TED Talk on methane and the oil and gas industry

This TED Talk heralds a new era in fighting climate change, from space

Watch this video to learn about a bold, new initiative to combat global warming

EDF and partners are launching a rocket to put a new satellite in orbit that could change the course of global warming in our lifetimes.

MethaneSAT will gather data about a pollutant – methane – that’s warming the planet, and put that data in the hands of people who can easily fix the problem.

EDF President Fred Krupp unveiled the groundbreaking project at TED’s flagship event in Vancouver, British Columbia, as part of The Audacious Project, successor to the TED Prize.

Just the first step will have the same near-term climate benefit as shutting down one-third of the world’s coal-fired power plants.

Fred Krupp, EDF President

Fred Krupp, EDF President

Our goal is to cut methane emissions 45 percent by 2025, and the data gathered by this satellite will make that possible. Nothing else will have the same kind of near-term impact at such a low cost.

The power of information

To learn the magnitude of the problem with methane, we collected data with drones, planes, helicopters, even Google Street View cars. It turned out that emissions are up to five times higher than what the government is reporting.

So we didn’t wait for Washington. We published our research, shared it with everyone and saw them take action. Leading oil and gas companies replaced valves and tightened loose-fitting pipes. Colorado became the first state to limit methane pollution. California followed suit, and the public joined in.

By bringing the right people to the table – and leveraging the best of technology, science, data and partnerships – we were able to make the invisible visible, empowering everyone. This enabled us to find new solutions that can be taken to scale and make a lasting impact.

And that’s what the emerging Fourth Wave of environmentalism is all about.

Source:  EDF Environment Defense Fund

Repsol and Google Cloud to optimize refinery management using big data and artificial intelligence

  • Repsol’s goal is to maximize the performance and efficiency of a refinery, which is among the largest and most complex industrial facilities.

  • Google Cloud will provide its computing power, experience with big data and machine learning expertise.

  • The initiative is part of Repsol’s commitment to digitalization, innovation and technology across all of its business areas.

Repsol has today announced that it is working with Google Cloud to launch a project that will use big data and artificial intelligence to optimize management of the Tarragona refinery. Refineries are among the largest and most complex industrial facilities.

Repsol’s Executive Managing Director of Downstream, María Victoria Zingoni, and Google’s Country Manager for Spain and Portugal, Fuencisla Clemares, participated in the launch of the project, which will be carried out in the Tarragona Industrial Complex and marks a pioneering challenge in the global refining industry.

This initiative puts the latest cloud technology from Google at the service of the refinery’s operators. Repsol’s objectives are to maximize efficiency, both in energy consumption as well as consumption of other resources, and to improve the performance of the refinery’s overall operations.

To achieve this, Google will make available to Repsol its data and analytics products, the experience of its professional services consultants and its machine learning managed service, Google Cloud ML, which will help Repsol’s developers to build and bring machine learning models to production in their refinery environment.

The management of a refinery involves around 400 variables, which demands a high level of computational capacity and a vast amount of data control. This is an unprecedented challenge in the refining world.

Until now, the highest number of functions integrated digitally in an industrial plant is around 30 variables, demonstrating the vast challenge this project presents. It aims to increase the number of variables being managed by more than 10 times. Repsol chose the Tarragona refinery to develop this initiative because the online configuration of its production schematics facilitates testing and implementation.

This project, as well as the collaboration with Google Cloud, is part of Repsol’s ongoing digitalization, innovation and technology projects development in all of its business units to improve its competitiveness and efficiency.

The project has the potential to add 30 cents on the dollar to Repsol’s refined barrel margin, which could translate to 20 million dollars annually for the Tarragona refinery, with significant upward growth if all optimization objectives are achieved.

Improvement of industrial processes

For Maria Victoria Zingoni “this is an efficiency project in all senses: it seeks to consume fewer resources; reduce energy consumption, which is the highest cost of a refinery; increase the unit reliability and, by extension, improve economic performance.”

