1. COPPE/UFRJ
Completion Course Work
Digital Management of Oil Fields
Executive Post Graduate in Oil & Gas
March 13, 2007 / February 28, 2008
18ª Class
Coordinator: Suzana Kahn Ribeiro
Flávio Ferreira da Fonte

2. Summary of work submitted to the COPPE / UFRJ as part of the requirements for
obtaining the Diploma of Specialization in Executive Post Graduate in Oil and Natural
Gas.
DIGITAL MANAGEMENT OF OIL FIELDS
Flávio Ferreira da Fonte
February/2008
Advisor: Prof. Gilberto Ellwanger
This study aims to examine the emerging technologies being employed in the
Digital Management of Oil Fields, which aims to maximize production, increase the rate
of recovery of oil and optimize the costs of exploration and production.
2

3. Curriculum Summary
The author, Flavio Ferreira da Fonte, has been working at Oracle since 2004 as a
Senior Sales Consultant and expert in technology solutions from Oracle to customers
such as Petrobras, PDVSA and PEMEX. In June 2007 attended the Oil & Gas Oracle
Global Industry Business Unit training. He also participed in the development of a
Business Intelligence Dashboards for the Upstream area.
Mr. Fonte worked at Petrobras in the Information Technology area from 2000 to
2004 onn Downstream systems. He also participated in the implementation and
deployment of the Petrobras e-Marketplace, called Petronect and participated in the
ISO-9001 certification process at Petrobras IT.
Graduated in Technologist in Data Processing, the author also completed the
courses of specialization of Systems Analysis and Post-Graduate at IAG Master, both
from Catholic University from Rio de Janeiro (PUC-RIO).
The author is doing an MBA at IBMEC Business School at Rio de Janeiro.
3

4. Acknowledgements
I want to thank my family and co-workers from Oracle, Andres Prieto, David Shimbo,
Miguel Cruz, Eduardo Lopez, Elizabeth Faria, João Fernandez and Samy Szpigiel for
the support received.
4

5. Index
1. Introduction ..........................................................................................................................6
2. Analysis of key technologies used in Digital Oilfields projects .....................................8
2.1.Gathering information in real time...............................................................................8
2.2.Information Management ...........................................................................................15
2.3. High Performance Computing ..................................................................................17
2.4. Centers of command and remote monitoring ........................................................18
2.5 Sistems for analysis and simulations of hydrocarbon reservoirs .........................20
2.6. Systems for analysis and decision support ............................................................22
3. Conclusions ........................................................................................................................28
References .............................................................................................................................30
5

6. 1. Introduction
The world`s geopolitical dependence on fossil fuels, the duration of hydrocarbon
reserves, the rapid economic expansion of China and India, and a complex petroleum
refining and supply chain have caused oil prices to skyrocket.
With the price of oil above US$125/Bbl, companies are investing more in research
and development of new technologies to improve recovery and reduce operating costs.
Chevron has spent more than $5 billion of its budget in the past 5 years on industrial
automation and information technology.
Despite this large capital investment, the oil industry still has a shortage of
operational resources, such as drilling rigs and production platforms and associated
skilled oilfield workers. These scarce resources are now being leased or constructed
and immediately utilized, thereby increasing the costs associated with exploration and
production (E & P) operations.
Given this competitive environment, oil companies need to optimize profitability and
reduce operating costs. The major oil companies began increasingly to innovate and
implement projects with intensive use of automation and information technologies in
the area of E & P, aiming to mitigate operational risk, accelerate production, improve
recovery of reserves and optimize costs.
These projects which integrate operational, technical and financial data are called
"Digital Oilfields" [1]. Examples are: Shell, with Smart Fields [2], BP [3] with the Fields
of Future (which envisages achieving the goal of 1 billion barrels by incremental use of
new technologies) and Chevron [4], with the i-Field.
In Brazil, Petrobras is running a Digital Oilfield programme called GeDIg [5]. This
program provides the integrated management of E&P production processes through
the use of oilfield information, automation, modeling and simulation technologies to add
value to E&P assets.
In this project six pilot programmes are being evaluated, seeking to establish
standards and "benchmarks" which are most suitable and profitable for several different
6

