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Solutions for 3D Asset Integrity Management Augmenting Business Performance with Asset Virtualization
Issue 1
In this issue
Introduction 2
Product Highlights 3
Research for Gartner: Predicts 2016: Upstream Oil and Gas 6
Intelligent 3D Models 16
About Us 18
2
One of the biggest challenges faced by companies operating in hazardous environments such as refining, oil and
gas, and other industrial settings is the administration of aging assets and related infrastructure. Moreover, the
lack of awareness among organizations about the status, deployment, and utilization of the same assets is a
major hurdle to an organization. Effective Asset Management and Asset Integrity Management systems will help
augment the value of assets, improve reliability, decrease wrench time, and reduce down time.
INOVX’s value proposition includes higher asset productivity, reduced maintenance costs, and increased visibility
of the operations and asset performance – all of which lead to enhanced situational awareness and certainty
regarding all information about assets.
Introduction
3
Product Highlights
INOVX provides a platform and solutions for 3D Asset
Integrity Management to companies in the process
industry worldwide. INOVX accomplishes this through
its latest game-changing software platform V-Suite®.
V-Suite is the 3D Asset Integrity Management platform
that is unique in its ability to integrate operational
management of both Inspection and Maintenance
processes with accurate and complete active 3D
models of enterprise assets. V-Suite is an active 3D
platform that allows users to navigate their entire
operational facility and interoperate with supporting
data from multiple enterprise systems. The V-Suite
search engine allows users to navigate to, and view
in detail any asset and automatically associate
data that can provide intelligence with regard to
asset performance, location and access points,
interconnected dependencies, realtime isometric
preparation, integrated P&ID, shut down & start up
procedures, asset performance history, work orders,
inventory etc.
V-Suite is designed to interoperate with all of the
major business applications that add value to
inspection and maintenance business execution,
represented through an active 3D operational model
of the entire plant. The active 3D model answers
fundamental questions: What is the Asset?, Where
is the Asset?, How is the Asset performing?, What
needs to be done to maintain optimum performance?
The solution then allows users to engage with assets
in the manner they choose, whether at their desk in
the engineering office, as a field inspector utilizing
a notebook or tablet, or as a maintenance engineer
using a combination of media from paper, to android
or mobile device of choice.
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Mobile device access is the next wave of doing
business and INOVX is at the forefront of providing
its clients with immediate access to data. With the
release of V-Suite in July 2016, INOVX moved that
functionality into the cloud and onto the mobile
device of choice. Rather than print out an Inspection
routine with 2D isometrics, asset history, shut down
procedures etc. onto hundreds of pages of paper,
users can use V-Suite Knowledge Books which are
created for online access via a browser, or mobile
devices, or packaged onto a portable file to a mobile
device for offline use where there is no network
connectivity.
The web-based solution includes V-Suite Core,
V-Inspection, V-Maintenance, and V-Engineer. The
V-Suite Core is at the center of V-Suite and its object
oriented database is interoperable, customizable,
and extensible. The intuitive 3D interface allows
end users to access plant information for decision
support, work planning, execution, and analysis with
exceptional reliability and efficiency. V-Inspection is
the end user application that brings the power of a 3D
Plant model into the hands of the Inspection Engineer.
V-Maintenance brings planned maintenance, exception
maintenance and emergency maintenance together in
one application. Using the Engineer’s mobile device
of choice, maintenance routines can be optimized
to continually survey asset points close to point of
operation. Additionally, the V-Engineer brings the value
of Artificial Intelligence to the Asset Integrity team.
V-Suite’s web-based and mobile device deployment
proves to add significant additional value by
presenting asset information and specific end-user
application in support of organizational needs in ways
not otherwise possible. This is further enhanced by
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integration with existing EAM systems already in place
within the enterprise. In preparation of inspection
routines alone, companies measured 40% productivity
gains, greater accuracy of observation uploads, and
seamless data uploads and interoperativity.
The use of a 3D model in the operation of an
industrial plant is growing exponentially. The majority
of 3D tools currently available have been created for
the exclusive use of design engineers, and as such
were designed to be passive in their nature and end-
user viewing only. The first days after a plant handover
or the plant goes live, changes made to the plant
rendering a passive 3D model will be immediately
out of date and quite possibly a danger to the user.
