript are held pending publisher-source access. The conference source is dated 2026; its exact publication day is not established.
A source grade describes provenance, not independent verification. This is a research profile, not a measure of net return. Report a correction.