7. types of oilfields – deepwater offshore, shallow water offshore, onshore brown field,
heavy oil, etc.
The main topics discussed by GeDIg are: the testing of software provided by oilfield
service companies (Halliburton / Landmark, Schlumberger, etc.); recommending new
oilfield procedures and workflows; implementation of remote centres of operations;
assessment of intelligent completions; optimization of artificial lift, and management of
real time operational data.
The figure below shows the vision of technology of Chevron and Shell for these
Digital Oilfield projects [6], which includes obtaining information in real time, information
management, high performance computing, visualization systems, reservoir simulation,
centres of command and remote monitoring, analysis and decision support systems.
FIGURE 1
7

8. Digital Oilfield projects are one of the major strategic initiatives for all oil companies
The technologies used must be innovative and are often borrowed from other
industries so this new technology must be analyzed and studied before being used.
The next topic details the main technologies used in these Digital Oilfield projects.
This information can be used as an initial guide for those who wish to study this issue
or work on related oilfield automation projects.
2. Analysis of key technologies used in Digital Oilfields projects
2.1. Real Time Information
Oilfield operational events, such monitoring the operation of a turbine, must be
captured and mapped in a technology platform that enables real time monitoring,
analysis and decision-making.
Several emerging technologies such as radio frequency identification (RFID),
sensors, Wi-Max, and satellites are being used to obtain real time information. For the
acquisition of data from oil wells in real time, companies are upgrading their facilities
infrastructure, implementing process control systems and installing sensors and fibre
optic across platforms and risers.
During the drilling of wells, the sensors are used to obtain information about drilling
in real time. These real time drilling systems can read the pressures, formation density,
torque, vibration and so on.
Figure 2 shows LWD (Log While Drilling) equipment capable of obtaining
petrophysical information (well logs) during drilling.
FIGURE 2
8

9. With real time logging and drilling information, engineers can identify geologic
formations immediately and determine if that formation contains oil and/or gas.
In this case, the operational challenges for downhole sensors include high wellbore
temperatures/pressures, corrosive fluids that can damage the downhole sensors, and
mechanical abrasion that can physically damage the equipment
In the production phase, these sensors monitor the production of oil, gas and water
versus cumulative time and volume; differences in downhole pressure versus wellhead
pressure; the flow efficiency of artificial lift systems; etc.
The figure below shows two pressure and temperature sensors specifically
designed for the monitoring of the bottom of oil well. This sensor is a version of the
PDG conventional optical fiber (Permanent Downhole Gauge).
9

10. FIGURE 3
The fiber optic sensor technology has been developing rapidly in recent years.
The main reasons for implementation of these sensors in the systems of
measurement are inherent characteristics of the optical fibres such as low weight,
flexibility, long-distance transmission, low reactivity of the material, electrical insulation
and electromagnetic immunity. Besides these, in many cases there is the possibility of
multiplexing the signals from several sensors, including various ampliitudes along the
same fiber sensor. These technological advantages that contribute to the fibre-optic
sensors will replace the conventional sensors in various applications. [7]
As an example of the use of these sensors in the petroleum industry, the
Norwegian company StatoilHydro [8] uses a system called Catamaran TurboWatch,
supplied by the company Shipcom Wireless [9], which tracks more than 200 devices on
eight oil platforms in the North Sea. This system collects operational information from
various machines and feeds other business and maintenance systems for the
company.
Figure 4 shows screens monitoring equipment from Catamaran TurboWatch
system.
FIGURE 4
Figure 5 identifies the eight Statoil platforms using the Catamaran TurboWatch
system.
10

11. FIGURE 5
The sensors can be installed on the wellhead, in the production tubing and on other
wellbore equipment. The data collected by the sensors is transferred to supervisory
systems devices called SCADA (Supervisory Control and Data Aquisition). In the
SCADA system each sensor is seen as a single "tag", or a unique identifier, which
gather and stores operational data.
In addition to the SCADA system, some companies use other layers of software to
maintain a history of these measures obtained. Usually the first interface with the
SCADA system is made by a data historian. One of the historians systems currently
used is called OSI / IP, from OSIsoft company [10].
11

12. However, beyond this data historian layer, companies also use a relational
database manager system (RDBMS), which stores all the information related to fields
and wells into relational tables.
Currently, Oracle’s RDBMS (Relational Database Manager System) [11] is the most
widely used data base that stores critical E&P information for oil companies.
Figure 6 shows the flow of information between the SCADA systems, OSI / PI and
RDBMS.
FIGURE 6
Figure 6 also shows that it is necessary to have a layer of applications that create a
user-friendly experience. In this case, the use of a personalized portal on the company
Intranet is strongly recommended to unify all systems and applications that the user
needs as a single point of interaction.
12

