Big Oil Big Tech Big Data

Eni SpA, an Italian oil and gas (O&G) multinational, recently announced a partnership with Google Cloud. BP and Amazon also agreed to further collaborations. Why are supermajors in the O&G industry collaborating with tech companies, and what benefits come out of such enterprises?

There has recently been unprecedented upheaval in the global O&G industry due to various complex challenges, including upstream volatility, midstream constraints, industry consolidation and shifting customer demands based on an increasing swing toward greener alternatives. With an unprecedented drop in demand due to COVID-19 becoming the proverbial straw on the camel’s back, it has become imperative for businesses to go on a cost-cutting drive. 

Contrary to popular belief, the oil business is very technologically advanced. Cutting-edge tools are used to map out and drill into complex rock formations thousands of feet below the ground.  For example, Total S.A, the French oil major, and Eni are running two of the most powerful supercomputers in the world. Total’s Pangea has clocked speeds of more than 5 quadrillion calculations a second (yes, that is extremely fast), according to The Top 500 List.

Nevertheless, the industry has fallen behind in terms of digital transformation and leveraging real-time data. In late 2014, MIT Sloane Management Review and Deloitte scored the O&G sector's "digital maturity" at 4.68 out of 10. By the fall of 2019, things got even worse, with O&G scoring a mere 1.3, easily the lowest amongst all the sectors. However, this is changing due to the perfect storm of advancements in technologies, falling costs of digitalization and lower oil prices, which may never reach the high levels previously attained. PwC has reported that O&G executives see the most potential in cloud computing, energy analytics and machine learning.

To accomplish this, big oil has finally joined other industries in the digitalization drive and turned to big tech to provide.

An enormous amount of data is constantly being generated by the O&G industry:

• Data volume for a single well exceeds 10 TB per day, thanks to optical fibers combined with various sensors being used in wells to record different parameters, such as fluid pressure, temperature and composition.
• A single offshore drilling rig can create over one terabyte (TB) of data per day, especially due to recent innovations in drilling tools, such as logging while drilling (LWD) and measurement while drilling (MWD).
• A large refinery generates one terabyte of data daily.
• Pipeline inspections generate approximately 1.5 TB for every 600 km inspected and ultrasounds around 1.2 TB for eight hours of scanning.
• Seismic surveys collect around 10 TB each.

But what can be done with such oceans of data? This is where big tech is providing expertise, innovation and new technologies for the digitalization of big oil.

Within the past couple of years, Microsoft has announced collaborations with Chevron, ExxonMobil, Suncor and Petrobras. These partnerships have established Microsoft Azure as their primary cloud provider in order to harness the power of cloud computing, big data and machine learning.

Halliburton is using Microsoft’s technologies, such as machine learning and augmented reality (AR), an example being DecisionSpace365 created on Azure. It enables real-time data streaming from devices in oil fields and the ability to apply deep-learning models for optimized drilling and production, consequently lowering costs for customers. Predictive deep-learning algorithms help optimize field assets and enable exploration and deep-earth models by using software to fill gaps in sensor data while reducing the number of steps and time required for rendering models.

Suncor, a Canadian energy company specializing primarily in oil sands, is applying Microsoft’s technologies in various ways. One example is its use of fully autonomous trucks at its oil sands mines. Employees at some of their facilities wear wireless badges, allowing the company to track and analyze frontline maintenance work with the goal to improve safety and productivity.

Amazon Web Services (AWS) counts BP and Shell amongst its customers. BP in particular has significantly expanded its relationship with AWS by agreeing to supply renewable energy to power Amazon’s operations. In exchange, Amazon will help BP digitize its infrastructure and operations. This includes applications migration from BP’s own European mega data centers to the AWS cloud, in addition to collaborating on different AI and machine-learning initiatives. In this way, BP can reduce energy use and emissions from its own digital infrastructure and data centers. The resulting lower operating costs are the cherry on top of the cake.

Total and Google Cloud signed an agreement to jointly develop AI solutions. These can be applied to subsurface data analysis for O&G exploration and production, most notably from seismic studies (using Computer Vision technology) and to automate the analysis of technical documents (using Natural Language Processing technology).

Eni has also linked up with Google Cloud to construct a new digital platform, Open-es, to support sustainability in the industrial supply chain. It will be open to all players in the energy sector to pool data, best practices and sustainability models. Knowledge-sharing will set in motion an upsurge in safety and efficiency across the industry.

Schlumberger, partnering with Google, is deploying its O&G software suite, including the WesternGeco Omega geophysical data processing platform and Software Integrated Solutions DELFI cognitive E&P environment on Google Cloud Platform (GCP), to perform seismic processing, interpretation and subsurface modeling.

