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The Dbriefs Oil & Gas series presents:

The Internet of ThingsA new analytical framework for addressing industry challenges

John England, Vice Chairman, US Oil and Gas Leader, Deloitte LLPGregory Bean, Director, Deloitte Consulting LLP Andrew Slaughter, Executive Director, Deloitte Services LP

August 20, 2015

Copyright © 2015 Deloitte Development LLC. All rights reserved.2

Agenda

Information flow and Internet of Things (IoT)

Linking with business priorities

Perspectives by oil and gas segments

Next steps

Summing up

Q&A


IoT: Creating differentiated value from information• It is not merely the features of a product

or service, information about that product or service creates differentiated value for companies.

• Creating information is enabled by a suite of technologies that basically integrates sensing, communications, and analytics capabilities, typically referred as the “Internet of Things.”*

• Companies that control the flow of information, and complete the Information Value Loop for modifying future action, enjoy competitive advantage.

Information value loop

*The Internet of Things (IoT) is a suite of technologies and associated business processes that allows us to track and count, observe and identify, and evaluate and act in circumstances heretofore effectively invisible and beyond reach.

Source: Michael E. Raynor and Mark J. Cotteleer, The more things change: Value creation, value capture, and the Internet of Things, Deloitte Review 17, Deloitte University Press

4 Copyright © 2015 Deloitte Development LLC. All rights reserved.

Cheaper, smarter, and smaller sensors/devices

Higher network speed and lower data transfer cost

Lower data storage costs

Faster data processing and lower computing cost

The price of typical sensors has fallen from above $20 in 1994 to 40 cents in 2014.

In 2003, it cost about $120 to transfer 1 Mbps, now it costs about 63 cents.

Storing a gigabyte now costs 3 cents, compared to $569 in 1992.

The cost of computing power has fallen from $222 per million transistors in 1992 to about $0.06 per million transistors in 2012

What has led to the growth in information?

Source: John Hagel et al, From exponential technologies to exponential innovation, Deloitte University Press

http://dupress.com/articles/from-exponential-technologies-to-exponential-innovation/


Poll question # 1

Relative to other industries, what do you think is the digital maturity of the oil and gas industry?

• High• Medium• Low• Not digitized at all


Linking IoT with business prioritiesIoT deployments should address specific business priorities, which can be classified into three: improving reliability, optimizing operations, and creating new value.

• Lower oil prices drive upstream firms to place higher business priority on optimization where IoT applications are relatively immature.

• Increase in business complexity drives midstream players to advance commercial opportunities, along with improving pipeline safety and reliability.

• Slowing demand growth, rising competition, and volatile feedstock market pressure downstream players to explore new areas of optimization and value creation.


Upstream: Aggregating diverse data-sets

Rising technical and operational

complexity

• Companies developing subsea systems that operate at 20,000 psi and withstand temperatures of up to 350F.

• Firms increasing downhole intensity and above-ground activity in shales, and moving to hostile/remote locations.

Bulk data generated by smart sensors capturing

this complexity

• The growing scale and frequency of hydrocarbon reservoirs data has led to data explosion.

• Internal data generated by large integrated firms now exceeds 1.5 terabytes a day.1

Lack of standards choking

information flow

• The need to expand the scope of data (data independent of scientific principles and cross-disciplinary) is restricted by industries’ weak data-management capabilities.

• Lack of open standards to integrate diverse data create the bottleneck at the aggregation stage of the value loop.

1. Abdelkader Baaziz and Luc Quoniam, “How to use Big Data technologies to optimize operations in Upstream Petroleum Industry,” 21st World Petroleum Congress, June 19, 2014.


Poll question # 2

In which upstream sub-segment will the IoT create the maximum impact?

• Exploration• Drilling & Completion• Production


Upstream: Creating new valueIf common data standards are able to integrate diverse data sets, companies can gain insights into previously disconnected aspects of operations and adjust how they make decisions.

Case study: Apache, in collaboration with an analytics software firm, not only improved the performance of its electrical submersible pumps (ESPs) but also predicted a field’s production capacity in three steps1:

The pump failure data generated in Step 1 was used to prescribe right pump configuration for the next well.

The companies used multi-disciplinary data about pumps, production, completion, and subsurface characteristics to predict the pump failure with prescriptions to avoid future failures.

The ESP performance and configuration data generated in Step 2 was used to evaluate field’s potential production capacity before acquiring them.

Step 1: Predict pump failure

Step 2: Prescribe optimal pump configuration

Step 3: Predict

production capacity

1. Ayata, “Customer Profile: Apache Corporation,” September 05, 2013


Midstream: Building a data-enabled infrastructure

• US midstream has seen a shift from a simple business model of transporting limited grades of products to a complex and dynamic model of transporting variable volumes/grades from multiple locations.

• Rising business complexity, combined with aging pipeline network and legacy control devices, creates reliability issues. Annual losses touch $10 billion due to fuel leaks and thefts.1

• What is needed is a shift towards building a data-enabled infrastructure, in other words, getting started on the informational value loop by investing in sensors that create data.

1. Penn Energy, “The Role of satellites in oil and gas pipeline monitoring for leak & theft detection,” May 30, 2014


Midstream: Sensorizing the networkSelect players are addressing this bottleneck by creating data through advanced sensors that accurately identifies and measures dents, cracks, spills, corrosion, etc.

Case study: TransCanada and Enbridge are testing four technologies that essentially see, feel, smell, and hear various aspects of their oil pipelines.

1. Vapor-sensing tubes that “see” bitumen spilled by shooting air down a tube.

2. A fiber-optic distributed temperature sensing system that “feels” fluctuations in temperature caused by bitumen leaking into ambient soil.