13. This kind of information portal can be developed by the company customized to
meet specific oilfield requirements or can be provided by oilfield service companies
such as Landmark [12] or Schlumberger [13].
Figure 7 shows an offshore process control centre, provided by the company ABB.
FIGURE 7
Each type of well (mature, light oil, heavy oil, deep water, etc.) may have a different
levels of automation, which can range from simple one way monitoring to complex
subsurface controls with intelligent completions [14].
The Petrobras GeDIg of Petrobras selected the Carapeba field as a pilot project. It
is a mature field composed of 3 wells located in the northeastern part of the Campos
Basin which has installed automated subsurface sensors in the wells.
Figure 8 details the configuration of the Carapeba field.
13

14. FIGURE 8
In the Carapeba pilot project, production rates, well pressures, total flow versus
time, pressure/temperature versus depth, and operational alerts are measured using
RFID.
The wells that use these technologies for monitoring, tracking and control are called
Smart Wells or Intelligent Wells.
Smart Well technology benefits include:
1) Reduction of well maintenance time
2) Easier detection of abnormal conditions
3) Accelerated problem analysis
4) Reduction of mechanical failures
5) Prioritizes the scheduling of operational activities,
6) Optimization of the use of crew and equipment resource
7) Improved reservoir management
8) Mitigation of operational risk.
14

15. .
2.2.Information Management
Depending on the technology used in wells, the number of operational sensors, and
the ranges of measurements, more than 10 GB (gigabyte) of data per day is generated
for a single offshore field. This is a large concern for CIOs (Chief Information Officers)
of oil companies.
Because of the rapid increase of Digital Oilfield data, Information Lifecycle
Management is very important for oil companies. It is necessary to understand which
data sets are dynamically changing (ex, SCADA) or static (ex. seismic) and which
device is best suited for storing this data. There are several types of storage devices
with different technologies and different data management speeds.
The figure below shows two types of storage equipment from EMC [15].
FIGURE 9
Storage systems with faster access to data cost more than those who offer slower
access to data.
With a proper understanding of the data sources and their related applications, you
can save space and money on efficient use of storage.
15

16. Another major concern is the availability of such data to users, given the agreed
levels of service and security necessary.
To ensure the high speed data access performance, regular studies of capacity and
new technology (hardware and software) should be carried out.
Every user should have a customized security profile which includes a digital
credential that is verified and authenticated (user identification, password, biometrics,
etc.), Role-based security is also necessary to access restricted information. The figure
below illustrates an authentification and authorization system designed by Oracle.
FIGURE 10
Confidential information should be restricted and carefully monitored and, if
possible, should be kept in encrypted form.
Access to confidential data via the Internet must be conducted using the VPN
(Virtual Private Network) or other secure protocols (i.e. HTTPS).
System and data auditing must be archived so that if an illegal access takes place,
alerts are rapidly fired to security administrators.
Petroleum data management standards are critical to maintaining an open, flexible,
best-of-breed system. Major E&P initiaitives include PPDM for an upstream data
16

17. model, Energistics for WITSML and PRODML data exhange formats, PODS for
pipeline data, and MIMOSA for real time monitoring. Addtionally, IT standards such as
SOA and web services should be evaluated for an oilfield architecture.
It is also necessary that companies have solutions for disaster recovery, ensuring
the least possible time of interruption in case of a disaster in the main site.
Today, Oracle provides solutions for data management, information security and
disaster recovery for various oil & gas companies.
2.3. High Performance Computing
The amount of data generated by Digital Oilfields projects and the need for
geophysicists and engineers to access huge amounts of information in real time, have
forced oil companies to use high-performance servers for data processing.
These systems large multiprocessor systems are called High Performance
Computing (HPC) systems. The term High Performance Computing refers to the use
of parallel processors and clusters of computers linked to multiple processors on a
single grid.
A high level of technical knowledge is required to assemble and use these systems,
but they can be created from existing components in the market.
Because of its flexibility, high processing capacity, and relatively low cost, the HPC
systems are increasingly dominating the world of supercomputing.
The use of high performance computing has significantly improved performance of
E&P applications, mainly in the areas of seismic processing, velocity modeling, 3D
earth models and reservoir simulation.
Landmark, Schlumberger, SGI [16], Oracle and Sun [17] have adopted high
performance grid computing as a key part of their technology strategy.
17

