More Than Thirty Years of Innovative Thought and Accelerated Results
18–21 January 2016
Dubai, UAE
Chairpersons:
Marko Maucec
Saudi Aramco
Ahmed Hutheli
Saudi Aramco
Committee:
Next Generation of Smart
Reservoir Management: The Eminent
Role of Big Data Analytics
Application
Deadline:
18 December
2015
As asset yields are becoming harder to assess and even harder to forecast, oil and gas operating companies and services
providers must enable real-time decisions to better predict business outcomes that drive improved efficiencies and utilisation
in order to achieve improved bottom line results and profitability.
Arun Kumar
ADCO
With the continued world-wide expansion of Intelligent Digital Oilfield (DOF) assets and projects, coupled with the exponential
growth in the volume and complexity of acquired data, the industry needs to rapidly adapt to a new generation of “digital
transformation” technology and processes including:
Ayman Mohamed
ADMA-OPCO
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Implementation of large-scale, big data-driven advanced analytics integrated into role-centric, relevant time workflows
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Delivery of holistic ability for capture, classification, integration and interpretation of ALL relevant data (geological,
engineering, production, equipment, performance, etc.) to a high degree of accuracy and precision
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Ability to understand advanced analytical trends and correlation models to quickly and efficiently unlock the “hidden”
knowledge from ALL datasets; from small data to large-scale and complex data
Mohamed Al Marzouqi
ADNOC
Chris Lenzsch
EMC
Dave Stern
ExxonMobil
Luigi Saputelli
Frontender
Morgan Eldred
Gartner
Stan Cullick
Greenway Energy Transformations
It is imperative that we simultaneously advance science-driven as well as data-driven technologies and processes that enable
companies to capture and transform ALL data into actionable insight. Our ultimate goals are to:
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Improve asset value and returns
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Enhance safe and environmental-friendly operations
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Improve production and recovery rates, as well as
facilities and manufacturing efficiency
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Increase efficiencies and productivity across major
business units
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Optimise global operations
The proposed Forum is designed to address the technologies, methods, solutions, and best practices for improved data
management and data utilisation in core business processes leveraging “big data and advanced analytics” in the oil and gas
industry and aims to deliver value to exploration, drilling, and production operations. Some of the challenges to address:
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How to collect, classify, integrate and maintain data efficiently?
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Automation in big data and analytics: Is it feasible, when and how?
Tony Milan
IBM
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What are some of the predicaments of selecting the “fit-for-purpose” tools?
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Does big data necessarily mean big uncertainty?
Serkan Dursun
Independent Consultant
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What are the pros and cons of big data driven analytics?
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How to incorporate and utilise data driven solutions with science driven solutions?
Huda Jassem Ibrahim Al-Aradi
Kuwait Oil Company
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How to enable change and increased capacity in people, processes, and technology to ensure success?
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How can this impact HSE and social responsibility?
Lapi Dixit
Halliburton
Nasser Mahrooqi
Petroleum Development Oman
Sebastien Matringe
Quantum Reservoir Impact
Who will the Forum Appeal to?
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Managers/Directors CIOs, COOs
•
HSE Managers
Parijat Mukerji
Schlumberger
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IT Managers/Directors
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Other C-Level Executives
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Business Intelligence/Development Managers
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Academics, Researchers
Steve Matthews
Teradata
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Data Warehouse Managers and Regulators
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Project Managers
Engineers and Geoscientists: Users/Practitioners of
Predictive Data-Driven Analytics
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Technical Professionals in Predictive Data-Driven Analytics
Forum Series Liaison:
Abdullatif Omair
Saudi Aramco
Birol Demiral
Schlumberger
What is a Forum?
SPE Forums offer an exclusive opportunity to interact with innovators, foremost professionals, and leading technologists.
The objective is to create a collaborative, idea-generating forum that stimulates new ideas and innovation about future challenges
facing the E&P industry.
Participants at SPE Forums are selected by the Forum Steering Committee based on their ability to contribute to facilitated
discussions of the topic. Participants are encouraged to come prepared to contribute their experience and knowledge, rather
than be spectators or students.
If you have a role to play in meeting the challenges of tomorrow head-on, apply today.
Benefits to You and Your Organisation
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Gain insight and perspective through conversations with peers who share your same interests.