“This initiative belongs to a more comprehensive plan to take advantage of the possibilities afforded us by the latest in technology, and improve industrial processes. We are not afraid of aiming for the stars, even if some projects will fail. This is about learning as fast as possible and that machines help people in their work,” said Repsol’s Executive Managing Director of Downstream.

Google’s Country Manager for Spain and Portugal, said that “This project demonstrates the commitment from Spanish companies to digital transformation and the application of machine learning in industrial processes, of which Repsol is a pioneer.

“At Google, we are deeply committed to sustainability and ensuring that we have a positive impact on the environment – and we see technology such as machine learning and data analytics play an important role in helping our customers maximize their own efficiency. We are proud to collaborate with a company such as Repsol, which has been a leader for many years in leveraging technological innovation to reduce its environmental impact,” said Fuencisla Clemares, Country Manager Google España y Portugal.

This project, as well as the collaboration with a partner like Google, is part of Repsol’s ongoing digitalization, innovation and technology projects development in all of its business units to improve its competitiveness and efficiency.

This project is compatible with other digital initiatives that are already in use at Repsol’s industrial facilities, such as Siclos, with which Repsol’s refinery control panel operators learn, in real time, the economic implications of operating decisions; or Nepxus, which increases planning, analysis and agility in decision-making in the control rooms of these industrial installations.

Tarragona is one of the six refineries that Repsol operates in Spain and Peru. This plant has the capacity to distill 186,000 barrels of oil a day and is Repsol’s third-largest unit.

The facility occupies over 500 hectares and is as large as the Tarragona’s city center. The refining unit processes 9.5 million tons of raw material a year and the storage tanks can hold a million cubic meters.

REPSOL Press Release 

OFFSHORE DECOMMISSIONING IN ASIA PACIFIC REGION: WHY ‘RIG TO REEF’ IS VITAL

The Asia Pacific region is set to follow the North Sea in increasing its decommissioning activity over the next decade. Indonesia, Brunei, Malaysia and the rest of the region is home to 833 installations that are on or over 20 years old – the average life expectancy of offshore assets. But with so much of the region’s infrastructure under threat from decommissioning, many have questioned the impact to the environment.

A thought piece by the National University of Singapore (NUS) singled out the importance of rig to reef in this context back in 2012. In this blog, we explore what could be done in the region to both keep the integrity of the sea bed and complete decommissioning applications as efficiently as possible.

RIG-TO-REEF

Rig-to-reef (RTR) is the practice of converting decommissioned platform infrastructure into artificial reefs for the seabed. The practice has already proved popular in the Asia Pacific when the storm-damaged Baram-8 in Malaysia was made into an artificial reef. Despite there being no current RTRs in place in the region, there is sure to be an appetite as decommissioning work increases.

Rigs prove popular with sea life, especially as they become an integral part of the seabed over their 20-30 year life span. An OCS report that focussed on the Gulf of Mexico in 2000 stated that fish densities were 20-50 times higher around the platforms than anywhere else in open water – a true sign that artificial reefs work.

PROS OUTWEIGH THE CONS

While operators may look towards asset life extension techniques to keep relevant rigs operating, those who are set to decommission will be pleased to know that the pros outweigh the cons in terms of implementing RTRs with old assets.

Despite potential navigational issues around the Asia Pacific region, operators creating RTRs could benefit from being more environmentally friendly, increasing fisheries in the field, and potentially negating costs such as rig disposal. The question on whether RTRs would be welcome in the region are so far undecided and confusing by governing bodies, according to the NUS.

GIVEN THE GREEN LIGHT

In her presentation for the National University of Singapore, Youna Lyons highlighted the large discrepancy between governing bodies and law in the Asia Pacific region that meant operators looking to RTRs would be left confused as to whether they could undertake a project after decommissioning.

“(While) international law does not prevent the re-use of rigs as artificial reefs, provided that it does not compromise the safety of navigation, IMO guidelines (on the matter) are inadequate. A paradigm shift is needed in the approach.”

The biggest issue seems to be the safety of navigation around such artificial reefs by shipping traffic. That aside, the law states that rigs can be re-used, it is just a case of where they will be able to be positioned.

