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.
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 were the three most important benefits that digital technologies can drive 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, we 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 and browsers. We are also able to improve on safety as we leverage of 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 us also make sense of the piles of seismic data, logs, and project data. We are able to search across, identify and correlate images and patterns, saving our geoscientists and engineers countless hours navigating through loads of data across their organizations. Bringing around big compute capabilities and combining it with time-series data, we are also able to develop reservoir models that furnish a dynamic and current understanding of our reservoir characteristics.
Artificial intelligence is also delivering and promising big advancements in drilling optimization; enabling better penetration rates, asset longevity, and reducing downtime. We 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’re able to predict 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 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.
A connected and empowered workforce
Equally important to the intelligent cloud and intelligent edge discussion, is streamlining those experiences to the industry information and field workers through secure productivity platforms.
The productivity case is one in which we need to make sure we are empowering a connected workforce; providing them the tools and insights as and when needed. There is need to bring predictability and integration across our different processes, and optimize the tasks carried along.
As an example, building on Microsoft Azure, Office 365 and Dynamics 365, we brought our Connected Field Service (CFS) platform offering to proficiently address many use cases across the Oil & Gas. CFS allows the leverage of data from sensors, devices, knowledgebases and big data stores to support field workers with actionable insights. Building on CFS, companies can mobilize the right resources to carry maintenance tasks and workorders, support them with the right tools and insights, optimize 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 tops our priority list as we bring all above capabilities. Since 2012, the GCC energy sector has been rocked by several severe cyber-attacks that have cost companies time, money and brand prestige. Tools as Big data and advanced analytics solutions provided by Microsoft – 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 here again plays a major role in improving and empowering threat detection, containment and response.
Case in point
In September, Shell announced it has selected 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. Shell expects to realize substantial economic value by rapidly scaling and replicating AI and machine learning applications across its upstream and downstream businesses and improving operational performance.
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 UAE last month, ENOC and Microsoft announced a partnership on 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 the queuing and waiting times in the forecourt, improve the availability of services and assets, bring relevant marketing and advertising context to all customers – allowing them to avail the right products at the right time. 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 (AR), and industrial IoT technologies to deliver deep-learning capabilities for reservoir characterisation, modelling and simulation. 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 artificial intelligence (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 innovaions are real. They have produced measurable and advantageous efficiencies – sustained and improved production, operational excellence enhancements, cost reductions, productivity surges and safer workplaces. 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, and we look forward to demonstrating its perfect convergence with the intelligent edge, at the upcoming Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC) 2018.
ADIPEC has become a key event on the calendar of the global oil and gas industry, gathering stakeholders and specialists from multiple disciplines for the purposes of knowledge transfer and collaboration. Microsoft’s theme at this year’s event is “Empowering Oil & Gas with AI” where the company will showcase solutions around artificial intelligence and Internet of Things to highlight how they can enable digital transformation within the industry – the means to engage customers, empower employees, optimise operations and reinvent products and services.
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. Organizations in the region’s oil and gas sector can make the most out of the Microsoft Cloud by availing themselves of enterprise-grade reliability and performance, combined with data residency and the broadest compliance.
