Case Smarter Oil and Gas

8/3/2019 Case Smarter Oil and Gas

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The case for a smarter oil and gas industry

White Paper Oil and Gas Industry


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The oil and gas industry is, in one sense, a very simple

business: Its about extracting large amounts o a small number

o substances rom the earth or use by consumers. But this

conceptually straightorward task is risky, dangerous, wildly

expensive and very, very important to everyone on the planet.

Its also an intricately related system o systems, ranging

rom the relentless geologic search operations, to the awesome

engineering needed to capture resources miles beneath

the ocean oor, to a supply chain o giant physical assets

(pipelines, tankers, storage acilities and refneries). Along the

way, irrevocable decisions must be made about converting a

resource into one end product or another in anticipation o

uture patterns in weather, trafc or consumer buying behavior,and only then delivering raw materials to other industries and

retail products to outlets everywhere.

Some o the largest companies in the world compete in

this industry. It is an industry where fnancial commitments

must be made years ahead o payback, putting a tremendous

premium on predictive inormation that can be trusted.

And the fnancial uncertainty is compounded by political

uncertainty, with governments regulating its activities in

many dimensions, as well as actively participating in the

industry itsel.

It is an industry where prices uctuate based not only on

supply and demand, but on economic orecasts, currency

trends and speculation. It has a results-oriented, show me

engineering culture, a lot o fnancial sophistication in

the C-suite, a need or collaboration between frms on major

projects and a sub-industry o support, service and construction

frms that can mask the true points o decision-making on

major eorts.

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As the events of April 20, 2010 have shown, the

cost of a single accident can be devastating. The

spill in the Gulf of Mexico will influence how the

industry moves forward in ways that are not yetknownalthough a tougher regulatory and

compliance environment is a certainty.

On top o that, its an industry where, as the events o

April 20, 2010 have shown, the cost o a single accident can

be devastating fnancially, environmentally and in the loss

o lie. The gul spill will inuence how the industry moves

orward in a number ways that are yet to be known though

a tougher regulatory and compliance environment is a

certainty.


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technologies as horizontal drilling and multilateral wells.

But in general, the readings and measurements are notshared across tools or processes, and are highly dependent

on human interpretation, making it difcult to optimize in

an integrated and timely way.

The same goes or business intelligence. The analytic tools

in the industry today are oten very sophisticated scientifc

devices. But most are ocused on answering a particular

question, such as: Is there oil down there? or How long

can we expect that saety device to keep working? Those

dont scratch the surace o what is possible by mining

captured data in real time, in an interconnected way, with

new analytical tools.

What catalysts will drive the oil and gas

industry to become smarter?Given the difculty o fnding new reserves, combined with

rising conservation and environmental pressures, we might

have expected to see more o a transormation in this industry

already. But sustained higher prices and rising demand in

emerging economies, along with the growing importance o

Liquefed Natural Gas (LNG) and Shale Gas, have combined

to give the industry something o a second wind. Regardless

o how ast renewable energy sources are developed, its widelyagreed that the demand or marketed energy will continue to

grow into the oreseeable uture, by as much as 50 percent

rom current levels. So what will fnally convince the industry

that it needs to become smarter?

Oil and Gas Industry

The industry also fnds itsel in the crosshairs o the great

global awakening about the environment, and acing anear-universal desire to see some o its main products

completely replaced with renewable alternatives. All in all,

a lot to deal with.

Considering the fnancial risks, as well as the growing

difculty o locating new reserves, its no surprise that oil

and gas frms have been signifcant users o inormation

technology or a long time, both upstream (exploration

and production) and downstream (refning and delivery).

This includes analog instrumentation on wells up to 75 years

old. More recent systems capture data digitally, but with a

wide variety o tools and processes that reects 40 years o

experimentation and customization. And these instruments

are operated by a specialized workorce with a well-developed

(and thus perishable, when they retire) body o tacit

knowledge.

Thus, the oil and gas industry already has a level o

instrumentation that probably exceeds that o most other

industries, a level that will only grow in the years ahead,

especially upstream, as new energy targets become increasingly

remote. This instrumentation enables such leading-edge

Regardless of how fast renewable energy sources

are developed, its widely agreed that the demand

for marketed energy will continue to grow by as

much as 50 percent from current levels.