INOVX has always built an active 3D Model specifically
designed for the end-user operator. The model
Management of Change (MoC) provides the tools for
the operator to reflect change requests within the
model itself and allow integrated workflow to route
any change request for approval. This can rapidly
improve the status of the model to always be current.
Changes within an active 3D model can take minutes,
and without users be forced offline while changes are
made. And so V-Suite delivers a 24/7 active model,
always current, and interoperating realtime with all
associated data sources.
3D has been the domain of the Design Engineer
for over 20 years now, and despite operational
management seeing use in applying the technology
into plant operations, 3D has largely been passive and
Design Engineer focused. The advent of the INOVX
active 3D Model with its V-Suite platform is based on
relational database technology, designed specifically
for plant operation management, rich in end user
functionality, and now with full mobility creates the
first enterprise wide deployable solution of active 3D
for plant operations.
Source: INOVX Solutions
6
Low market prices are keeping the pressure on oil and
gas executives to improve business performance via
digital technologies and data-driven optimization. In
the coming years, business operations will continue to
transform, altering the business expectations of CIOs.
Key Findings
■ New digital technologies such as 3D asset
visualization are creating new value from old
assets in legacy oil fields.
■ Advanced digital technologies such as algorithmic
drilling and completion are giving oil and gas
companies new capabilities to improve operations
and reduce the cost structure of new assets.
■ IT leaders are being challenged to resolve
traditional barriers to data-driven optimization,
such as information management.
■ As IT becomes more engaged with the
digitalization of operations, CIOs are turning to
bimodal IT as a means to enable agile and creative
innovation, while maintaining efficient and reliable
IT services.
■ CIOs are adopting agile and adaptable planning
methods to create IT plans capable of addressing
the uncertain and volatile environment present in
upstream companies.
Research From Gartner
Predicts 2016: Upstream Oil and Gas
7
Recommendations
Oil and gas CIOs should:
■ Promote adoption of new technologies such as 3D
asset visualization, and algorithmic drilling and
completion to improve business performance and
reduce operational risk.
■ Take accountability for reducing the barriers to digital
innovation, particularly, the problem of information
incompatibility across organizational silos.
■ Adopt new IT management practices such as
bimodal IT and scenario planning to foster creative
innovation and maintain business relevance as
volatile market conditions shift business priorities.
Strategic Planning Assumptions
■ By 2020, 40% of field assets will be monitored and
managed by interactions with virtual 3D models.
■ By 2020, more than 50% of wellbore drilling
activities on electric rigs will be controlled primarily
by algorithm and secondarily by human expertise.
■ By 2020, 50% of upstream oil and gas CIOs
will be accountable for integrating information
management across IT, operational technology
(OT) and upstream-modeling domains.
■ By 2018, more than half of upstream oil and gas
companies will expect digital innovation from IT,
forcing CIOs to create bimodal IT organizations.
■ By 2020, 30% of upstream CIOs will adopt
scenario planning methodology to guide digital
innovation and future-proof their companies
against market volatility.
Analysis
What You Need to Know
Nearly all upstream companies have already seen the
impact of digitalization in reducing their operating costs,
increasing ultimate recovery rates, accelerating the pace
of their business and improving safety performance. Use
of data to drive optimization of business performance
will continue to grow in scope and sophistication. As
competition intensifies in global oil and gas markets,
driving forces such as expansion of digital oil field
scope, increased advanced analytic capabilities, broader
integration of planning and operations, and digitalization
of work streams are transforming operating practices in
upstream companies.
The role of the CIO and the IT organization will
increasingly be to initiate change, foster relationships
and change the culture of the organization. As more
companies elevate data-driven optimization to a top
business priority, the skills of IT talent will have to
expand to increase their influence and leadership
effectiveness. At the same time, upstream CIOs
remain under pressure to deliver basic IT services
more efficiently. However, the need to reduce overall
IT costs now must be balanced with the need to
advance digitalization priorities. Upstream CIOs will
need to take a stronger leadership role in introducing
new technologies such as 3D asset visualization, and
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algorithmic drilling and completions. In addition, they
must take greater accountability for overcoming the
barriers to digital business transformation, such as
weak and fragmented information management. And,
at the same time, they must refresh IT management
practices by introducing new capabilities such as
bimodal innovation and scenario planning.
Strategic Planning Assumptions
Strategic Planning Assumption: By 2020, 40%
of field assets will be monitored and managed by
interactions with virtual 3D models.