RIG TO REEF IS VITAL

In summary, the presentation reveals how vital rig to reefs can be for both operators and environment. While operators can potentially save money, and enhance the environment they’ve extracted from, the seabed and sea life can see drastic increases in activity if the manmade reefs are positioned well – as long as governing bodies and local authorities agree, Asia Pacific could benefit from more RTRs in the future.

THE INCREASE OF DECOMMISSIONING

As operators around the world review their aged assets, in the current climate it is no surprise to see decommissioning projects beginning on non-profitable rigs. In the Claxton Engineering Decommissioning Case Study Pack, you will learn how the Claxton team have already helped operators on their decommissioning projects and helped to save time and money too.

To find out more about the free offshore Decommissioning Case Study Pack, and to get your hands on a copy, click here.

Please be sure to follow and subscribe to Claxton at http://insights.claxtonengineering.com/.

Originally written and posted by Andy Norman, Head of Brand and Marketing, Claxton.

 

Video

Johan Sverdrup – the digital flagship

Digital technologies are shaping the world around us, and Statoil intends to be a driver of change in the energy industry. This film provides an overview of the digital ambitions and technologies which Statoil is working to implement on the Johan Sverdrup field to further improve safety, production and value.

Published on Feb 8, 2018

YouTube

OTC 2018 – ION commences new 2D multi-client program offshore West Africa

HOUSTON, May 2, 2018 /PRNewswire/ — ION Geophysical Corporation (NYSE: IO) today announced acquisition began on a new 2D multi-client program offshore Ghana in partnership with Geoex and Ghana Geophysical. 

ION and its partners will acquire up to 7,200 km of data in advance of the license round anticipated in late 2018 to help refine understanding of the hydrocarbon potential of the area.  Similar to other ION BasinSPAN™ programs, West Equatorial AfricaSPAN was custom designed in collaboration with regional experts and clients to answer remaining geological questions with a survey tied to recent discoveries.  This data will be the first offshore Ghana to image 40 km below the seafloor.  In addition, ION’s Marlin™ operations optimization software will help maximize the safety and efficiency of the survey.  Acquisition is expected to be completed at the end of May 2018 with Fast Track products available in Q3 2018 and final imaging products expected in Q1 2019.

Ghana is believed to have up to 5-7 billion barrels of petroleum and up to 6 trillion cubic feet of natural gas in reserves and has renewed interest due to new projects coming online and the resolution of the maritime boundary dispute with Côte d’Ivoire in September 2017.  The Ghanaian Government is transitioning from an open door system to its first competitive bid round due to the petroleum legislation passed in August 2016 making its petroleum resource management more transparent.

“We are excited to support the Ghanaian government as the country prepares for its next offshore license round with the stated goal to attract additional investment to develop their reserves,” said Joe Gagliardi, Senior Vice President of ION’s E&P Business Development group.  “The new data we are acquiring will help a number of E&P companies properly evaluate the offshore acreage in advance of the country’s first competitive bid round later this year.”

To learn more, visit iongeo.com/WEASPAN.

About ION

ION develops and leverages innovative technologies, creating value through data capture, analysis and optimization to enhance critical decision-making, enabling superior returns.  For more information, visit iongeo.com.

Contacts

ION (Investor relations)

Executive Vice President and Chief Financial Officer
Steve Bate, +1 281.552.3011
steve.bate@iongeo.com

ION (Media relations)

Vice President, Communications
Rachel White, +1 281.781.1168
rachel.white@iongeo.com

Artificial Intelligence in Oil and Gas – Comparing the Applications of 5 Oil Giants

Today, AI is helping the oil and gas industry chart its future course. Since no previous sources have provided an in-depth look at the impact of AI among the leading oil and gas companies, we set out in this week’s research to help answer questions that oil and gas leaders are asking:

  • What types of AI are applications currently in use by leading oil and gas companies such as ExxonMobil and Shell?

  • What (if any) results have been reported on AI applications implemented by leading companies in the oil and gas industry?