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Dwindling productivity

A decade ago, there was a burst o mega-mergers aimed atsignifcant productivity gains. That strategy paid o, but has

now about run its course. Recently announced layos by a

major international oil company and the shopping o their

downstream capabilities both underscore that many frms

are scrutinizing their operations very careully or urther

improvements. But the well is nearly dry in trying to

squeeze additional margin out o current ways o doing

business. The cost o liting oil out o the earth keeps

rising in the U.S. by as much as 18 percent over what it

was as recently as 2006. As an industry that gets a lot o

attention rom the investment community, oil and gas frms

will have a powerul incentive to achieve undamental

changes in how work is done within the industry i they

hope to take their fnancial perormance to the next level.

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The cost of lifting oil out of the earth keeps

rising - in the U.S. by as much as 18 percent over

what it was as recently as 2006.


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The natural environmentEnvironmental pressures will escalate rom both public

and private sources, placing even more o a premium on

developing processes and operations that leverage system

intelligence to meet and maintain a frms environmental

objectives. As the world demonstrates an increasing level

o concern about all orms o emissions, the ability to know,

evaluate and respond to emissions data, in real time, will

represent a signifcant competitive advantage. So will the

ability to quickly recognize, understand and fx breakdowns

o any sort throughout the system.

Our approach to smarter oil and gasThe industry is no stranger to doing original research in

basic science, and many frms maintain signifcant laboratories.

Some also support think tanks to explore the impact o

various issues and public policies. And, as weve seen, its

an industry with a lot a highly instrumented, heavy duty

inrastructure that is operated by highly trained personnel.

So in what sense is the oil and gas industry not smart

enough already?

The answer to that question lies in the very breadth and

complexity o the industry itsel the amount oinstrumentation in use today, the amount o data already

being captured, and the vast gains to be had rom insights

and actions that data could provide i it were integrated

and analyzed in real time across the industrys vast global

landscape, where even small improvements can add up to

multi-billion dollar payos.

When we think about where the industry can start becoming

smarter, three key areas jump out.

Oil and Gas Industry

The need for better visibilityAs the odds o fnding new sources become longer, and

optimizing the downstream more essential, the fnancial

leadership at major frms will demand more line o sight into

the fnancial impact o operating decisions. But that wont be

possible without creating a more integrated, transparent and

predictive analytic capability. The oil and gas industry is also

notable or the degree to which key operating decisions are

oten made in real time by individuals with hands-on process

responsibility, rather than hierarchical authority. This can be

especially true when responsibilities are shared among

corporations acting in consortium. So pressure or better

visibility on key perormance metrics will come rom engineersat the process level, as well as rom the corporate boardroom.

Due diligence

As frms collaborate to und expensive explorations and

jointly fnanced inrastructures, there will be a heightened

premium on being a more knowledgeable dealmaker. Trust

is never in oversupply in an industry that regularly makes

multi-billion dollar trades o invisible assets. So being a

successul player in this environment will depend more

than ever on knowing in real time ones own circumstances

(assets, fnances, markets, skills, commitments), AND being

able to accurately evaluate inormation oered by others.

The stakes will be too great to play industry poker with

twentieth-century levels o knowledge.


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Its been estimated that some industry workers spend upto 60 percent o their time mining data. Yet even with all

that brain power siting through numbers and images or

patterns, the average recovery rom a given feld is, according

to several surveys, around 30 percent. Other studies, however,

have reported that recovery can go as high as 70 percent

with the help o secondary recovery techniques, driven by

the data. So the fnancial reward or increasing the amount

o resource extracted per reservoir would be, on an industry-

wide basis, gigantic.

And it will not only be more proftable, but saer too, or

both workers and the environment. By using historicaltrends linked to event triggers, the industry will be able to

create a sense-and-respond environment that maximizes

well lie and minimizes physical risks, anticipating situations

remotely and responding automatically. Where tacit knowledge

is vital, frms will bring together global teams (including

retirees employed on a part-time basis) to analyze sensitive

data in secure real-time virtual collaboration. The payo:

longer well lie, optimized production, and less risk to people

and the environment.