Analysis by: Leif Eriksen, Morgan Eldred
Key Findings:
■ The technology necessary to create virtual 3D models
of physical assets and infrastructure, and connect the
models to related data is rapidly maturing.
■ During the past five years, the cost to create
intelligent 3D models of infrastructure has
dropped by more than 50%, lowering the financial
barriers to adoption.
■ 3D models are becoming “digital twins” of
physical assets and delivering multiple benefits,
including better and more cost-effective training,
improved equipment reliability, and reduced
operational risks.
■ The challenges organizations face in adopting
and realizing the value of using virtual 3D models
include the costs of deployment (lower, but still
high), lack of quality data about assets and
infrastructure, and change management.
Market Implications:
3D virtualization technology is on the cusp of
transforming how upstream oil and gas companies
visualize and interact with their physical assets, such
as pipelines, compressors and rigs. Creating and using
intelligent 3D virtual models of facilities – sometimes
referred to as digital twins – is already a reality and is
having an impact on other industries such as refining,
petrochemicals and utilities. It is changing the way
decisions are made, how personnel are trained and
the degree to which field personnel are exposed
to unnecessary risks. It will eventually lead to an
immersive approach to data visualization, training and
decision making.
The upstream oil and gas industry stands to benefit at
least as much, if not more, from the use of intelligent
3D models than other asset-centric industries. A
high level of personnel turnover puts an emphasis on
effective training and a highly visual way of interacting
with data. In addition, the risks that personnel face
when they are in the field can be substantial and favors
virtual, as opposed to direct, interaction with assets.
Use of intelligent 3D models by the upstream oil and
gas sector stands to mitigate these risks, reduce
unplanned downtime and improve safety performance.
There are still significant barriers to adoption of
intelligent 3D models, and these barriers could stand
in the way of rapid adoption. The most significant
barrier may end up being persistently low oil prices,
which could put a damper on technology investments
by the industry. Another key challenge is the lack
of data and/or poor quality data. Older assets are
lightly instrumented, and the costs to retrofit them
(including deploying the necessary communications
9
infrastructure) could limit the value of any investments
made in 3D technology. And, as with the adoption
of any transformational technology, there could
be resistance from segments of the workforce
uncomfortable with change.
Working in favor of more rapid adoption are the
ongoing and rapid technological innovations in both
the core 3D modeling technology and supporting
technologies such as cloud and the Internet of Things
(IoT). For instance, during the past five years, the cost
to create intelligent 3D models of infrastructure has
dropped by more than 50%, lowering the financial
barriers to adoption. In addition, IoT-driven advances
in sensor technology are opening the door to more and
better data on the status and condition of assets. And
in the next five years, better field connectivity, more
powerful mobile form factors and cloud technology will
lead to increasing use of 3D models as the primary
mechanism for viewing asset data anywhere, anytime.
Recommendations:
■ Invest in the technology necessary to create
intelligent 3D models of their existing physical
assets and infrastructure.
■ Develop plans to expand adoption of related
technologies such as the IoT and mobile to
increase edge awareness and to enable better data
capture and visualization.
Strategic Planning Assumption: By 2020, more than
50% of wellbore drilling activities on electric rigs will
be controlled primarily by algorithm and secondarily
by human expertise.
Analysis by: Rich McAvey
Key Findings:
■ Operational automation in other industries has
well-established the benefit of using algorithms to
control and optimize operational activities.
■ Drilling rigs and completion equipment in
the oil and gas industry have become heavily
instrumented, enabling very accurate modeling
and simulation.
■ Most motors, pumps and field equipment are
already digitally controlled. These control systems
are being integrated, enabling effective real-time
control of rigs.
Market Implications:
Data from heavily instrumented drilling rigs and
completion equipment, in combination with asset,
transactional, financial and engineering data,
is enabling the oil and gas companies to build
very accurate models that reliably predict future
performance. In addition, digital controllers are
increasingly controlling all the motors, pumps and
other operating elements of the rig. This control has
improved reliability of the components, but is also
enabling oil and gas companies to optimize every
rig’s performance in near real time. Consequently,
as in other industries, these capabilities are
combining together to enable algorithmic drilling and
completions.1
The new capabilities that algorithmic drilling and
completions enable will unlock substantial business
and engineering performance improvements, such as
optimized rates of penetration, consistent hole quality,
lower cost of completions and reduced operating risk.