18. 2.4. Centers of command and remote monitoring
The oil industry has undergone rapid growth in recent years but still lacks human
resources to meet the needs of these companies.
Companies usually produce oil in inhospitable regions, such as deepwater offshore,
in deserts, or in politically dangerous places that are difficult to access where not many
qualified people want work.
There are a lot of situations where specialized knowledge is needed. Development
efforts are often delayed because of the lack of skilled employees and the inability to
relocate these experts to the oilfield work site.
Oil companies are investing heavily in command centres and remote monitoring, so
that the operations specialists, engineers and geoscientists do not need to travel to
remote oilfields.
Cross-disciplinary teams composed of geoscientists, engineers, operations
managers and financial analysts now interact in remote command centres,
encouraging teamwork and collaboration and solving problems faster.
As an example of successful use of such technology is Statoil. At Kristin platform
located 240 km off the coast of Norway, Statoil saved USD $36.5 million in yearly
operational costs by minimizing the number of employees on the platform, reducing the
number of shifts, reducing safety incidents, improving security, accelerating problem
resolution and improving the quality of life for its employees. [18]
Figure 11 shows the Center for operations managers at the Kristin platform, which
is connected continuously with the onshore command center.
18

19. FIGURE 11
In Brazil, Petrobras’ GeDig Digital Oilfield projects have already implemented two
Command Centres using the command centre technology.
In these centres, multidisciplinary teams work collaborate on monitoring production,
detecting problems, developing solutions and using Best Practice decision making
processes. The teams from these centres interact with the teams that are on platforms
in real time.
Figure 12 shows one of the centers of remote control of Petrobras.
FIGURE 12
19

20. Oil companies are using the name “Integrated Operations” for this new concept,
where different offshore and onshore departments work in an integrated manner,
increasing productivity and efficiency.
2.5 Systems for Analysis and Simulation of Hydrocarbon Reservoirs
The E&P industry is very advanced is the modeling and simulation of reservoirs but
the supporting systems are still in technology silos. Great improvements have been
incorporated into existing software, so that accurate geologic reservoir models can be
easily visualized, loaded, and modeled. The earth model of a reservoir is very
important because it is used for reserve estimates, production forecasts and field
development plans.
Until very recently in the North Sea region, because of poor recovery analysis and
inaccurate reservoir models, oil companies drilled more wells than necessary and
constantly revised their production forecasts, causing delays and extra costs for oil field
development.
The earth model is built initially from the seismic data, then is refined to a geological
model using seismic interpretation software. This geologic model is combined with
20

21. petrophysical and drilling data to build a 3D earth model which can be input into a
reservoir simulator.
Because of its extreme importance with respect to production forecasting and
reserves analysis, these models are updated with field data, which thwn use simulation
sensitivities to understand the behavior of the reservoir under the influence of various
factors.
Most Digital Oilfield projects makes intensive use of software for visualization and
simulation of reservoirs during inital phases of field development. With the additon of
real time operational information, these systems can be used for real time production
management and well monitoring. Well operations and drilling data is loaded
continuously into reservoir and well simulators, allowing more accurate computer
modeling of production facilities and providing more realistic forecasts.
From the existing models, different scenarios can be assembled to assess
development sensitivities and their possible results. Historical data from analagous
fields can be used to predict reservoir performance of undeveloped fields.
The figure 13 exemplifies a typical reservoir simulation image from the Roxar Field
[19].
FIGURE 13
21

22. 2.6. Systems for analysis and decision support
The E&P industry is adopting several new concepts. One of the concepts is "Fast-
Loop" versus "Slow-Loop" information processing, depending on the needs of business
operations.
For example, oilfield operations (flow, pressure, temperature, etc.) can be classified
as "Fast Loop". This type of information must be displayed and analyzed as soon as
possible.
"Slow Loop" processes may include longer term transactional information such as
ERP data or monthly costs of E&P projects.
The use of real time information from producing oil wells, intervention status, loss
details for each well, costs of materials and labour costs have become essential to E&P
operations and are the basis for many real time decisions.
The volume of “Fast Loop” information is increasing exponentially and is creating
data management problems for Digital Oilfield managers. The task of analyzing both
22

