OPERATIONS & MAINTENANCE
embracing declarative AI equips industry players with the agility and innovation necessary to drive enhanced operational efficiencies, strategic decision-making, and profitability.
PLATFORM-AGNOSTIC APPROACH A flexible, platform-agnostic approach is essential in the dynamic landscape of applied AI. This flexibility allows organisations to leverage the best tools and technologies across various platforms, ensuring adaptability, and fostering innovation tailored to industry- specific needs and challenges.
KEY APPLIED AI FEATURES IN OIL & GAS Applied AI can be used in oil and gas applications in a number of different ways. One application is for predictive maintenance. The objective here is to minimise unplanned downtime and optimise maintenance schedules. How this can be achieved is by using AI algorithms to analyse equipment data, identifying patterns and anomalies that precede failure. This approach enhances operational efficiency, reduces maintenance costs, and improves overall equipment effectiveness.
PIPELINE MONITORING When using applied AI for pipeline monitoring, the aim is to ensure the integrity of pipeline infrastructure and prevent leaks or failures. AI analyses data from sensors along pipelines, detecting anomalies and predicting potential failure points. This improves environmental safety, reduces the risk of costly leaks, and ensures continuous operation. Exploration data analysis is
another good example of how applied AI can be used in this sector. Here, it can enhance the discovery and evaluation processes of new energy reserves by deploying AL algorithms to analyse geological and seismic data, identifying patterns and insights that guide exploration decisions. This helps to streamline the exploration process, improves decision-making, and increases the likelihood of discovering viable reserves.
SUPPLY CHAIN OPTIMISATION Improving the efficiency and responsiveness of the supply chain is also possible. Here, AI analyses supply chain data, optimising routes, inventory levels, and supplier interactions. Impact: Reduces operational costs,
minimises waste, and improves the adaptability of the supply chain.
AI-POWERED PROJECT DESIGN AND DELIVERY The objective here is to enhance the planning, design, and execution of oil and gas projects. AI supports project managers in
scheduling, risk management, and resource allocation, utilising historical data and predictive analytics. Ultimately, this approach improves
project outcomes, reduces risks, and ensures projects are delivered on time and within budget.
SUMMARY Applied AI holds transformative potential in the oil and gas sector, promising enhanced operational efficiencies, innovation, and profitability. A strategic, outcome- focused approach, coupled with the adoption of declarative AI models and a platform-agnostic strategy, is essential for navigating the integration journey successfully. By harnessing the power of AI, industry players can unlock new realms of possibility, driving forward innovation, efficiency, and success in the oil and gas exploration landscape.
Nick King is CEO and founder of Data Kinetic.
www.datakinetic.com
www.engineerlive.com 19
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52