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Benefits also go further than completing an individual
well. Algorithmic drilling and completions will
provide oil and gas companies with a wider and more
diverse portfolio of engineering options for exploiting
reservoirs during their entire life cycle. This means
higher production rates, greater ultimate recover
factors and superior economic performance from new
and existing oil fields.
Algorithmic drilling will continue to expand in scope
and scale until rigs are primarily controlled by
optimization algorithms. In this regard, drilling and
completion automation is following in the footsteps
of other industries, such as aviation (autopilot),
automotive (self-driving cars), power generation
(automated power dispatching) and space exploration
(Mars rover). In all these cases, algorithmic
optimization of operations has resulted in higher
levels of performance. Algorithmic control allows for
repetition to occur without suffering from boredom or
lapses in attention that its human counterparts are
capable of doing. Oil and gas executives are looking to
replicate the technological success of other industries
by making drill bits (and completion equipment)
more intelligent and able to respond instantly to any
conditions they may encounter.
More than optimized business performance is at
stake. With the help of autonomous computer-
controlled drilling operations, oil and gas operators
are developing new ways of mitigating risk and
improving safety performance. Drilling and completion
work mixes rig teams with heavy machinery operating
in tight spaces and often under extreme weather
conditions, which means it is inherently risky. Oil and
gas executives rightly ask, “Why not let machines do
the hazardous work?”
As algorithmic drilling and completions become
more mainstream, the industry will see significant
transformations. The value of drilling/completion
expertise will shift from humans to algorithms. Joint
ventures will seek partners with proven analytic
superiority, resulting in higher growth rates for
companies that can successfully create superior
algorithmic drilling and completions. In turn,
operating companies will want to have stronger control
over the information generated from rigs, as well as
real-time control over their operations (at least within
safety guardrails). Traditional drilling and completion
contractors will be forced to disaggregate drilling and
completion services that are heavily bundled today.
Recommendations:
■ Anticipate a shift of real-time control of drilling
and completion activities from oil field service
companies to company-provided algorithms,
and assess the implications for IT systems and
infrastructure.
■ Begin establishing appropriate governance and
technical architecture to manage algorithm design
and development, as well as operational risks.
11
Strategic Planning Assumption: By 2020, 50% of
upstream oil and gas CIOs will be accountable for
integrating information management across IT, OT and
upstream-modeling domains.
Analysis by: Morgan Eldred
Key Findings:
■ Upstream oil and gas firms are increasingly
looking to integrate subsurface and surface data
across domains to enable better business and
asset planning.
■ Most upstream oil and gas companies have
multiple teams responsible for information
management and have a need for more integrated
information governance.
Market Implications:
Overall, upstream oil companies have yet to find
much common ground on how to best manage the
wide range of data types and sources needed to
deliver on the promise of data-driven optimization.
Most have numerous functional teams that focus on a
compartmentalized area of the value chain, such as
subsurface data management, drilling and day-to-day
production operations, with each team choosing the
required applications and managing the associated
data. The end result is siloed information stores and
an inability to optimize asset operations.
CIOs in some leading firms have stepped up and taken
responsibility for information management across
the entire upstream value chain. These firms have
higher capability toward business intelligence, big
data analytics, upstream modelling and production
management. Alternatively, some firms have created
separate teams outside of IT solely responsible for
integration and data management. However, this
is the minority, and many of these firms are still
challenged, as IT is still required to contribute toward
the architecture and system management. Where
firms have taken these actions, the expectation is
to pass the overall responsibility of integration and
information management to IT in the longer term.
Challenges will exist initially when CIOs take on this
initiative, as the payback will take a long time to
materialize, and the change management will be
difficult. And while low oil prices are putting pressure
on IT budgets, they also create an opportunity for
system rationalization and a more integrated approach
to information management. CIOs willing to take the
lead will likely find some resistance, but ultimately, will
be positioned to deliver on the promise of data-driven
optimization of business performance and the digital
oil field.
Recommendations:
■ Broaden the CIO role to include OT data
management and establish information governance
across the entire enterprise, with a focus on
enabling business value creation from digital oil
field data management and analysis.
■ Create an enterprise information architecture
that incorporates all data, inclusive of all OT
data, including production, geoscience and
engineering data.
12
Strategic Planning Assumption: By 2018, more than
half of upstream oil and gas companies will expect
digital innovation from IT, forcing CIOs to create
bimodal IT organizations.