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Enjoy the relaxed atmosphere of learning through one-on-one interaction.
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Meet with other experts from international companies, research institutes, and universities in an off-the-record format.
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Form professional relationships that will continue after the forum has ended.
www.spe.org/events/15fme1
18–21 January 2016
Dubai, UAE
Next Generation of Smart Reservoir Management:
The Eminent Role of Big Data Analytics
These exciting topics will be discussed in an open setting designed for optimal
input from all participants.
Sunday, 17 January 2016
1830–1930 hours
Monday, 18 January 2016
1830–2030 hours
Welcome Reception
Group Dinner
Monday, 18 January 2016
0900–1230 hours
Tuesday, 19 January 2016
0900–1230 hours
Session I: Data Quality, Validation, and Standardisation
Session Managers: Serkan Dursun, Independent Consultant;
Ahmed Hutheli, Saudi Aramco
Session III: Data Mining, Statistics, and Predictive Modelling
Session Managers: Luigi Saputelli, Frontender;
Marko Maucec, Saudi Aramco
With the implementation of intelligent fields and state-of-the-art
technologies for best-in-class reservoir management practices, data quality
assurance and standardisation become imperative.
Recently, the pursuit of excellence in the upstream petroleum area has
been reinforced by data-driven sciences such as descriptive statistics,
automatic-process-control theory, data mining, and predictive-analyticsmodelling techniques. The development and production of oil and gas
resources supported by continuous real-time data entail learning and
knowledge search over a relatively long period of time. As we drill
more wells and produce for various decades we acquire more data
and information, progressively reduce the uncertainty in production
forecasts and continuously improve the economic value of oil and gas
fields. However, challenges persist in identifying and characterising the
basic modelling elements affecting petroleum production forecasts in a
multidisciplinary fashion.
This opening session examines the key factors for establishing a robust and
reliable data management system that has the resilience and scalability
to handle and deliver consistent data. We believe such a system should
have the following factors: data standardisation, data quality control,
data filtration, data access and visualisation, and system reliability and
availability. In the context of each factor, associated challenges will be
identified and assessed. Moreover, the session will discuss how the actual
impact of each factor on data quality assurance depends on the conditions
of any particular case. For instance real-time downhole sensor capture
undergoes through data quality assurance processes that are different than
manual data capture processes. Hence, only a subset of the mentioned
factors may be relevant in that scenario. Therefore, it is important to
understand the risks to data quality in each specific case. Implementing
and understanding such systems will provide reliable and consistent data
which will result in fast and optimised decision making and ultimately will
contribute significantly in increasing production potential, recovery factor,
and efficiency.
Monday, 18 January 2016
1400–1730 hours
Session II: Integration of Disparate Data Sources Regardless of
Origin, Time Scale, or Structure
Session Managers: Steve Matthews, Teradata
Every well planned, drilled, completed, put into production, and later
abandoned, generates a huge amount of data at every stage of the process.
Upscale to the field level and terabytes of data is available to engineers
and scientists, and it seems likely that the future of field development will
continue to drive the collection of ever more varied data—especially with
the growth of automation and advanced analytics.
Increasingly, such operations are characterised not only by the size, but
also the variety of the associated datasets: not all data is in structured rows
and columns, but in unstructured images, video, text, work logs, streams,
and more. The full value of these disparate datasets can be significant, but
is only realised when data is integrated and seen in context of each other
and in context of relevant time, role-centric workflows. The opposite is also
true: unless usable information is produced, data collection can be seen as
a burden and waste of time and company budgets.
The discussion in this session will focus on the techniques and processes
that business professionals will need to develop and employ to properly
capture and transform complex, multi-timescale, structured and
unstructured, and other highly variable data into reliable information that
can be used to create insight in taking profitable actions.
This session will explore the cross-link between fundamental sciences
and rapidly changing digital-information technologies in the area of hybrid
approaches to oilfield-knowledge management by addressing questions
like:
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How could data analysis refine physical models and determine values
or related parameters so robust that reliable predictions can be
made?
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How data are validated and interpreted and how results are
communicated fast enough to make the right decisions at the right
time in the right context?
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How can we more efficiently analyse existing and new data using
cross-validation approaches and dimensionality-reduction modelling
to uncover patterns, useful for predictions on production and
recovery?