23. “Fast Loop” and “Slow Loop” data without specialized software can waste a lot of time
for engineers in the field.
To provide the right information to the right people in time, the oil companies are
investing heavily in Business Intelligence software projects for Fast Loop and Slow
Loop information.
According to Wikipedia [20], Business Intelligence is a business term, which refers
to applications and technologies that are used to obtain, provide access and analyse
data and information in accordance with the operations of companies.
Business Intelligence can help companies understand the factors affecting its
business, assist in decision-making via KPIs, and is currently one of the main needs of
E&P companies.
A Business Intelligence solution is composed of a data warehouse
("Datawarehouse", "DataMarts") and tools to analyse and display results to users
through analytical reports.
There are several tools on the market for construction of these reports. These
reports use web portals to display important KPIs (production of oil and gas, alarms of
production below the optimal point, etc.).
The data for the assembly of these reports comes from many different sources,
such as Landmark or Schlumberger, company databases and ERP systems (Oracle E-
Business Suite, JD Edwards, SAP, etc.).
British Petroleum, OXY, Marathon, Chevron, XOM, Shell and many other IOCs
have already started Business Intelligence projects that analyze the rapid cycle
information.
BP’s Gulf of Mexico operation is using a Business Intelligence solution that
integrates information from its various systems and publishes web reports that help in
increasing productivity and reducing costs.
This system can be configured so that different people can have different visions of
operational and corporate data, according to their work needs. Each employee using
23

24. the system has a customized profile that manages the transactions needed for their
daily work.
The figure 14 shows a web portal customized for the user that is used to monitor
the production of oil, gas and water. The user interacts with the plot and can drill down
into specific details if necessary.
In this example, production is declining, and the user can drill down for more detail
(Figure 15) by clicking on the line graph.
The dashboard from figures 14 and 15 was built using the Oracle’s Business
Intelligence software.
FIGURE 14
24

25. FIGURE 15
Business Intelligence tools can also provide a series of graphs (Figure 16), which
combine structured and unstructured data and help in understanding both operational,
technical and financial information.
FIGURE 16
25

26. Another important feature of such tools is the integration with Microsoft Office . The
reports and graphics built in Business Intelligence tool can be opened and used in
Excel and Powerpoint (Figure 17).
FIGURE 17
With these new Business Intelligence tools, the engineers can analyze the overall
field performance, identify which wells are not producing according to plan, analyze
costs and access real-time KPIs. These key indicators include revenue and profit per
barrel, lifting costs, etc.
Spatial performance maps can significantly improve the understanding of many
Digital Oilfield operational situations. These portals allow operators to make decisions
better and faster, encouraging safer and more efficient operations.
Information originating from different geographical locations and company
departments which previously took weeks to be gathered, are now rapidly analyzed
from a single control panel.
Business Intelligence applications continue to evolve and are integrating GIS
(Geographical Information Systems) systems of companies, making a spatial
connection between data and its specific location on a map.
26

27. With this type of GIS integration, intuitive applications are being built for hurricane
tracking, personnel safety, production monitoring and facilities management. (see
Figure 18)
FIGURE 18
Long cycle information can also be spatially visualized including actual vs budgeted
AFEs, revenue versus expenditure, financial reports for government agencies and HSE
compliance reporting.
For this types of information, there is specialized Business Intelligence software
which facilitates the tasks performed by users, increases productivity and derives
detailed management information for improved decision-making.
Usually these systems are integrated with those previously used in the rapid cycle
information.
Another E&P need is detailed analysis of existing data to find patterns and predict
situations. Companies are using Data Mining to identify areas to be drilled, optimize
results of well interventions, select candidates for hydraulic fracture versus chemical
treatment and analyze exploration anomalies.
There are two types of Data Mining - Descriptive and Predictive.
27

28. Descriptive Data Mining is used on exploration data to discover patterns and
relationships that are repeated in similar geologic structures.
Predictive Data Minin is being used on maintenance data to anticipate possible
equipment failures [21].
Data Mining tools make intensive use of statistical algorithms. These include
Prioritized Allocation, Classification and Prediction, Regression, Clusters, Rules of
Association, Extraction of Features, Text Mining, BLAST, Decision Models Trees and
SVM.
3. Conclusions
The oil industry is going through a phase of unprecedented technological
developments with their rapid implementation of Digital Oilfields.
Current advances are allowing oil companies to improve recovery and accelerate
production but all of this information and technology is not being fully utilized.
The exploitation of oil reserves has grown because of new oilfield technologies and
better definition of existing fields. One of the companies that have achieved great
success in this field is Saudi Aramco, which has had significant incremental production
increases.
Saudi Aramco increased its production from 10 million barrels per day in 2004 to 11
million barrels per day in 2008. All new wells are equipped with permanent downhole
monitoring, submersible pumps, intelligent completions and are connected to a central
remote command centre which have multidisciplinary teams managing production
operations.
More expensive energy sources, such as heavy oil from the Orinoco basin and
Canadian Tar Sands, are now economically viable at prices greater than $60/Bbl.
Companies such as Petrobras and Chevron, through the use of technologies cited
in this work are already drilling in ultra-deep waters using fully automated Digital Oilfield
technology.
28