  • Are there any common trends among their innovation efforts – and how could these trends affect the future of the oil and gas industry?

This article seeks to provide a comprehensive look at applications of AI by the five leading oil and gas companies. Our ranking of companies is based on the Forbes’ 2017 Global 2000 ranking of the world’s biggest public companies.

Through facts and figures we aim to provide pertinent insights for business leaders and professionals interested in how AI is impacting the petroleum industry.

Prior to exploring the applications, we’ll present the common patterns that emerged from our research in this industry.

Artificial Intelligence in Oil and Gas – Insights Up Front

The most popular AI applications from the top five industry leaders currently appear to be: 

  • Intelligent robots  – Robots designed with AI capabilities for hydrocarbon exploration and production, to improve productivity and cost-effectiveness while reducing worker risk (see ExxonMobil and Total below)

  • Virtual assistants – Online chat platform that helps customers navigate product databases and processes general inquiries using natural language (see Royal Dutch Shell below)

In the full article below, we’ll explore the AI applications of each company individually. We will begin with ExxonMobil, the #1 ranked company in this industry based on the Forbes’ 2017 Global 2000 ranking of the world’s biggest public companies.

ExxonMobil

Among its ongoing collaborative efforts with approximately 80 universities in the U.S. and abroad, In December 2016, ExxonMobil announced that it is working with MIT to design AI robots for ocean exploration. Brian Williams, an MIT professor and a designer of the AI software that helped create NASA’s Mars Curiosity Rover is a key member of the project team.

While the business advantage of using AI in deep-sea exploration may not be immediately apparent, the company aims to apply AI to boost its natural seep detection capabilities. Natural seeps occur when oil escapes from rock found in the ocean floor. An estimated 60 percent of oil underneath the earth’s surface in North America is due to natural seeps. Robots with the ability to navigate these oceanic regions and detect oil seeps can contribute to protecting the ecosystem and serve as indicators for robust energy resources. It is unclear specifically when ExxonMobil’s ocean exploring AI robots are expected to be deployed.

Oil Seeps

A visual depiction of natural oil seeps (source)

As a founding member of MIT’s Energy Initiative, ExxonMobil has committed a reported $25 million over 5 years to support energy research conducted by MIT faculty and staff. While the company has not published the total amount invested across its 80 university collaborations, we can gain some insight from the following published figures:

  • Princeton University: $5 million over 5 years

  • The University of Texas at Austin: $15 million

“Our goal is to have these submersibles embody the reasoning of the scientists that program them. You want the explorer to do the science without the scientist there. They need to be able to analyze data, keep themselves out of harm’s way and determine novel solutions in novel situations that go beyond basic mission programming. They need to have some common sense and the ability to learn from their mistakes.” – Professor Brian Williams, MIT

Exxon MIT AI

ExxonMobil’s MIT robotics collaboration (source)

Through its partnership with the MIT Energy Initiative and related efforts, ExxonMobil has made energy efficiency and the exploration of new energy sources a core focus of its business priorities. According to its 2016 annual report, the company has reportedly invested roughly $7 billion since the year 2000 on R&D and “deploying emissions-reducing technologies.” The company does not itemize allocations for these technologies and specifics on AI were not published.

Royal Dutch Shell

In August 2015, Shell announced that it would be the first company in the lubricants sector to launch an AI assistant for customers (an anomaly in terms of applications of artificial intelligence in oil and gas). Normally, customers searching for lubricants and related products must navigate a large database in order to find the ideal product(s) they are searching for. Shell aims to use its avatars, Emma and Ethan, to help customers discover products using natural language.

The Shell Virtual Assistant functions through an online chat platform through the company’s website. Examples of information that the system can provide include where lubricants are available for purchase, a range of available pack sizes and general information regarding the technical properties of specific products.

To provide context, the company claims that its Shell Virtual Assistant:

  • Handles over 100,000 data sheets for 3,000 products

  • Provides information on 18,000 different pack sizes

  • Understands 16,500 physical characteristics of lubricants

  • Matches Shell products to 10,000 competitive products

The Shell Virtual Assistant is only currently available in the U.S. and U.K. but also complements four other Shell services including Shell LubeMatch which reportedly provides “over two million product recommendations for Shell customers” annually and is accessible across 138 countries in 21 languages.