Analysis by: Rich McAvey
Key Findings:
■ Low and volatile oil prices have led many oil and
gas companies to make data-driven optimization
a top priority to drive business efficiency,
productivity and agility.
■ Traditional IT management practices, which excel
at creating stable, reliable and efficient services
and systems, have proved to also be inhibiters to
emergent innovation processes (for example, IT as
the department of “no”).
■ IT organizations that operate in only one traditional
mode of IT are ill-equipped to support data-driven
optimization. Consequently, CIOs are adopting a
bimodal approach: One mode is focused on reliable
and efficient delivery of traditional IT services (Mode
1), and the other on innovation, agility and business
transformation (Mode 2).
Market Implications:
At many (but not all) oil and gas companies, the
traditional view of IT has been as an essential,
but commodity, function that supports core
business activities (such as exploration, drilling and
production), but does not contribute directly to them.
In recent years, the impact of digital technologies and
data-driven optimization has been well-documented
as they have brought substantial volumes of new oil
supplies to the market at low cost. Consequently,
many oil and gas companies have changed their view
of IT, and now expect IT to be stronger contributors
in using digital technologies to increase business
performance through innovation.
To contribute to digital innovation, IT will need
different talent. Traditional IT leaders have careers,
experience sets and capabilities oriented around
reliable delivery of IT functional workflows (application
development, infrastructure, requirements definition,
waterfall project management, vendor performance
management and functional budgeting, for example).
As oil and gas CIOs began taking on greater
responsibilities for data-driven optimization, it has
become clear that IT leaders with new experience sets
and capabilities are required. IT now needs talent
that understands current business operations and
the potential impacts of digital technologies, and can
identify and develop transformational initiatives that
elevate business performance.
In addition, IT management and operating practices
will need to change to support digital innovation.
Traditional IT processes have been developed to
deliver two things: stable and efficient IT services
(such as provisioning a laptop or maintaining a third-
party application) and on-time/on-budget delivery
of predefined IT projects (such as standing up a new
application or providing infrastructure to a new field
office). However, creative innovation work follows
processes that are agile, emergent and ad hoc, which
are characteristics that traditional IT processes
are designed to stamp out. CIOs must augment IT
processes with new ones that enable collaborative and
emergent development of creative solutions by fluid
teams of talent from multiple entities.
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To support innovation, IT will also need to consider
new technology architectures. The traditional approach
to technology architecture in oil and gas companies,
particularly, the larger ones, has been to organize
them in multiple portfolios associated with business
assets/regions (such as Gulf of Mexico versus
North Sea versus corporate functions), engineering
functions (such as reliability, drilling or production
operations) or by major capital project (such as a
multibillion dollar gas project in Northwest Australia).
This has produced a fragmented and siloed technical
architecture that greatly inhibits digital innovation.
Companies seeking to be more agile and adaptable
are migrating to enterprise architectures based on
the pace-layering model. This model reorganizes
technology portfolios into three groups – systems
of record, systems of differentiation and systems of
innovation – enabling each to be optimized for their
desired business outcomes.
Oil and gas CIOs who want their departments to be
agile, to handle uncertainty and to be more flexible,
while maintaining their capacity to handle day-to-day
service delivery and system management pressures
are turning to a bimodal approach for IT. Bimodal IT
overcomes the inertia of the status quo and helps
organizations develop speed and agility to meet digital
challenges. Bimodal IT is the practice of managing
two separate, coherent modes of IT: One is focused
on stability, predictability and efficiency (Mode 1),
and the other focused on transformation, innovation
and agility (Mode 2). Each mode has all the people,
resources, partners, structure, culture, methodologies,
governance, metrics and attitudes toward value and
risk that its operation requires.
Recommendations:
■ Establish a small, but diverse, IT team to organize
and drive digital innovation.
■ Create a strategy for bimodal IT, including
a vision, an organizational change plan and
a communications plan. Ensure that the
communications plan explains how bimodal IT
will lead to data-driven optimization of business
performance.
■ Sponsor agile digital innovation projects, but
do not mix modes within the same IT team.
Keep Mode 1 teams focused and accountable
for delivering stable, predictable and reliable IT
services. Keep Mode 2 teams focused on digital
business transformation, innovation and agility.
Strategic Planning Assumption: By 2020, 30%
of upstream CIOs will adopt scenario planning
methodology to guide digital innovation and future-
proof their companies against market volatility.