3. Hydrocarbon sensing cables that sends electric signals to “smell” hydrocarbons.

4. Fiber-optic distributed acoustic sensing system that “hears” sound variations and can indicate a pipeline leak.

Sensor cables that TransCanada is testing in an industry partnership with Enbridge and the Governments of Alberta and Canada

Hydrocarbon sensing cable’s electrical impedance will change when it gets in contact with oil.

Vapor sensing tube can report volatile organic compound (VOC) to terminal hydrocarbon vapor sensor.

Fiber optic cable used for either distributed temperature sensing (DTS) or distributed acoustic sensing (DAS).


Midstream: Analyzing data all along the network A company would likely accrue a larger competitive and commercial advantage if it analyzes product and flow data more comprehensively all along its network.

Indicative examples:

• Leveraging data across the company’s network to help shippers find the best paths to market, charging them differently for having route optionality in contracts.

• Forecasting algorithms on historic volumes transported can reveal ways in which the company might use pricing incentives that induce producers and end users to smooth volumes.

• Similarly, a real-time analysis of changing volumes across the company’s network of shale plays can alert it to new price differentials.


Poll question # 3

Which oil and gas segment has traditionally had the most sophisticated data infrastructure with more established data processes and a longer history of automation and optimization?

• Upstream• Oilfield services• Midstream• Downstream


Downstream: Taking intelligence beyond asset level• Unscheduled shutdowns and

ineffective maintenance practices remain a big concern for refiners—US alone witnessed 2,200 unplanned shutdowns between 2009 and 2013.1

• Condition-based predictive maintenance solutions at an asset or plant level have already started to make inroads. What is needed is new areas of competitive differentiation and revenue generation outside the refinery limits.

• This calls for analysis of data across the system (including pre- and post- links in logistics & distribution) and, moreover, across the ecosystem (adding external variables such as consumer profile and behavior, etc.)

1. Hydrocarbon Publishing Company, “Refinery Power Outage Mitigations,” 2014


Case Study: A US refiner integrated the logistics of oil movement data with the information from pervasive sensors deployed on refining equipment.1

• The refiner wanted to properly value its future crude purchases, especially crude available on the spot market where time was key.

• It had limited data on future operating & maintenance costs for various crudes it processes and buys.

• The refiner installed pervasive sensors on refinery equipment, which allowed it to gather data on the impact of processing various crudes.

• Collected and analyzed data from sensors was then integrated with market data on crudes [cargo availability, price, grade, etc.] on a central hub.

• This information helped the refiner to effectively bid for its future crude cargoes in a timely manner.

Downstream: Integrating information at system level

1. Discussions with Emerson Electric Co.


Downstream: Building connected enterprise

Indicative example: Refiners can target new age customers by using innovation in smart handheld devices and advanced telematics system in vehicles, like the one developed by Toyota with SAP and Verifone to simplify drivers fueling experience. [1]

Refiners send customized offers via telematics to customers and add more appeal to their traditional loyalty and reward programs.

Refiners enroll in such connected-car prototypes which direct customers to the nearest enrolled fuel retail outlet by analyzing distance and fuel levels.

Refiners gain more visibility into consumer behaviors by mashing up existing petro-cards data with the data collected by cloud-enabled emerging telematics solutions across vendors.

[1] SAP, “SAP, Toyota InfoTechnology Center and VeriFone Connect Cars and Provide Drivers With Simplified Fueling,” July 01, 2014

Step 1: Getting customers to nearest outlet

Step 2: Pushing offers to build loyalty

Step 3: Analyzing

consumer profiles


Companies need to closely monitor IoT deployments and regularly ask and answer questions such as:

• Is the IoT creating the necessary momentum and learning across the businesses and employees?

• What are the future costs and complexities associated with retrofitting and interoperability of applications?

• What are the security shortcomings in light of new developments?

Companies need to have a long term goal of taking intelligence to a new level. For example, goals of:

• Taking the intelligence from the fuels to a “molecule” level.

• Extending IoT’s reach from cost optimization to capital efficiency and mega-project management.

• Exploring business models that enable new information value chains and promoting information convergence across the enterprise.

Next Steps

Near term Long term


Poll question # 4

Which business approach would have lower time-to-commercialization and realize higher IoT benefits?

• Proprietary/self development• Collaborative/shared development • Not sure


Summing upCreating and capturing value from IoT requires identifying primary business objectives, ascertaining new sources of information, and clearing bottlenecks that limit the flow of information.

Oil and gas segment

Top business objective

Dominant value drivers Bottleneck Potential

solution

Upstream Optimization Scope and latency Aggregate Standards

Midstream Reliability Scale, accuracy, and timeliness Create Sensors

Downstream New value creation

Scope, timeliness, and security Act Ecosystem

management

Table 1. Analysis of IoT value by oil and gas segment

For more information about IoT in the oil and gas industry, see our latest report Connected barrels: Transforming oil and gas strategies with the Internet of Things.

http://dupress.com/articles/internet-of-things-iot-in-oil-and-gas-industry/



Copyright © 2015 Deloitte Development LLC. All rights reserved.

Contact info

John EnglandVice Chairman, US Oil and Gas LeaderDeloitte [email protected] Connect with me on LinkedIn @JohnWEngland

Gregory BeanDirectorDeloitte Consulting [email protected]

Andrew SlaughterExecutive Director, Deloitte Center for Energy SolutionsDeloitte Services [email protected]

Connect with me on LinkedIn

mailto:[email protected]



https://www.linkedin.com/pub/john-england/4/253/744

https://www.linkedin.com/in/slaughterandrew

https://twitter.com/JohnWEngland?lang=en

Copyright © 2015 Deloitte Development LLC. All rights reserved.

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