29. The IOCs and NOCs are focused on programs to reduce costs and increase
productivity in order to achieve their operational and financial objectives. The net profit
of Exxon Mobil was USD $40B in 2007, USD $18B for Chevron and USD $11B for
ConocoPhillips in 2007. [22]
Use of the technology by itself does not guarantee a company better results. It is
also necessary to invest in human capital management and technology training. Only
with a well trained and motivated workforce can deliver increased productivity at lower
costs. Currently one of the biggest challenges for the oil and gas industry is to attract
and train skilled employees. The oil companies are investing heavily in training
programmes, in partnerships with educational institutions and in joint ventures with
oilfield service and technology companies.
The exchange of experiences and collaboration on a global scale is causing an
increasing number of electronic communities geared to the oil and gas industry. The
use of blogs and wikis for dissemination of oilfield knowledge and the use of virtual
environments such as "Second Life" for promotion of companies and new technologies
is continuing to be adopted by progressive companies.
Within this context the SPE (Society of Petroleum Engineers) [23], the IBP
(Brazilian Institute of Oil Gas and Biofuels) [24] and COPPE / UFRJ (Luiz Alberto
Coimbra Institute of Post-Graduate Engineering and Research) have provided valuable
contributions.
Oil companies must continue to develop the skills of their employees. They must
merge engineering expertise, exploration and production skills, and information
technology to fully leverage the Digital Oilfield.
According to the Vice President of Chevron, Donald L. Paul, there will soon be a
new generation of applications for integrated seismic interpretation, earth modeling and
reservoir simulation. He expects major advances in underwater robotics and the
inevitable exploration and production of offshore oil in the Arctic [25].
With all these technological advances in Digital Oilfield projects, the amount of
information being processed will continue to expand exponentially, leading to advanced
software development and more complex integrated software applications.
29

30. Critical data can be cached in memory, thus allowing faster access. Software from
the market such as "Oracle Times Ten (In-Memory Database)" [26], which can carry
information from the database to the server memory will become widely used in
industry.
In the field of technological research some companies are investing in
nanotechnology and biotechnology. In the field of nanotechnology one of the major
applications is the creation of nano robots capable of being inserted into a petroleum
reservoir to collect reservoir description information. In the field of biotechnology one of
the lines of research is related to the development of bacteria capable of turning heavy
oil into lighter oil while still in the reservoir. Another line of research is investigating the
use of enzymes to increase oil recovery. Another important technology research area
are Health/Safety/Environmental (HSE) issues, which require that companies make
their operations safer and more eco-sensitive.
I think the industry will continue to meet the growing global needs for energy.. IOCs
and NOCs will seek out new technologies to improve recovery, find more reserves,
explore new alternative sources, optimize the costs of E & P and work in a more
secure, collaborative manner.
The Digital Oil Field will be deployed on a large scale by most of E & P companies
and the technologies used in these projects will be increasingly employed in this
industry.
References
Jacobs – “Digital Oil Field of the Future Lessons from Other Industries” Cambridge
Energy Research Inc (CERA)
Lima e outros - SPE PAPER 112191 – GEDIG Carapeba – A journey from Integrated
Intelligent Field Operation to Asset Value Chain Optimization
www.shell.com
www.bp.com
www.chevron.com
www.energyinsight.com
www.gaveasensors.com
30

31. http://www.statoilhydro.com
www.shipcomwireless.com
www.osisoft.com
www.oracle.com
www.halliburton/landmark
www.schlumberger.com
José Eduardo Thomas – Book Fundamentos de Engenharia do Petróleo
www.emc.com
www.sgi.com
www.sun.com
Digital Energy Journal (Nov & Dec 2007 issue)
Digital Energy Journal (Jun 2006 issue)
Wikipedia – www.wikipedia.com
Shahab D Mohaghegh – SPE PAPER 84441 – Essential Components for a Data
Mining Tool for the Oil & Gas Industry.
O Globo Newspaper – 04 March 2008
www.spe.org
www.ibp.org.br
Journal of Petroleum Technology - October 2007 – Special Commemorative Issue
Oracle Times Ten - http://www.oracle.com/technology/products/timesten/index.html
31