Oil & Gas
AI that finds more barrels and keeps your operations compliant
You get reservoir modelling agents, drilling optimisation, predictive maintenance for rotating equipment, HSE compliance workflows, production forecasting, and emissions monitoring — all running on your cloud with full audit trails.
Built on your AWS, Azure or GCP tenant. HSE-compliant. Regulator-ready.
Proof of concept
To measurable ROI
AWS, Azure or GCP
In oil and gas, unactioned data costs barrels, lives, and operating licences
A single compressor failure on an offshore platform costs $3–5 million in lost production before the maintenance vessel arrives. HSE incidents trigger investigations that consume management time for months. Emissions exceedances now attract regulatory penalties that scale with severity and duration.
Your SCADA systems, well sensors, and reservoir models already contain the signals that predict these events. We build AI agents that connect those systems, predict equipment failures weeks ahead, optimise drilling and production parameters, and generate the HSE and emissions documentation your regulators demand.
reduction in non-productive drilling time through AI-driven optimisation — McKinsey Oil & Gas Practice 2023
average cost of a single unplanned offshore compressor failure including deferred production — BCG Energy Operations
improvement in reservoir prediction accuracy using ML-enhanced seismic interpretation — BP Technology
methane emissions reduction achievable through AI-driven continuous monitoring — McKinsey Sustainability Practice
From wellhead sensor to compliance record — in one workflow
We connect your SCADA, well monitoring, reservoir modelling, and HSE systems to AI agents that predict equipment failures, optimise production, monitor emissions, and generate the documentation your HSE and regulatory teams require — all on your cloud
SCADA, reservoir models, well sensors, HSE systems
- Approval gates
- Human-in-loop
- Audit logging
AWS, Azure or GCP
- Production forecasts
- HSE reports
- Emissions records
What we deliver for oil and gas operators
Agents built for high-consequence, compliance-critical energy operations
Reservoir modelling and production forecasting
Enhance reservoir simulations and forecast decline curves in real time.
ROI
Process
Ingest subsurface data
Seismic volumes, well logs, production histories, and pressure data from across the field
Enhance reservoir models
ML identifies geological patterns, improves facies classification, and refines flow simulations
Forecast production
Updated decline curves and recovery estimates with uncertainty quantification for reserves reporting
Sources
Originally published: BP — Technology & Innovation; Saudi Aramco Technology Development — reproduced for illustrative purposes
Predictive maintenance for rotating equipment
Predict equipment failures 3-6 weeks ahead from sensor data.
ROI
Process
Ingest equipment telemetry
Vibration, temperature, pressure, and performance data from compressors, pumps, turbines, and generators
Predict failure windows
ML models forecast component degradation 3–6 weeks ahead with asset-specific confidence scoring
Schedule maintenance
Prioritised work orders aligned to production turnaround schedules with risk-based justification
Sources
Originally published: Shell — Digitalisation & AI Programme; Azure Case Study — Saudi Aramco — reproduced for illustrative purposes
Drilling optimisation
Optimise rate of penetration and prevent wellbore events.
ROI
Process
Collect drilling data
Surface and downhole sensors, mud logging, offset well histories, and geological prognosis data
Optimise parameters
AI recommends weight-on-bit, RPM, and mud weight adjustments to maximise ROP and minimise risk
Prevent wellbore events
Real-time detection of stuck pipe, kicks, and lost circulation indicators before they escalate
Sources
Originally published: Shell Drilling AI Programme; Saudi Aramco — IKTVA Drilling Technology — reproduced for illustrative purposes
HSE compliance and incident management
Track compliance, analyse near-misses, generate HSE reports.
ROI
Process
Monitor HSE data
Incident reports, near-miss logs, permit-to-work records, inspection results, and safety observations
Identify risk patterns
AI analyses near-miss trends, correlates with operational conditions, and predicts elevated risk periods
Generate compliance records
Automated HSE reports structured for regulator submission, insurer requirements, and board reporting
Sources
Originally published: BP — Safety & Operational Risk; TotalEnergies HSE Programme — reproduced for illustrative purposes
Emissions monitoring and methane detection
Detect methane leaks and automate emissions regulatory reporting.
ROI
Process
Monitor emissions data
CEMS, satellite methane detection, flare efficiency sensors, and fugitive emissions surveys
Detect and quantify leaks
AI identifies methane sources, quantifies emission rates, and prioritises repairs by environmental impact
Generate regulatory reports
Automated emissions reports structured for EPA, EU ETS, and national regulator submission
Sources
Originally published: TotalEnergies — Methane Emissions Reduction; Shell Methane Monitoring Programme — reproduced for illustrative purposes
Production optimisation
Optimise production allocation and artificial lift in real time.
ROI
Process
Collect production data
Well rates, pressures, water cut, gas-oil ratios, facility capacities, and pipeline constraints
Optimise allocation
AI recommends production rates per well to maximise field output within facility and regulatory constraints
Adjust in real time
Continuous parameter adjustments for artificial lift, choke settings, and chemical injection rates
Sources
Originally published: Saudi Aramco Production Optimisation; Shell — Smart Fields Programme — reproduced for illustrative purposes
Audit and regulatory documentation
Traceable decision records for petroleum regulator inquiries.
ROI
Process
Capture decision data
Every AI-assisted operational and safety decision logged with data inputs and model outputs
Structure for audit
Records organised by well, facility, regulation, and time period for rapid retrieval
Enable rapid response
Compliance team can answer petroleum regulator inquiries in hours with complete traceability
Sources
Originally published: BP — Governance & Compliance; Shell Regulatory Documentation Programme — reproduced for illustrative purposes
CEO, Shell
Wael Sawan
"Shell has deployed AI across our upstream and downstream operations. Predictive maintenance on our rotating equipment fleet has reduced unplanned downtime by 20 percent. Our AI-driven drilling optimisation programme has cut non-productive time by 25 percent across wells in the Permian Basin. These are production gains measured in barrels, not pilot metrics"
Originally published: Shell — Digitalisation & AI Programme — reproduced for illustrative purposes
How we work in oil and gas environments
We do not deploy AI into oil and gas operations without first understanding what a failure means — in production terms, in HSE terms, and in regulatory terms. We map your use case to your petroleum licence conditions and environmental obligations before we write code.
Every agent runs on your cloud tenant. Your well data, your reservoir models, your production records — none of it leaves your environment. Your safety officers, your petroleum regulators, and your environmental agencies can inspect the system directly.
01
Operational risk mapping
We identify your use case, assess its HSE, environmental, and regulatory implications, and define the governance framework before any build begins.
02
30-day proof of concept
A working AI agent on your cloud, connected to your SCADA and well monitoring systems, with demonstrable output in 30 days.
03
Governance by design
Human-in-the-loop controls, audit trails, and explainable outputs — built so your safety case and environmental regulators can sign off.
04
Scale in 12–18 weeks
From one validated workflow to measurable operational ROI — with documentation your compliance team can present to petroleum authorities.
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Frequently Asked Questions
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