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How can we adopt and implement best-practice technologies from
fellow industries and create a game-changing momentum for the oil
and gas business?
Tuesday, 19 January 2016
1400–1730 hours
Session IV: Scalable Big Data Analytics for Production and
Operational Excellence
Session Managers: Stan Cullick, Greenway Energy Transformations;
Sebastien Matringe, Quantum Reservoir Impact
The session will focus on production: surveillance, diagnostics, optimisation
and operations, failure tracking and analysis, systems and equipment
reliability, EH&S, and field execution.
Real-time production instrumentation, i.e. pressure, multi-phase flow,
temperature, vibration, erosion, pump performance, power, etc., from
the entire value chain of completions, well heads, flow lines, batteries,
separators, etc., is loading databases with terabytes of data.
In addition to this real-time data, massive operational historic data,
operational engineering models, digital and non-digital context
unstructured data, and event data from across the well/field life cycle must
be integrated for full utilisation with this high density digital data.
www.spe.org/events/15fme1
The analytics tools of the future must be able to scale the data for
production decisions, and engineers must be able to fully analyse all of
these data elements with highly advanced analytics and models to better
understand correlations and inter-dependencies that will enable a more
proactive, predictive, and prescriptive operations environment.
The future of operations will require advanced analytics for equipment
tracking and reliability statistics and predictive analytics to improve
operational efficiencies. Operations will be advancing to use of extensive
automation, closed loop control, and even robotics to operate equipment,
service wells, etc. which will require new ways of looking at and using
the data and analytics in a highly proactive and predictive manner. This
session will discuss technologies to advance production and operations as
described above.
Wednesday, 20 January 2016
0900–1230 hours
Session V: Large-Scale Data Analytics for Portfolio Management
Session Managers: Serkan Dursun, Independent Consultant;
Steve Matthews, Teradata
As competition for scarce resources intensifies, portfolio management is
becoming one of the most critical analytical exercises in our industry. For
some companies, a strategic shift from an integrated business model to a
pure-play E&P operations model gives sharper focus to the imperative of
developing high-performing assets, while uncertainty persists in how to
optimise their portfolio from harder to reach and harder to manage assets
in mature fields, offshore fields, and unconventional plays.
More data and analytical modelling techniques are available to portfolio
managers than ever before. New technologies are delivering new
measurement and modelling techniques, the data growth trend is set to
continue, and these managers are expected to utilise all of this data to
make faster, better decisions on company portfolios and investments that
can have business impact for years if not decades. This session will explore
the techniques that analysts will need to master in order to:
•
Leverage advanced analytics and other methodologies to derive the
best possible information from available data
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Use that information in decision analysis regarding portfolio
investment and which assets to acquire, develop, retain, or sell
Wednesday, 20 January 2016
1400–1730 hours
Session VI: Potential of Big Data Analytics throughout the Asset
Life Cycle
Session Managers: Arun Kumar, ADCO; Parijat Mukerji, Schlumberger
Historically, large amounts of data are generated throughout the life cycle
of hydrocarbon assets, and the amount of generated data usually correlates
with the size of the recoverable reserves. With the increase in continuous
monitoring of vital signs of wells and surveillance techniques used in an
asset, the amount of generated data has shown multi-fold growth.
Can “big data” be referred to as the existing volume of data in many mature
assets? When would it be justified, if ever, to incorporate this terminology in
the upstream oil and gas industry? Is data-driven analytics only applicable
to “big data”? Can data-driven analytics meaningfully contribute to the
asset life cycle with current data volumes? Where in the asset life cycle is
data-driven analytics most applicable? This session, attempts to shed light
on these types of issues.
Wednesday, 20 January 2016
1830–2030 hours
Group Dinner
Thursday, 21 January 2016
0900–1230 hours
Session VII: Advances in Data Visualisation
Session Managers: Dave Stern, ExxonMobil;
Stan Cullick, Greenway Energy Transformations
A critical challenge in applying advanced analytics to reservoir management
is developing tools that can be used by practicing reservoir engineers
and geoscientists to understand the results of analysis, and ultimately
use those results to make decisions to optimise reservoir performance.
