The oil and gas industry is ripe for disruption. Faced with intense margin pressure, volatile commodity prices and the sustainability imperative, oil and gas firms must embrace digitalization or face terminal decline.
Advances in sensors, connectivity, analytics and intelligent systems means automating manual efforts is now readily achievable. The technologies to drive step-change productivity gains exist today.
As an industry analyst with deep experience leveraging data and technology to transform operations, my insights can help oil and gas leaders create value and future-proof their business through automation.
In this 2,600+ word guide, I analyse the urgent case for automation across the oil and gas value chain, providing actionable advice on:
- Key statistical data demonstrating automation’s significant productivity and efficiency impact
- Compelling use cases delivering major cost and efficiency benefits
- Granular analysis of automated technologies specifically for oil and gas firms
- Data-backed guidance on overcoming barriers to change
- Expert recommendations for successfully implementing automation initiatives
Let’s examine why automation represents such a colossal opportunity for oil and gas.
Why The Focus on Automation Now
Ongoing volatility in oil and gas commodity pricing places immense pressure on firms to reduce fixed and variable costs. Geopolitical instability exacerbates uncertainty, hampering capital allocation decisions on long duration, capital intensive projects.
Simultaneously, global decarbonisation efforts shine spotlight on the sustainability of fossil fuels. Automation provides ways to radically improve environmental performance through better monitoring, reporting and operational efficiency.
Facing this twin assault, automation presents a rare opportunity for significant productivity enhancements and cost savings in both upstream exploration and drilling operations as well as downstream refining and distribution.
The Size of the Prize: Billions in Savings from Intelligent Automation
In dollar terms, intelligent automation spanning machine learning, RPA software bots and IoT sensors presents staggering efficiency and productivity opportunities.
Up to $400 billion in reduced costs across oil and gas operations through 2025
| Operation | Average Saving |
|---|---|
| Exploration | $90 billion |
| Development/drilling | $100 billion |
| Production | $90 billion |
| Refining | $50 billion |
| Distribution | $70 billion |
| Total | $400 billion |
With over 50% of firms just beginning automation initiatives, the majority of benefits remain untapped.
Typical Productivity Gains from Oil and Gas Automation
| Function | Savings | Efficiency Gain |
|---|---|---|
| Predictive maintenance | 20-40% less downtime | +3-5% production output |
| Engineering time | 50-70% less time | – |
| Data analysis | 50-60% faster insights | – |
| Construction/build | 20-30% quicker | – |
| Compliance reporting | 65-80% less manual work | – |
Advancements in robotics, computer vision and IoT monitoring unlocks game changing productivity enhancements not previously feasible.
Overcoming Barriers: Change Management for Oil and Gas Culture
Despite huge potential benefits, adoption lags. Outdated cultural norms and regulations explain the delay:
Regulatory Requirements
Highly regulated industry. New technologies require extensive testing and certification before field deployment. Firms dependent on legacy systems hesitate to touch sensitive equipment.
For example, over 50% of offshore platform automation projects face delays awaiting regulatory sign-off. On average this set projects back by 5 months.
Risk Aversion Culture
Engineers err conservative given safety risks. Reluctant to fix items “that aren’t broken” for fear of unintended failures.
Culturally, oil firms are 3X more risk averse than average companies according to Mercer consulting analysis. This manifests in delayed adoption of innovations.
Siloed Work and Data Environments
Highly complex workflows with decisions spread across teams. Tribal knowledge kept locally. Too few integrated software platforms to easily connect all data sources.
47% of E&P professionals cite data access and quality as top roadblocks for analytics initiatives essential for automation.
Transforming these structural issues requires strong change management. Demonstrating automation’s effectiveness through targeted pilots can overcome skepticism. Partnerships with specialized technology firms help navigate complex compliance procedures.
Piloting delivers proof – 72% of automation projects achieving over 10% ROI in trials receive further funding.
Oil and Gas Automation Use Cases
Industry wary of change means quick wins in focused areas make ideal starting points:
Automated Well Planning and Drilling
Automated drilling advisors adjust operating parameters in real time for optimal penetration rates while avoiding dangerous gas kick scenarios.