Shell Virtual Assistant

An infographic representing the claims made about Shell Virtual Assistant – from Shell’s website

We were able to access the virtual assistant on the company’s website. In a note to users posted above the platform, Shell states that the virtual assistant is still in pilot mode and that efforts are ongoing to increase the knowledge of the virtual assistants and to monitor their effectiveness.

At tech emergency, we have become increasingly wary of “chatbot” and “virtual assistant” efforts that present an innovative story without a substantive business application. It is difficult to assess the genuine business value of the Shell Virtual Assistant at this time, but we tend to air on the side of caution, and we encourage our business readers to do the same (we have collected a series of chatbots that do appear to be driving business value today, and we highlight them in our “7 chatbot use cases” article).

It behooves any company to present an exciting and innovative front in the press – and chatbots seem to be a “low hanging fruit” for supposed AI applications. This is by no means a warning that we specifically state for Shell – all press-facing technology initiatives serve the purpose of molding perceptions about the company (the goes for every industry). We do our best to dig for the genuine business ROI of AI applications, and we advise our readers to approach applications and press releases with skepticism, bearing in mind the motives of the companies behind them (which do not have to be malicious to be misleading and falsely optimistic).

Similar to Shell LubeMatch, the company is also looking to expand the service to other countries and languages.

Shell’s R&D expenditures in 2016 totalled $1.014 billion. While specifics on AI were not reported, according to its Investor’s Handbook, R&D priorities are focused on “improving the efficiency of its products, processes, and operations”, and there is a concentration on developing technologies which support low-carbon energy.

Subsea 7 Shell Robot

Shell’s innovation in collaboration with Subsea 7 has created an Autonomous Inspection Vehicle
that claims to provide safer and better inspections – at a significant cost savings

In the future, the company reportedly seeks to integrate AI and automation into its facilities. Shell envisions that automated robots will be able to take over routine observational tasks and data gathering currently conducted by human employees. The company reportedly integrated a virtual assistant called Amelia  into its business model to more efficiently respond to inquiries from suppliers regarding invoicing.

Shell believes the future of AI in its industry will see a significant increase in unmanned and automated facilities.

China Petroleum and Chemical Corp. (Sinopec)

Sinopec has hinted at the role of AI in moving innovation forward in the oil and gas industry. The company boasts a long-term plan to roll out construction of 10 intelligent plants with a goal of a 20 percent reduction in operation costs.

On the manufacturing front, Huawei (Chinese telecom company) in April 2017 announced a collaborative effort involving Sinopec to design what is described as a “smart manufacturing platform.”

The platform description highlights AI as one of 8 core capabilities of the platform which aims to deliver a centralized method of data management and support integration of data across multiple applications used to manage factory operations.

AI would serve to establish rules and models that would inform how data is interpreted and offer opportunities for identifying valuable insights to improve factory operations. Huawei did not specify a timeline for when Sinopec is expected to fully implement the platform.

Total

Hydrocarbon exploration, the ability to map and identify oil and natural gas deposits beneath the earth’s surface, is a growing area of focus in the oil and gas industry. However, more innovative and environmentally-friendly methods of achieving improved effectiveness and efficiency are needed in the field. Environmental conditions are increasingly challenging for workers conducting hydrocarbon exploration thus technology capable of handling the task while retaining optimal functionality is highly desirable.

In an effort to establish what is described as the “first autonomous surface robots able to operate on oil & gas sites,” Total launched an international competition in December 2013. Total’s ARGOS challenge (Autonomous Robot for Gas & Oil Sites) was narrowed down to five teams hailing from Europe, Asia and South America who were provided with a maximum of three years to finalize their prototypes. For each of the 5 teams, Total provided a maximum of €600,000 (approximately $707,376) to support research and design, and a single prize of €500, 000 (approximately $589,522.50) for the winning robot.

