Use AI/ML data-physics study recommendations to optimize water-injection rates: pilot in Heera, implement recommendations in South Heera and later in North and Mid Heera wells, adjusting rates for field performance and regularly monitoring production-injection performance.
Company
ONGC
Department
Reservoir engineering & field development
Record type
company_adoption
Disclosed stage
Scaled. ONGC’s 2025 annual report says AI/ML-plus-physics water-injection recommendations started implementation at South Heera in March 2023 and were subsequently implemented in North and Mid Heera wells; the 2025 filing says field-performance monitoring continues. Multi-area implementation supports scaled within Heera, not whole-company scale.
Source date
2025-08-07
Source-date precision
day
Source provenance
A · Operator filing
Review disposition
Source-attributed; not an independent validation
Reported result
No quantified production gain, recovery uplift, injection reduction, accuracy, cost saving, or ROI disclosed.
What this does not establish
Implementation is described, but no quantified result or validation is reported. The pilot and dated South Heera start precede the window; only the August 2025 report disclosure is in-window. The source does not state well count, input data, decision rights, or model design.
Distinct operator deployment in India, separate from ONGC's AI gas-lift tender and SLB's Tachyus/Aqueon product acquisition.
Annexures to the Board's Report, printed p. 131, item 30; PDF p. 157
Disclosure history
AI/ML data-physics water-injection optimization across Heera assets
Use AI/ML data-physics study recommendations to optimize water-injection rates: pilot in Heera, implement recommendations in South Heera and later in North and Mid Heera wells, adjusting rates for field performance and regularly monitoring production-injection performance.
A source grade describes provenance, not independent verification. This is a research profile, not a measure of net return. Report a correction.