The global oil and gas industry stands at a crossroads. Facing market volatility, increased competition, sustainability mandates, and an aging workforce nearing retirement, companies require fresh solutions to thrive. Intelligent automation has emerged as a transformative digital technology, merging cutting-edge AI with proven automation to help oil and gas businesses tackle these modern challenges.
This expert technology overview explores how intelligent automation is upgrading operations across the oil and gas value chain. Discover how innovative firms gain an edge by leveraging intelligent automation in 2024 and beyond.
Legacy Modernization Bridges Past and Future
Many oil and gas companies rely on legacy systems that complicate upgrading to advanced intelligent automation. Hard-coded workflows, proprietary code languages, and incompatible boards make integration tricky.
Platforms like Appian provide low-code intelligent automation with hundreds of prebuilt industry connectors. This makes it faster for energy companies to bridge across legacy systems. Seamless orchestration and monitoring aids change management.
According to Andrew Towne, CIO of industry leader Baker Hughes, intelligent automation serves as “a cornerstone of the digital transformation process” providing "stability and reliability” even while upgrading underlying systems.
Back-Office Tasks Made Easier with Intelligent Document Processing
Upstream, midstream and downstream oil and gas operations generate a flood of unstructured data from sources like seismic images, well logs, contracts, safety procedures, regulatory filings and more. Making sense of these document-centric processes manually bogs down critical back-office teams.
Intelligent document processing solutions combine optical character recognition (OCR), natural language processing (NLP) and machine learning. This gives systems the ability to ingest data from scanned documents and electronic files in any format. Automated classification, extraction and analysis of text and data speeds processes like:
- Accounts payable and invoicing – According to payables software leader Beanworks, around 2% of processed invoices typically contain errors, which intelligent automation catches consistently. Correct coding on all entries prevents costly problems downstream.
- HR onboarding and record management – IDP structured + unstructured personnel data critical for compliance, audits and decision making.
- Compliance reporting across regulations like DOT hazardous materials transport rules demanding meticulous vehicle safety documentation.
- Lease data administration – Unconventional wells require more intensive planning with 3x the paperwork. IDP assimilates details locked in these files.
- Permitting and licensing – ConocoPhillips applied intelligent document processing to clear extensive inactive well permit backlogs 8x faster, organizing 300,000 documents for reliable retrieval.
For example, ConocoPhillips turned to intelligent document processing to assist with a backlog of 300,000 inactive well permits. Automation helped archives staff classify and validate these permits up to 8 times faster. across all back-office documents.
Intelligent automation handles variable data in document-driven workflows seamlessly. This shrinks processing times from weeks to days or hours. Consistent 24/7 productivity liberates back-office teams to focus on high-value responsibilities.
Unplanned Downtime Slashed with Predictive Maintenance
Oil rigs, pipelines, refineries and associated infrastructure run non-stop under intense pressure in precarious environments. Unexpected equipment failures lead to expensive unplanned downtime along with safety and environmental risks.
Intelligent predictive maintenance utilizes IIoT sensors along with big data analytics, computer vision and machine learning algorithms. Continuous equipment monitoring provides early detection of looming failures from telltale signs like vibration or temperature changes – mostly invisible to humans.
Sophisticated deep learning algorithms group clusters of normal operating sensor data to precisely detect even subtle anomalies indicative of a growing problem. Together with computer vision checking for any unexpected visual irregularities, algorithms pinpoint potential failures extremely reliably weeks or months in advance.
Instead of reacting to unexpected breakdowns, issues get flagged weeks or months in advance. This wide window enables orderly planning of cost-efficient maintenance at optimal times to minimize operational impacts. Technicians also understand specifically which components need proactive care.
BP reports optimizing maintenance timing helped reduce unplanned downtime at one of its refineries by 97%. Intelligent automation enables major productivity improvements by predicting problems early and pinpointing where to direct limited maintenance resources.
Sheer Volume of Sensor Data Harnessed with Anomaly Detection
Modern oil fields and pipelines embed millions of IoT sensors to monitor every aspect of production. This firehose of streaming time-series data gets analyzed by machine learning algorithms specialized in grouping normal behavior versus exceptional anomalies that may indicate emerging production problems or safety issues.
Rapid automated anomaly detection outperforms limited human capacity to process high-velocity structured data. Response agility to subtle early alerts prevents small inconsistencies from cascading into major disruptive events.
For example, unusual vibrations picked up from subsea risers allowed Brazilian oil giant Petrobras to identify and resolve small pipeline gas leaks. This avoided catastrophic ruptures like the one that caused BP’s Deepwater Horizon tragedy. Advanced analytics makes oil and gas operations an order of magnitude safer by acting on the flood sensor measurements as an early warning system.
Inventory and Logistics Optimization with Demand Forecasting
Balancing the intricate supply chain logistics supporting massive drilling, pipeline and storage operations represents a monumental challenge. Intelligent automation crunches inputs ranging from production schedules and equipment maintenance to weather forecasts and geopolitical factors driving demand.
Sophisticated machine learning algorithms generate incredibly accurate demand predictions. This gives supply chain managers enhanced ability to optimize dynamically across the interconnected web of suppliers, storage, transport and distribution to exceed customer needs as economically as possible.
McKinsey research shows AI-enhanced demand planning can reduce inventory costs by 25-50% while improving service levels over manual methods prone to inherent human bias. Intelligent automation empowers just-in-time precision across oil and gas supply chains.
Regulatory Compliance Assurance with Continuous Monitoring
Few industries face stiffer governance than oil and gas. Ever-increasing local, state, federal and international rules enforced by EPA, OSHA, DOT and other agencies demand diligent tracking. Just one oversight could lead to shutdown production or millions in fines.
Intelligent automation continuously cross-checks operational sensor telemetry, unstructured filings and emerging regulations to pinpoint compliance anomalies in real-time. Natural language processing keeps dynamic regulatory documents in scope. Automated systems vastly surpass limited human capacity to synthesize regulatory complexity. This safeguards organizations against accidentally overlooking updated codes which may expose them to legal jeopardies or reputational harm.
Attorneys specialized in oil and gas emphasize that staying abreast of "ever-changing regulatory requirements" presents operators and contractors with a herculean burden. Intelligent automation optimally shoulders this load.
The Future Runs on Intelligent Automation
Legacy oil giants and agile upstarts alike turn to intelligent automation as the digital linchpin enabling modernization. Leading firms creatively merge blue-collar expertise with exponential technological change to claim market leadership today and into the emerging energy landscape. With the global oil and gas automation market exploding at a 75% CAGR to top $42B by 2030, no player can afford to be left behind.