The Covid-19 pandemic has intensified the pre-existing imbalance between demand and supply in the oil and gas (O&G) sector. This disruption has resulted in financial instability, forcing companies to cut costs, including reductions in workforce and salaries.
Another threat is the competition from the renewable energy industry, which is projected to be valued at $1.1 trillion by 2027. The oil and gas sector must leverage digital transformation to overcome these disruptions and remain competitive.
See the top six digital technologies and how they are transforming the oil and gas industry.
1. Traditional AI & data science in O&G
- Advanced analytics: Big data and AI (Artificial Intelligence) can enable powerful analytics platforms to provide insights for improved operational and managerial efficiency to reduce disruptions across the oil and gas supply chain. Advanced analytics combined with cloud software can provide significant infrastructure cost savings.
- Seismic data: During location search for oil drilling, advanced analytics can analyze seismic data to provide risk insights, increasing the success rate and saving time and money. Seismic data analytics can also be combined with historical data to identify reservoir oil levels.
- Predictive maintenance: Big data gathered from expensive machines working on offshore drilling platforms can be used to predict asset maintenance and reduce failures.
2. GenAI & LLMs in O&G
The implications of generative AI and large language models in the oil and gas sector are:
Cost Reduction:
GenAI and LLMs streamline operations by automating data analysis and decision-making processes. For example, these technologies can reduce exploration, maintenance, and legal compliance costs by 20–50% by faster identifying drilling opportunities, predictive maintenance to avoid downtime, and automated regulatory reporting. 1
Enhanced Safety:
By leveraging predictive analytics and virtual reality training, AI systems can foresee potential hazards and simulate emergency scenarios. This proactive approach minimizes workplace accidents by thoroughly practicing safety protocols and addressing potential issues before they escalate.
Sustainability Improvements:
AI optimizes energy consumption and reduces emissions by enhancing operational efficiencies. Smarter logistics, energy management, and precise reservoir modeling mean that resources are used more sustainably, directly contributing to a lower environmental footprint.
Case Studies:
- Schlumberger’s AI Legal Assistant:
Schlumberger uses an LLM-based contract analysis tool to review 10,000+ pages of drilling contracts annually, cutting processing time by 50% and reducing legal costs by $12M/year. 2 - Shell’s AI-Driven Exploration:
Shell analyzes subsurface data using GenAI-powered seismic interpretation. Their AI model predicts optimal well locations, reducing exploration time by 40% and improving drilling success rates by 25%. 3 - BP’s AI-Powered Predictive Maintenance:
BP deployed LLM-based predictive analytics on offshore rigs. The system reduced unplanned downtime by 30% and saved $50M annually by forecasting pump failures 2 weeks in advance. 4
3. Industrial IoT in O&G
- Monitoring pipelines: Leaks and oil and gas extraction damages can cause significant financial and environmental damage. IoT (Internet of Things) can efficiently monitor the system’s pipes, pumps, and filters with real-time data to avoid these leaks. This reduces unnecessary manual system checks, and workers are only deployed when anomalies are detected.
- Asset Monitoring: IoT-enabled sensors can provide remote access to usage and maintenance data of heavy offshore drilling machines in remote areas with extreme conditions.
- IoT in oil refineries: IoT-enabled sensors can also provide real-time data to control performance parameters. Real-time data is available around the clock to achieve accurate measurements.
- Oil and Gas Logistics: Some areas are inaccessible since oil and gas-containing ships are big. LPWANs (low-power wide-area networks) provide monitoring capability to the workers on the ship with real-time data for maintenance.
Case Studies:
- BP’s IoT-Enabled Pipeline Sensors:
BP installed IoT sensors across Alaskan pipelines, reducing manual inspection time by 50% and preventing potential environmental cleanup costs by $10M/year. 5 - Saudi Aramco’s Smart Fields:
IoT networks in Saudi oil fields optimized extraction by analyzing real-time pressure and temperature data, boosting recovery rates by 12%. 6 - Shell’s IoT-Connected Drilling Rigs:
IoT rig sensors reduced non-productive drilling time by 30% by detecting real-time equipment anomalies. 7
4. Automation in O&G
The global market value of automation technology in the oil and gas sector will almost double and reach around $42 billion by 2030. The implications of automation in the oil and gas sector are:
- RPA & Intelligent automation: Automating the closing process through RPA (Robotics Process Automation) can significantly reduce closing time, reduce the risk of human errors, and improve auditability in the oil and gas sector. Feel free to check our article on intelligent automation in the oil and gas industry.
- Automating O&G supply chains: Through RPA, procurement transactions can be automated to improve cycle times and achieve overall efficiency in oil and gas supply chains.
- Drones in offshore drilling: Drones and submersible bots are used to automate inspecting inaccessible areas in offshore drilling. Bots can also reduce errors and increase worker safety while installing new parts and repairing existing ones in risky locations.
Case Studies:
- Shell’s Autonomous Drilling Robots:
Automated drilling systems increased operational efficiency by 20% in deepwater Gulf of Mexico projects, reducing human error risks. 8 - Chevron’s Submersible Robots:
Autonomous underwater vehicles (AUVs) inspected subsea pipelines, cutting inspection costs by $15M/year and improving safety in hazardous environments. 9
Figure 1. The global market value of O&G automation by 2030
5. AR & VR in O&G
The AR (Augmented Reality) and VR (Virtual reality) market is projected to increase 10 times to ~$300 billion by 2024. AR and VR have implications for the oil and gas sector.
- Improved training: VR headsets can give workers practical training without visiting offshore plants. This can provide an efficient and safer way of applying theoretical knowledge in practical cases.
- Improved maintenance: AR headsets can provide hands-free instruction steps and relevant tools and parts. This can significantly increase maintenance efficiency, providing graphical information and eliminating the need to read lengthy manuals. Additionally, these AR headsets can provide live video access to technicians who are not available at the maintenance location and record the process for the future.
Case Study:
- BP’s VR Safety Training:
VR simulations for offshore emergencies improved worker response times by 25% and reduced accidents by 18% in the North Sea. 10
6. Blockchain in O&G
The implications of blockchain technology in the oil and gas sector are:
- Secure O&G transactions: Blockchain technology allows digital transactions to be performed with higher transparency and security. For example, Natixis, IBM, and Trafigura initiated a smart contract platform based on blockchain for the USA to manage crude oil deals securely. IBM has also launched a shareable ledger system based on SAP, which helps improve visibility and efficiency in daily transactions, specifically for the oil and gas sector.
- Increased trust: Blockchain technology can also enable the storage and authentication of certificates of recruitment training. It can also enable increased transparency between business partners regarding sustainability and ethical practices.
Case Study:
- BP’s ESG Compliance Tracking:
Blockchain recorded emissions data across 500+ facilities, ensuring compliance with EU regulations and reducing audit costs by $5M/year. 11
For broader utility sector applications, such as utility asset management, SAP meter to cash process automation, and advanced metering infrastructure optimization, check out these tools:
- SAP utility solutions
- AI in utilities
- RPA in utilities
- Customer information system utilities
- Smart grid solutions
External Links
- 1. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 2. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 3. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 4. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 5. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 6. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 7. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 8. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 9. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
- 10. The growing role of generative AI in the Oil and Gas industry.
- 11. iDempiere 10 "Peace" - Free Open Source ERP and CRM. Free Open Source ERP and CRM
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