Analysis by: Rich McAvey
Key Findings:
■ IT planning in the oil and gas industry is typically
based on annual, rigid, single-point forecasting
methodologies, and produces plans that can
quickly become irrelevant.
■ Volatile hydrocarbon markets have introduced
substantial volatility among business priorities and
timing for IT projects.
14
Market Implications:
In the fourth quarter of 2014, as crude oil prices began
a rapid decline of roughly 50%, the IT plans of most
upstream companies were disrupted by changes in
market conditions. Why? Because IT planning in the
oil and gas industry is typically based on annual, rigid,
single-point forecasting methodologies, and produces
service roadmaps and project plans that can quickly
become inappropriate when conditions change. It is
important to note that in 2014, IT plans did not adapt
or adjust; for the most part, they simply failed as oil
prices slipped below $80 per barrel. The events of 2014
revealed the fragility of traditional IT planning methods.
Oil market volatility makes the future business
environment for oil and gas companies uncertain,
which, in turn, makes IT planning difficult. Oil markets
are impacted by unpredictable forces such as short-
term supply/demand imbalances, access to quality
reserves for future investment, the cost of capital,
shifting global politics (which often is generated
directly by trade balances due to oil and gas),
development of new petroleum technologies (such as
fracking, which has made the North American shales
economically viable) and alternative energy sources
(such as the penetration rate for electric cars). While
some business priorities (such as safety, economic
performance and risk management) remain stable,
most business priorities shift when market conditions
change.
Dynamic oil and gas markets are not the only source
of volatility that upstream oil and gas CIOs must
contend with. During the last several years, the
number of innovative oil and gas companies has
been growing. These companies have realized the
substantial business impact that digital technologies
are having on field productivity and business
performance among a wide variety of oil and gas
companies. The situation became very transparent in
late 2014. There was wide industry expectation that
the U.S. shale oil producers would be choked out if
oil prices dropped below $75 per barrel. Prices did
go lower than that, into the $50 and $40 range, and
yet, shale operations remained strong. This was a very
public testament to the efficacy of digital technologies
and data-driven optimization to reduce the break-
even cost of operations in oil and gas companies.
In retrospect, it became clear that digital innovators
had achieved this progress by prioritizing investments
in field sensors, analytics, integrated planning/
operations and digitally connected workers.
Volatility is making it hard to move forward. Business
and IT executives in the oil and gas industry are
struggling to formulate plans that are sufficiently
agile and adaptable for a future as uncertain as the
current environment. Plans should empower and align
leaders when there are choices by helping them focus
on appropriate business objectives and priorities. At
the same time, plans should also empower individuals
to make the right decision as business conditions
change. This is possible only if the plan is relevant,
easy to understand and easy to communicate.
Scenario planning is a strategic planning method
noted for its ability to make agile and adaptable long-
term plans, especially for complex military, social
and business environments. It can help business
executives and IT planners anticipate and prepare for
longer-term, uncertain future market conditions and
their implications. Within the oil and gas industry,
scenario-based planning was developed at Royal Dutch
15
Shell in the 1970s, and gained popularity due to its
anticipation of the significant drop in oil prices in
1986. Scenario planning initiatives create multiple
scenarios to describe potential future environments.
These scenarios are important constructs of the
scenario planning process as they bring focus
to the implications of critical uncertainties, and
make it possible to derive logical and coherent
implications that, in turn, enable leaders to assess the
consequences of future business decisions. However,
the decision-making processes that follow scenario
development are just as important as development
of the scenarios. Typically, scenario planners spend
as much time on the decision-making process as on
creating the scenarios themselves.
Recommendations:
■ Define the dimensions of uncertainty that can alter
IT plans due to changes in hydrocarbon markets,
digital technologies and business conditions. Focus
on dimensions that are directly relevant to IT such
as oil-market outlook (which affects the scale of
IT investment) and innovation philosophy (which
affects IT priorities and resources).
■ Shift to a more agile and adaptable planning
methodology, such as scenario planning, to
develop IT plans that can anticipate, accommodate
and adjust to changes in priorities and timing.
A Look Back
This topic area is too new to have on-target or missed
predictions.