Graphics processing units (GPUs), due to their enormous processing power, offer benefits through the concept of digital twins. A digital twin is a continuously learning virtual digital copy of all assets, systems and processes. It can predict asset behavior and capacity to deliver on specific outcomes within given parameters and cost constraints.

NVIDIA is assisting Baker Hughes in employing GPU-accelerated computing to work on platforms and build AI-enabled services for major O&G operators across the globe.

Similarly, Shell has chosen Bentley’s iTwin platform, which is an Azure cloud-based platform providing interoperability across supply chain systems. This will allow Shell to manage and analyze data, integrate with existing systems, and increase collaboration across business operations.

According to research by Kimberlite, just 3.65 days of unplanned downtime a year can cost O&G companies approximately $5 million. An average offshore O&G company experiences about 27 days of unplanned downtime a year, which can amount to $38 million in losses. In some cases, this number can rise to as much as $88 million.

Driven by the Internet of Things (IoT), operations and maintenance are turning more proactive and predictive as opposed to reactive and planned. Data can be leveraged from sensors (e.g. temperature, vibration, flow rate sensors, etc.) to identify any anomalies in equipment behavior and forecast failure modes within a certain timeframe.

Predictive-maintenance solutions help O&G companies forecast equipment breakdowns before they can have an adverse impact on their safety levels and bottom line. Schneider Electric reports that applying IoT-enabled predictive-maintenance solutions can help save $4 million due to early identification of rotating machinery damage, $500,000 due to early identification of coupling failures and $370,000 due to early identification of heat exchanger valve problems.

It can also improve asset utilization and increase productivity by making operations more flexible and agile. By comparing operational data across multiple pieces of equipment, IoT solutions can help estimate machine utilization, identify the periods of best performance and establish best practices to improve performance across the entire O&G supply chain—from exploration to refining and distribution.

While the O&G sector produces 29 percent of methane emissions, the greenhouse effect of methane is 86 times higher than that of carbon dioxide. In the U.S. alone, the O&G industry releases 1 million tons of methane into the environment every year due to leakages. IoT helps identify and reduce pipeline leaks, thus decreasing environmental damage.

O&G companies are also adopting AR/VR for subsurface studies, training and simulation, maintenance and planning. Hard hats equipped with AR can project instructions for the technician directly onto the equipment to conduct an inspection or maintain a system. Instead of being dependent on manuals, AR enables this information to be delivered graphically, thus increasing efficiency and reducing errors.

VR can be used for practical training instead of in a classroom or on location. Trainees use a VR headset to enter an environment or interact with a piece of equipment virtually. During the process, it provides invaluable hands-on training at a fraction of the cost. Likewise, VR apps connected to sensors enable engineers to monitor equipment in real-time without needing to be onsite. Geoscientists are also able to visualize seismic data through VR, and even drill virtually, so that they can better determine where to explore.

The three largest service providers in this field are Schlumberger, Halliburton and Baker Hughes. Before the pandemic, O&G companies always counted on these specialists to be onsite and control drill bits and interpret real-time data. Now, to adhere to travel restrictions and social-distancing recommendations, drillers had to work from home. 

For ongoing operations, during the second quarter of the year, Baker Hughes and Schlumberger both had two-thirds of their drilling activity supported by remote work. For Schlumberger, this was up 25 percent from the first quarter. For Baker Hughes, it was up 20 percent. Halliburton, the largest U.S. fracking company, has reduced the number of onsite engineers by shifting work to real-time operation centers. All of them have cited the adoption of remote work, which allowed them to shut down many operational sites, as the leading cause of significant operating cost reductions.

For drilling new wells, due to travel restrictions, many companies might not have been able to achieve their targets without the adoption of remote technology. Chevron was able to continue directional drilling in the Permian Basin of West Texas and New Mexico by setting up a remote team based mostly out of their homes in Houston because they were able to get real-time data through Azure. 

ExxonMobil was able to make its Permian Basin operations totally cloud-based, leading to secure and reliable collection of live data from the oil field assets. This has allowed for quicker and more accurate decision-making on drilling optimization, well completions and personnel deployment.

There is no doubt that the confluence of technologies is beneficial not only for the O&G industry but also the whole world. It will reduce health and safety incidents and lead to better-trained personnel by allowing remote work and simulations unless absolutely necessary. Predictive maintenance will save tons of money by streamlining maintenance plans, as well as an overall reduction in the number of catastrophic failures over time. Goldman Sachs estimates that a 1 percent reduction in the O&G industry’s capex (capital expenses), opex (operating expenses) and inventory management can result in savings of about $140 billion over a 10-year period. Last but not least, all these factors will lead to considerably minimizing adverse effects on the environment, thus protecting our precious lands, oceans and wildlife.