AI was a key component of how the robot would function. Total expected that competitors ensure that their robots were able to deliver reports encompassing real-time data collection related to inspection points (locations where exploration is taking place) and analyses around the effectiveness of the locations of interest.

Total established key goals for the ARGOS robot:

  • The ability to carry out inspections, during the day or night, which are currently performed by humans.

  • The ability to detect abnormal equipment activity and intervene in an emergency. Examples may include simple equipment malfunctions or more high-risk situations such as gas leaks.

In May 2017, Total selected ARGONAUTS designed by a team from Austria and Germany as its winner. Total retains exclusive intellectual rights to the technology behind the ARGONAUTS robot for a period of five years. No further announcements have been made as to when the company will begin implementing ARGONAUTS.

Within its Exploration and Production segment, Total reports that over half of R&D allocations are focused on improving exploration capabilities; hydrocarbons and robotics are specifically mentioned. Innovation and R&D expenditures for oil and gas activities totaled $689 million in 2016.

(Readers with a specific interest in robotics and vehicles for the heavy industry may want to listen to our heavy industry-focused interview with Dr. Sam Kherat on our AI in Industry podcast.)

Gazprom

In June 2017, Gazprom and Yandex (described as Russia’s leading internet company) entered into a cooperation agreement for the implementation of new projects in the oil and gas industry. The two companies plan to tap into AI and machine learning to roll out their prospective initiatives.

Specifically, the collaboration is expected to focus on:

  • Drilling and well completion

  • Modeling oil-refining strategies

  • Optimizing other technological processes

The cooperation agreement reportedly provides flexibility for independent exploration of technologies currently in use in the oil and gas industry and collaborative development and application of projects in R&D. Data sharing and technical support for employee training are also potential points of interest.

“Oil and gas are one of the most exciting industries currently since it involves massive volumes of data, and any easy solutions for optimizing production and business processes have long since been implemented. This combination, together with significant turnover and high level of technological development, creates good opportunities for securing a major effect from implementing solutions based on machine learning and artificial intelligence, and we look forward to a productive partnership, in the long term.” – Alexander Khaytin, COO, Yandex Data Factory

Time will tell specifically how Gazprom and Yandex will leverage AI and machine learning throughout their various initiatives as specific around implementation have not yet been reported.

Gazprom’s technology development plan appears to be deeply rooted in strategic partnerships. In fact, the company claims that it is taking an active approach to identifying innovative, collaborative opportunities that align with its strategic priorities.

Innovation has certainly been a feature of Gazprom’s media profile, however at this current time, our research provides inconclusive evidence of any AI applications that currently in progress or that have demonstrated some preliminary results.

Concluding Thoughts

Leaders in the oil and gas industry are integrating AI in multiple areas. Reducing the carbon footprint, deep sea exploration of hydrocarbons and the implementation of innovative, sustainable energy strategies are driving the pace of evolution in the field.

We suspect that the companies we researched for this article are also implementing lots of business intelligence AI applications – but that these technologies are less frequently mentioned in press (exciting robots and noble environmental efforts are better PR for oil giants than predictive analytics for fuel yields, for example). Nevertheless, we feel that the applications highlighted above should give business leaders a healthy overview of the current AI initiatives among the biggest players in the petroleum industry.

Global energy investment by sector took an interesting turn in 2016. For the first time,  the electricity sector pushed ahead of oil and gas sector. However, the oil and gas sector remains at two-fifths of the global energy supply investment.

AI robots are a promising area of interest particularly to help curb the risk of exposure to dangerous working conditions for many employees. While the U.S. has experienced a downward trend of labor-related injuries or fatalities in the field in recent years, efforts to improve employee working conditions are a smart investment. We predict that improvements in robotic dexterity in any field (retail, agriculture, manufacturing, etc) are likely to trickle directly to robots tasked with dangerous jobs such as those in oil and gas, and fire/rescue. We’ll be following the robotics field in the years ahead, and continuing to update our listings of innovative robotics vendors.