Source: Gartner Research Note G00279658, Rich McAvey, Leif Eriksen, Morgan Eldred, 19 November 2015
16
Analysis By: Morgan Eldred
Definition: Intelligent 3D models are virtual
3D models that allow projects, operations and
maintenance personnel to visualize assets and
associated data for the purposes of engineering
collaboration, inspections, maintenance,
troubleshooting and training. They can be built on
existing 3D models (originally created during the
design/build process) or created from scratch using
laser imaging technology.
Position and Adoption Speed Justification: Until
recently, the technology to effectively and efficiently
create and manage 3D models of existing physical
infrastructure and assets has been limited. In
addition, the technology for linking data from other
systems – including enterprise asset management
(EAM) systems and equipment databases – to the
3D models has been challenging to put in place and
maintain. But today, 3D laser scanning technology
can deliver accurate as-is models of critical
infrastructure within weeks. The tools for linking the
models to other data sources have become easier to
use and maintain.
The past five years have seen significant progress;
however, there is still a good deal of hype from the
vendors, and legacy technology investments can
still be a barrier to progress. The next 10 years will
see even more progress in using 3D models for
managing operational assets, including an
Intelligent 3D Models
17
expansion in vendor options, a reduction in the cost of
deploying and maintaining the models, and the use of
the models on mobile devices. These models also can
be used to converge the handover of information from
projects to operations.
User Advice: CIOs and IT leaders should work with
the business to create and maintain as-is 3D models
of critical infrastructure. They should support the
process of making the 3D models intelligent by
linking to data from back-end systems, including
maintenance systems and various sources of
condition and operating data. 3D models alone can be
useful for training and troubleshooting purposes, but
the greater value comes from making the 3D models
intelligent. Linking the 3D models to information about
the underlying components or objects allows users to
drill down and find information such as engineering
information, inspection history, maintenance history
and even part numbers. The 3D model in this
scenario becomes the primary tool for accessing
asset information, making decisions and managing
operational risk.
If you already have 3D models of your infrastructure
and assets, start your investigation there. However, be
wary of using legacy technology that might complicate
and increase the cost of keeping the model current,
creating the links to other systems, and maintaining
the resulting system. There are more examples of
failed projects in this area than successful ones. Once
the foundation is in place, consider extending the use
of the 3D models to the field. This should start with
pilot projects to make the 3D models and associated
data accessible on mobile devices – tablets will be the
most feasible approach. Some vendors are beginning
to support this capability, but it will be a few years
before it is considered a core part of the product’s
functionality.
Business Impact: Asset-intensive organizations are
under immense pressure to improve reliability and
reduce operational risk. The use of 3D models for
engineering, managing and maintaining operational
assets helps reduce costs and mitigate risk,
particularly as it relates to remote or inaccessible
assets. The use of 3D models will also become a
cornerstone of digital worker enablement. Information
will be as readily available in the field as it is in the
home office, and it will be tied to virtual views of the
physical assets.
Benefit Rating: High
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Sample Vendors: Autodesk; Aveva; Bentley Systems;
Dassault Systèmes; Intergraph; INOVX; Siemens
Recommended Reading: “Top 10 Trends That Affect Oil
and Gas CIOs in 2016”
“Cool Vendors in Oil and Gas, 2016”
Source: INOVX Solutions
Solutions for 3D Asset Integrity Management is published by Inovx Solutions. Editorial content supplied by Inovx Solutions is independent of Gartner analysis. All Gartner research is used with Gartner’s permission, and was originally published as part of Gartner’s syndicated research service available to all entitled Gartner clients. © 2016 Gartner, Inc. and/or its affiliates. All rights reserved. The use of Gartner research in this publication does not indicate Gartner’s endorsement of Inovx Solutions’s products and/or strategies. Reproduction or distribution of this publication in any form without Gartner’s prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner’s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see “Guiding Principles on Independence and Objectivity” on its website.
Contact us
For more information contact us at:
www.INOVX.com
Founded in 1999, INOVX provides a platform and
solutions for 3D Asset Integrity Management to
companies in the process industries worldwide. INOVX’s
V-Suite of products enable the creation, management
and access to high fidelity three dimensional views
of plant assets. These views are used in daily work
practices to better communicate and navigate all
asset information. INOVX’s solutions support many
plant functions such as reliability, safety, operations,
maintenance, inspection, and engineering. INOVX
is a pioneer and thought leader in the creation and
deployment of 3D Models in support of Operations and
Maintenance activities in existing facilities worldwide.
INOVX is headquartered in Irvine, California.
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