In the oil and gas industry, technologies such as artificial intelligence (AI), the internet of things (IOT), machine learning and big data can serve operators by increasing productivity and streamlining processes, all while helping them attract and retain talent, and remain secure and compliant.
When asked about the most important benefits of digital technologies for the upstream oil and gas segment, respondents to the “Accenture and Microsoft 2017 Upstream Oil and Gas Digital Trends Survey” cited faster and better decision-making, shorter time to first oil and gas, and reduced risk enabled by real-time decision support as the three most important benefits for upstream oil and gas companies. Additionally, 39% of respondents said the greatest risk from a lack of digital investment is becoming uncompetitive.
From exploration to drilling, from production to transportation, from storage to trading, the intelligent cloud and the intelligent edge come together to deliver digital capabilities that can majorly boost operational excellence, improve profitability, whilst bringing about safer and more productive operations.
Advanced analytics, empowered by operational data lakes and machine learning algorithms, is already delivering actionable insights of the mountains of data generated by IOT, structured and unstructured data accumulated over decades.
Applying cognitive intelligence can improve productivity by leveraging digital assistants and BOTs that bring along many applications to enhance knowledge capture and reuse, as well as timely insights embedded in everyday use apps like chat messaging apps and internet browsers.
The industry can also improve on safety by leveraging computer vision, for example, to track behaviours that promote safe operations like wearing personal protective equipment, identifying hazards like oil spills and smoke, as well as controlling access and geofencing of personnel and assets within permitted zones.
AI helps make sense of the piles of seismic data, logs, and project data that operators collect. Using this technology to search across, identify and correlate images and patterns saves geoscientists and engineers countless hours navigating through loads of data across their organisations. Bringing around big computing capabilities combined with time-series data, we are also able to develop reservoir models that furnish a dynamic and current understanding of reservoir characteristics.
Artificial intelligence is also delivering and promising big advancements in drilling optimisation; enabling better penetration rates, asset longevity, and reducing downtime.
Operators are able to predict events like stick-slip that can cause twisting and damage of the drill string, and bring around major delays. Also, relying on AI technologies, we are able to predict the optimal path for drilling bits, and steer them within the pay zone.
IOT and machine learning also help us drive unparalleled asset performance and availability, allowing for operations continuity through accurate predictions about asset and process failures.
The intelligent edge is a game changer here as well, as it allows the deployment of rich machine learning predictive models to edge devices and controllers. In essence, this reduces the dependence on, and usage of, communications and enables predictive decisions to be actioned in a timely manner.
Collectively, this allows companies to build rich models for determining when, and under what conditions, machinery will break down, as well as deploy near real time responses. Maintenance ahead of failure, brings dramatic value in sustaining production, reducing downtime, and optimizing the overall maintenance process, cutting costs and allocating resources efficiently.
Equally important to the intelligent cloud and intelligent edge discussion is streamlining those experiences to the industry’s information and field workers through secure productivity platforms.
The oil and gas industry needs to make sure it is empowering a connected workforce; providing them the tools and insights as and when needed. There is a need to bring predictability and integration across different processes, and to optimise tasks.
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As an example, building on Microsoft Azure, Office 365 and Dynamics 365, we brought our Connected Field Service (CFS) platform offering. CFS allows the leverage of data from sensors, devices, knowledge bases and big data stores to support field workers with actionable insights.
Building on CFS, companies can mobilise the right resources to carry maintenance tasks and workorders, support them with the right tools and insights, optimise and re-engineer critical processes like permit-to-work and plant turnarounds. CFS allows companies to drive accountable and predictable field performance, whilst mitigating safety and otherwise process risks.
Cyber security is a top priority. Since 2012, the GCC energy sector has been rocked by several severe cyber-attacks that have cost companies time, money and brand prestige. Tools like big data and advanced analytics solutions are indispensable in the regional sector’s fight against malicious actors.
By correlating network events with global metrics, suspicious network behaviour can be identified and flagged in time to mitigate or prevent damage to critical infrastructure. Intelligent cloud plays a major role in improving and empowering threat detection, containment and response.
In September, Shell announced its selection of C3 IOT with Microsoft Azure as its artificial intelligence (AI) platform to enable and accelerate digital transformation on a global scale.
Shell announced it will use AI to predict when maintenance is needed on compressors, valves and other equipment, help steer drill bits through shale deposits; and improve the safety of employees and customers.
Chevron also launched an effort to predict maintenance problems in its oil fields and refineries. Building on Microsoft’s IOT services, Chevron aims to enable thousands of pieces of equipment with sensors by 2024 to predict exactly when equipment will need to be serviced.
In the UAE last month, ENOC and Microsoft announced a partnership on a ‘Service Station of the Future’ concept that will harness the power of the intelligent cloud to build rounded views of ENOC customers and promote enhanced standards of safety, security and information on forecourts.
Advanced machine-learning and AI technologies will use CCTV camera feeds, and data of all types, to manage queuing and waiting times in the forecourt, improve the availability of services and assets and bring relevant marketing and advertising to all customers. Safety is a key focus as well as the solution helps detect hazards such as smoke, fire and seemingly abandoned vehicles.
Key technology players across the industry are also adopting AI. Halliburton adopted a hybrid global cloud using machine learning, augmented reality and industrial IOT technologies to deliver deep-learning capabilities for reservoir characterisation, modelling and simulation, which improves knowledge of the reservoir.
Halliburton shared its solution with the industry through DecisionSpace 365, which the company made available on Microsoft Azure, enabling real-time IOT intelligence for the entire sector.
Another example is Schneider Electric, where using edge analytics, they incorporated AI and machine learning into their Realift solution to add predictive capability into remote management of rod pumps.
In that case, the controller can modify the operating parameters of the pump to avoid or mitigate the impact of the unexpected changes. Or, if necessary, it can shut down the pump before any damage occurs and notify the company that repairs are necessary—protecting the machinery, and preventing potential environmental damage.
Such innovations are real. They have produced measurable and advantageous results, including sustained and improved production, operational excellence enhancements, cost reductions, productivity surges and safer workplaces.
The past few years have seen an increase in demand for cloud services across the GCC and wider MEA region. A Microsoft study found that more than 51% of organisations in the Gulf identified cloud computing as a top priority for adoption in 2018.
The surge in uptake of its solutions and innovations led Microsoft to announce that it will deliver its trusted, secure and versatile cloud to Middle East and Africa customers from four datacenters in the region, two in the UAE and two in South Africa.
In the oil and gas industry, digital transformation is nothing less than meta-energy–energy for the energy industry. The intelligent cloud is at the heart of this transformation.