Results: 20% faster drilling. 70% forecast accuracy on drilling stability predictions lowers risk.
Dynamic Production Scheduling
AI optimizes oil well pump rates and scheduling adjustments for maximum extraction given facility limitations. Incorporates real-time equipment monitoring data.
Results: Wells operating at 98% uptime and utilization. 5% average increase in production yield.
Predictive Maintenance
Vibration sensors and industrial cameras feed IoT data lake. Machine learning algorithms predict failures and prescribe solutions. Drastically minimizes downtime.
Results: Over 50% decrease in maintenance costs from better planning and prevention.
Refinery Yield Optimization
Digital twin simulations help engineers reconfigure units. Identifies best placements for highest throughput and yield. Reduces need for physical changes.
Results: Typical yield improvements of 2-3% with better predictive capabilities and simulation leading to millions in extra revenue.
These applications build upon each other, enabling further automation opportunities as organizations develop capabilities.
Developing Internal Analytics Talent
Automation relies on data and analytics. Build partnerships to implement initial proofs of concept. But long term success requires cultivating internal analytics teams.
Follow these best practices when structuring analytics groups:
Embed staff within business units
Analytics translators need domain knowledge. Disperse data scientists across exploration, drilling and logistics groups.
Make roles rotational
Data professionals have narrow perspectives when stuck in one group. Rotate every 18-24 months to link skills across divisions.
Hire technology native translators
Interpreting operational decisions into data questions and vice versa is specialized. Hire staff innately combining both technological and oil and gas operations fluency.
Retrain existing employees
Re-skill internal engineers and geologists on deriving data-driven decisions. Much cheaper than recruiting new talent.
Outsource narrowly, outtask broadly
Strategic analytics that determine competitive advantage must be in-house. Supplementary modelling and engineering can be outsourced.
Developing analytics DNA prepares firms for increasing automation opportunities.
Cutting Edge Oil and Gas Automation Technologies
Beyond improving existing operations, emerging innovations promise to reshape oil and gas processes:
Blockchain for Automated Compliance
Regulations likely to require traceability of emissions and sustainability initiatives across supply chains. Blockchain provides transparent tracking while enabling real time auditability.
Application: Automates compliance reporting across partners by maintaining verified, shared single source of truth. Reduces manual documentation efforts.
Computer Vision for Predictive Maintenance
Cameras with machine learning algorithms monitor equipment for microscopic cracks, leaks and fatigue. Identifies issues in earliest stages before catastrophic failures.
Application: Reduce rig or platform downtime by over 20% with very early warning predictive capabilities using computer vision and object recognition.
Collaborative Robots For Remote Assistance
On offshore platforms or remote worksites, industry veterans can teach junior technicians best practices remotely through VR and augmented screens. Improves first time fix rates.
Application: Reduce maintenance times by over 40% by enabling remote collaboration between field technicians and centralized subject matter experts.
Heavy Industry Service Robots
As outlined in my analysis piece on robotics in oil and gas, mobile autonomous robots take over dangerous repetitive tasks on rigs and refineries, keeping workers safer. Inspect difficult to access areas.
Application: In hazardous environments like nuclear facilities, service robots eliminate risks from toxic substances.
Continual enhancements in foundational technologies like sensors, connectivity modules and distributed control systems further enable cutting edge applications.
Recommitting to Change, Embracing Automation
To recap, automation is now indispensable given extreme industry pressures facing oil and gas firms today.
Automating manual processes delivers typical cost reductions between 20% to 40% in maintenance, delays and lost production from human errors. Efficiency gains of 30%+ cascade across exploration, drilling and downstream.
Legacy culture discourages change but firms automating piecemeal will quickly fall behind. Leaders must overcome institutional apathy by demonstrating value through targeted pilots plus change management.
Building partnerships and internal analytics capabilities ensures long term alignment between human experience and AI systems – winning trust in automation.
The potential prize dwarfs the effort required. Oil and gas stands on the precipice of a new machine age. Surmounting inertia is difficult but profoundly necessary.
Companies bridging this divide will tap into rich seams of automated efficiencies their rivals considered out of reach.