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Enhanced exploration and productionThe harder it becomes to fnd oil and gas reserves, the more it

makes sense to look or them with instrumentation, analytics

and graphic representation. By integrating seismic and

geologic data rom multiple sources, and using advanced data

modeling combined with supercomputing (including seismic

cloud computing or above-petascale resources), the industry

can fnd reservoirs that are very remote, like the large Tupi

feld that is 180 miles o the coast o Brazil, beneath 7000 eet

o water, 10,000 eet o sand and rock, and 6600 eet o salt.

When it comes to getting the most out o reservoirs that have

already been identifed, a host o new, enhanced oil recoverytechniques have been developed. But each one adds more

physical variables to manage, and more volumes to estimate

and track. By using advanced visualization to render larger

amounts o complex data in more intuitive ways, a smarter

industry can achieve improved decision making and aster

time-to-oil. And by deploying advanced nano-sensors to

improve reservoir modeling, as well as drawing on spatial and

temporal data assimilation rom time-lapse seismic systems,

it can run predictive assumptions that dramatically increase

efciency in extracting oil and gas.

Using integrated seismic and geologic data, advanced data modeling and supercomputing, its possible

to find remote reservoirs such as the Tupi field located 180 miles off the coast of Brazil under 7000 feet

of water, 10,000 feet of sand and rock and 6600 feet of salt.


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8 Oil and Gas Industry

Its already starting to happen. A major oil company iscurrently working to extend oil feld lie and increase

production yield through the implementation o new

decision support tools. They expect to reduce unplanned

downtime by 5 percent, as well as to reduce costs by up to

30 percent through the use o predictive maintenance

techniques. These decision-support tools bridge the gap

between dierent parts o the companys operations so that

BOTH data and employee knowledge can be leveraged across

all processes, resulting in lower costs and improved production

efciency, as well as great interdisciplinary collaboration.

Much o the industrys uture is being invented in thelaboratory right now. For example, IBM Research is

doing original research in reservoir simulation, grid-based

visualization, 4D seismic imaging, and stream analytics.

And academic institutions are working on it too, such as

the University o Calgary, which is teaming with the IBM

Center o Excellence there to ocus on oil sands development.

Stanord University is also leading a multidisciplinary,

multi-department consortium to conduct research in such

areas as optimizing where and when to drill, the design o

wells to be drilled and the type o monitoring that would

maximize the lie o the well.

As oil and gas become harder and harder to fnd, the tools

to look or them in ever smarter ways will only grow.

Improved asset managementThe industry is both asset and data intensive. An oil well

at sea can easily cost $150 million. And such a well can

generate a terabyte o data per day, roughly the inormation

in 1 million medium-sized novels. But ew frms currently

manage their assets in a way that optimizes the data they

are already gathering.

Consider, or example, how a typical oil and gas frm manages

alarms. To ensure saety and prevent environmental dangers,

the industry careully monitors its systems or unusual events.

When an alarm goes o, the technician who receives the

alarm will ascertain what has gone wrong and decide how torespond. Certainly it would be helpul or them to be able to

consult the systems history (to see i this event has happened

beore), or its maintenance inormation (to see what work has

been done on this system, or what maintenance is being done

close by, which might have caused the event), or its purchase

records or the ailing part (to see i the right part had been

installed in the frst place), etc. Today, all o these elements o

data are likely to reside in dierent places, perhaps even

dierent and incompatible systems. And even i all o this

inormation were instantly available to the operator, he would

still need to perorm the act o integrating the data into a

response plan, because very little analytic intelligence has

been applied to the data other than what can be provided by

the operator himsel.

An oil well at sea can easily cost $150 million.

And such a well can generate a terabyte of data

per day, roughly the information in 1 million

medium-sized novels.


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9 White Paper

This challenge has attracted serious academic investigation.For example, the Norwegian University o Science and

Technology is working to build a multidisciplinary approach

to the integration o asset management processes.

As science-fction writer William Gibson once said, the uture

is already here, just not evenly distributed. But that uture

has already arrived at a major global energy company that is

using a design once-build many approach or its oshore

production acilities, enabling them to bring new felds to

production in a raction o the time and cost o previous

operations. Consider what design once-build many can

mean in a sphere o human activity where a structure thatis routinely customized design once-build once can

cost $150 million.

