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The Dbriefs Oil & Gas series
presents:
The Internet of Things
A new analytical
framework for addressing
industry challenges
John England, Vice Chairman, US Oil and
Gas Leader, Deloitte LLP
Gregory 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

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 priorities
IoT 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 value
If 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 network
Select 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 up
Creating 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.

Copyright © 2015 Deloitte Development LLC. All rights reserved.
Contact info
John England
Vice Chairman, US Oil and Gas Leader
Deloitte LLP
jengland@deloitte.com
Connect with me on LinkedIn
@JohnWEngland
Gregory Bean
Director
Deloitte Consulting LLP
gbean@deloitte.com
Andrew Slaughter
Executive Director, Deloitte Center for Energy Solutions
Deloitte Services LP
anslaughter@deloitte.com
Connect with me on LinkedIn

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