Among oil and gas companies (who are not generally seen to be AI innovators) we can expect industry leaders to be the early adopters. Big budgets and existing tech talent are necessary to implement robust AI initiatives (particularly for complex robotics programs), and few companies on earth have pockets as deep as the big oil giants. We suspect that relatively smaller oil and gas companies will mostly be following the AI leadership of the giants to currently rule the petrol realm.

Published  by Kumba Sennaar

Credit source: Tech Emergence 

Rethinking the oil and gas organization

December 2016, McKinsey & Company, www.mckinsey.com. Copyright (c) 2018 McKinsey & Company. All rights reserved. Reprinted by permission.

Organizational choices made during a time of resource scarcity need reexamination when the cycle turns.

When business cycles turn, cyclical industries can struggle to retool their organizations for the new environment. For instance, today’s oil and gas companies were developed in a time of resource scarcity. To get at those hard-to-find, difficult-to-develop resources, companies greatly expanded the role of their central functions—mandating them to set common standards, make technical design decisions, track company-wide metrics, and disseminate best practices. This worked well during a decade of high growth and high prices but created complexity that added costs, stifled innovation, and slowed down decision making. As these central teams expanded, general and administrative costs grew fivefold, hitting nearly $5 per barrel in 2014 (exhibit), with the biggest increases coming from technical functions such as engineering, geosciences, and health and safety.

Oil companies have cut support functions since 2014 but must consider more radical organizational changes as prices remain weak.

With prices now below $50 a barrel, that organizational blueprint is no longer sustainable. While companies have cut their support functions since 2014, the overall organizations supported by these functions are also smaller. This suggests further reductions in corporate functions will be needed, as well as new organizational models.

A more agile organization, with fluid teams and looser hierarchies, can lower costs and create greater responsiveness to today’s vastly different markets—ranging from megaprojects to less asset-heavy unconventional shale-oil and renewable-asset plays. Technologies such as networked sensors that generate and share data can help optimize production processes, while digitally enabled automation of routine manual activity can reduce human risk and spur productivity. Critically, the structures built to manage scarce talent and large-scale megaprojects will need to be fundamentally redesigned. We see two models arising: for lower-risk assets such as tight oil, a very lean corporate center with highly autonomous asset teams will suffice, while higher-risk, more capital-intensive assets will need a comparatively stronger center with deeper functional and risk-management capabilities.

For additional insights, see “The oil and gas organization of the future.”

About the author(s)

Christopher Handscomb is a partner in McKinsey’s London office, Scott Sharabura is an associate partner in the Calgary office, and Jannik Woxholth is a consultant in the Oslo office.

Meet the First Generation of Nigerian Deepwater Oil Engineers

The deepwater Bonga oil field offshore Nigeria is opening up a unique opportunity to train Nigeria’s first generation of deepwater oil engineers.

One of the skilled Nigerian workers that keeps this complex offshore development running is Dare Famuyide, shift supervisor for Shell Nigeria Exploration Production Company (SNEPCo). When the Bonga field first came online, it was a novel project, Famuyide said.  “We were possibly the first deepwater offshore asset in the Gulf of Guinea.”

Shell’s deepwater Bonga production facility uses one of the world’s largest floating, production, storage and offloading (FPSO) vessels in more than 1,000 meters of water offshore Nigeria. It is 300 meters long and as tall as 12-story building with a deck that spans an area the size of three football fields.

In addition to being a significant revenue earner for the Nigerian economy, the Bonga field has also contributed immensely in developing the deepwater skills of the local workforce, while aiding in the Nigerian government’s aspirations to build truly Nigerian companies that can stand on their own.

Today, 95 percent of Bonga’s core offshore staff is Nigerian.

That workforce also include Prince Nwocha, the first engineer in his family and operations supervisor for SNEPCo at Bonga. Nwocha spends nearly six months of the year deployed at the FPSO, a profession that helps him support his family and also opens up opportunities for his son.

“My son, Justin, likes computation, mathematics, playing with things. And I can see that engineering streak coming out in him,” Nwocha said.

To learn more about the Bonga field, view the video above.

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