Optimize global operations

Few industries are as inherently global as oil and gas.

But the challenge o turning an oil and gas company into

a truly global enterprise remains daunting. One o the

key challenges is the handovers that exist throughout

the industry across proessional, geographic, national and

chronological boundaries. How does a company ensure

that they are seamless and eliminating the redundancies

while maintaining knowledge through the lie o systems

and assets?

Few industries are as inherently global as oil

and gas.

But i the data had been integrated, in context somethingthat a smarter asset management system can do it would

not only add speed and accuracy, but also automate and

apply analytics to the alarm itsel, leveraging the wisdom o

the companys prior experience. In other words, it would

be smarter.

That is just one example, and a hypothetical one at that.

But it gives a sense or how much smarter asset management

in the oil and gas industry can become when it applies

instrumentation and analytics in an interconnected and

integrated way. By combining workow inormation and

decision support tools across production activities, the industrywill be able to use dashboards to optimize both planned and

unplanned shutdowns, assess the preparedness o turnarounds,

run scenario planning with the beneft o mathematical models,

asset by asset, and thus maximize production, while minimizing

cost, down time and human error.

For the frst time, engineering, operations and maintenance

unctions will be able to collaborate through knowledge

sharing tools and peer networks that acilitate the sharing o

tacit knowledge, especially regarding saety and reliability

issues. And we will even be able to automatically actor

marketplace uctuations in supply and demand into decisions

about production.


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10 Oil and Gas Industry

Currently, a major liquefed petroleum corporation is workingto implement a comprehensive radio-requency identifcation

(RFID)-enabled solution or tracking its cylinders. Like

everyone else, they need greater efciency, but they also need

to prevent thet. Their RFID-tag solution will address both o

those needs, tracking the consumption level at each distributor,

while identiying unusual consumption patterns and short

turnaround times, indicating diversion. The customer

dashboard they are creating to oversee all o this will enable

the company to gain new and actionable business insights in

every step o their operation rom bottling plant to cylinder

management. Thats what we mean by smart.

Globalized solutions will require the industry to make the

most o new compute-intensive analytics. Thats why King

Abdullah University o Science and Technology is working

to build the most complex high perormance computing

system in the Middle East. And IBMs Center o Excellence

in Stavanger, Norway is ocusing on the science o Integrated

Operations rom the perspective o the industrys unique

global needs. Collaboration will be key, as oil and gas frms,

IT vendors, strategic business partners and academics work

together with oil and gas standards bodies in collaboratories

to drive more smartness into the industry.

In a smarter industry, handovers will capture real-timefeld, plant, pipeline and logistics inormation or improved

visibility, planning, exibility and decision support through

sensor-based technologies deployed enterprise-wide. And

that will automate supply chain transactions implemented

through advanced analytics and optimization programs.

Supply chains will be standardized and integrated across

multiple geographies through a common open standards-

based inormation inrastructure.

Already, one oil company is able to simultaneously monitor

the ow o oil rom more than 100 felds and nearly 50 gas-oil

separators, through 11,000 miles o pipeline, into sevenrefneries and chemical plants with only two dozen people

in one remote location.

Building on that example, a smarter industry will consolidate

global support operations into centers o excellence that use

remote collaboration and robust knowledge management

capabilities. It will also reduce IT costs and energy use through

standardized tracking and consolidation. Predictive weather

models, which are getting better all the time, will be harnessed

to minimize storm-related damages and supply disruptions.


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11 White Paper

ConclusionThe oil and gas industry has never been an easy business,

and its not getting any easier. Virtually no one expects the

industry to survive the twenty-frst century in its present

orm, with its present products. Yet its importance in

todays economy cannot be overestimated, and will remain

enormous or a long time, matched only by the size o the

sel-reinvention it must execute, as it gradually transorms

rom Oil and Gas to Energy.

In this environment, there is no alternative but or the

industry to become much smarter. The degree to which

it can do that will depend on the vision o its leaders, aswell as on the ability o its business partners, including

IBM and many other vendors, to apply instrumentation,

interconnectedness and advanced intelligence to the awesome

physical and fnancial challenges o this unique industry.


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Case Smarter Oil and Gas