Current 2D and 3D visualisations and dashboards may evolve to much
higher dimensional interactive visualisations in the future. Key features
of these tools are the ability to visualise disparate and dense, sometimes
high frequency data, to easily qualify and to see trends in high-dimensional
parameter space, find anomalous results, integrate disparate data types,
and visualise predicted scenarios with associated uncertainties.
This session will explore avenues for development of new tools to
enable more efficient and effective utilisation of big data and to provide
visualisations of “what-if predictive modelling”.
Thursday, 21 January 2016
1400–1730 hours
Session VIII: Impact of Access to All the Data All the Time to All
the Stakeholders
Session Managers: David Holmes, EMC;
Nasser Mahrooqi, Petroleum Development Oman
According to IDC, “The 3rd Platform is built on the technology pillars of
mobile computing, cloud services, big data and analytics, and social
networking. Adoption is being driven by business requirements for mobile
access by a distributed workforce, enhanced collaboration, and predictive
analytics to anticipate issues and prioritise decisions for resolution—made
available for cloud-agnostic deployment to mitigate implementation
complexity and risk.”
The objective of this session is to understand the 3rd Platform, its potential
impact on our industry and this forum’s focus areas, and to discuss and
develop ideas on how to harness the power and potential of the 3rd
Platform to maximise results.
With the promise and the premise that all data will be available to all users
and stakeholders in all of its forms (from raw to interpreted to real-time
to correlated models to advanced analytics to beyond) to generate more
proactive insight and make better decisions faster, how will our industry
need to “change” to be able to truly utilise all the data in the context of:
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Individual contributors, core workflows, and activities
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Cross functional, cross discipline teams, and assets
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Improved collaboration and collaborative decision making
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Real-time and relevant time predictive and prescriptive analytics
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Advanced monitoring and control, including closed-loop control
•
Operational technology, data management, and user experience
requirements to reach the potential “connected decisions” model
•
Improved business impact and bottom line results resulting from
such approach
Next Generation of Smart Reservoir Management:
The Eminent Role of Big Data Analytics
18–21 January 2016
Dubai, UAE
Forum Guidelines
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Participants are expected to attend every session.
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Slides are limited, allowing maximum time for informal discussions and exchange of experience.
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Conducted off the record to support the free interchange of information and ideas.
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Extensive note taking is not allowed.
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Recording of any forum session is prohibited.
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Information disclosed at a forum may not be used publicly without the originator’s permission.
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articipants are requested to omit reference to forum proceedings in any subsequent published work or
P
oral presentation.
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A written summary may be prepared and distributed to attendees after the forum with unanimous attendee
agreement and at the discretion of the steering committee and SPE approval.
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No commercialism.
Application Information
APPLY TODAY!
Participants at SPE Forums are selected by the Forum Steering Committee based on the ability to contribute to the
discussion of the topic. Attendance is limited to maximise each person’s opportunity to contribute.
Accepted applicants will receive their registration form and other materials within two weeks of the application
deadline. For those requiring visas to attend the forum, please ensure that you leave sufficient time for your visa to
be processed.
Online:www.spe.org/events/15fme1
Mail: SPE Middle East, PO Box 215959, Dubai, UAE
Fax:+971.4.457.3164
An electronic version of the printed application form is available for downloading and printing at
www.spe.org/events/14fme1. You may also contact SPE at +971.4.457.5800 or [email protected] to receive a printed
application form via mail, fax, or email.
If the committee accepts your application, you will receive registration materials, including more detailed information on
housing, transportation, and fees. If your application is placed on a waiting list, you will receive notification of that fact. After
notification of acceptance, your registration form with payment must be returned by 18 December 2015 to ensure your
place in the forum.
Forum Registration Fee: E
arly Bird: USD 2,800 (Before 18 December 2015)
Late Fee: USD 3,100 (After 18 December 2015)
Includes the following for the forum participant
•
•
•
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Registration to attend all seven forum sessions.
Four nights of hotel accommodation including breakfast based on single occupancy.
Welcome reception on Sunday, 17 January 2016.
Scheduled Meals
Please note: Attendees are expected to attend the full forum and the fee is a fixed full registration fee. The base
registration fee does not include accompanying persons. Details of accommodation and rates for spouses and
family members will be sent with the registration packet that will be emailed to each delegate upon acceptance.
www.spe.org/events/15fme1