PTE 589
Advanced Oilfield Operations
with Remote Visualization and Control
---------Moving from PDAs to Intelligent Cooperative
Assistants
4 April 2006
Gregory Finn
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© 2006 Gregory Finn
Lecture Plan
• Background & motivation
• Wireless sensors
– overview & potential applications
• Wearable computers
– overview & potential applications
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© 2006 Gregory Finn
Sensor material taken from:
– John Heidemann & Wei Ye [USC/ISI]
• “An Overview of Embedded Sensor Networks”,
ISI TR-2004-594, Heidemann and Govindan
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© 2006 Gregory Finn
Drives Toward Smarter Facilities
• Remote control …
– hurricanes, unsafe activities
• Enhance capabilities
– visualization, agility
• Increase productivity
– greater production efficiency
– reduced downtime
• Improve safety
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© 2006 Gregory Finn
Smart Area Characteristics
• Communication rich
– Pervasive networking
– Sensors, devices, processes & people in the net
• Compute rich
– Computers scattered throughout the space
• Autonomous monitoring
• Visualization rich
– Streams of real-time sensor, device & process data
• Control rich
– Remote access to devices, processes & people
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© 2006 Gregory Finn
Smart Areas & Visualization
Smart areas generate lots of data …
– Who can watch it all?
– Autonomous monitoring is a practical necessary
Monitoring is visualization …
– Uses sensors + network + computer to ‘see’
•
•
•
•
•
structure and device health
staff & objects
pipeline & pump activity
dangerous areas
dangerous actions
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© 2006 Gregory Finn
Staff as Part of Smart Area
Smart area is networked …
– Devices, sensors & processes communicate via networks
– But people do not ‘network’
Solution: Make staff part of the smart area
– Provide staff with personal wireless hosts
– Host act as eyes and ears in the area
– Host autonomously monitors smart area
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© 2006 Gregory Finn
Why Do That?
Several reasons …
– improve productivity
• bring data where it’s needed (manuals/procedures/info on demand)
video via display/camera
– enforce/aid safe practices
• know what sensors see
• know what to do & not to do
• know where to be & not to be
– improve oversight
• know where staff are
• improve dispatch/team forming
• prevent unauthorized operation
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© 2006 Gregory Finn
Why Possible Now?
Moore’s Law
(Gordon Moore – Intel 1965)
– roughly true, should continue ~20 years
– produces exponential rate of change
– #transistors/chip doubles in ~two years
Computers became exponentially …
–
–
–
–
smaller
faster
less expensive
less power hungry
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© 2006 Gregory Finn
1970 vs 2005
PDP-10 mainframe
Space
Power
Weight
Memory
Speed
Disk
Cost (2005 $)
60 sq meters
40,000 watts
1,800 kg
1 MB
1 Mips
80 MB
$2,000,000
Dell Precision 670
0.25 sq meter
650 watts
19 kg
16,000 MB
4,000 Mips
1,200,000 MB
$15,000
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© 2006 Gregory Finn
Portables & Sensors Today
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© 2006 Gregory Finn
Example: Telos-B Mote
Characteristics …
• Powered via USB or battery
• Internal antenna
• Controllable xmit power
Flexibility …
• Sensors – Light/IR/Humidity/Temp
• CPU + TinyOS + 48KB Flash + 10KB RAM
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© 2006 Gregory Finn
Future Sensor Platforms?
Smart dust (Kris Pister, UC Berkeley)
• nodes smaller than 1mm3
• prices less than $0.05/each
mote-size and price,
but 32-bit CPU power
or
Nokia
super cell-phones
or wearable computers
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© 2006 Gregory Finn
Why Else Is It Possible Now?
1969
1980
… the Internet
2000
[courtesy of UCSD’s caida.org]
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© 2006 Gregory Finn
Back in the Old Days...
the “router”
(Aunt Mable)
wire
1920s telephony:
circuits---a physical wire from one end to the other
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© 2006 Gregory Finn
Multiplexing: Splitting a Shared Channel
Frequency Division Multiplexing
Time Division Multiplexing
a a a a a a a a a a a
a a a a a a a a a a a
Code Division Multiplexing
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© 2006 Gregory Finn
Logical View of the Telephone Network
Fixed size pipe from source to destination
 perfect for voice
 reliable conversations (QoS)
 provisioning, good engineering
 dumb & cheap end points, smart network
 evolved for 100 years (analog to digital)
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© 2006 Gregory Finn
Packet Switching (Internet)
Differences:
 packets as low-level component
 multiple kinds of traffic
 smart edges, (dumb network)
But:
 guarantees are much harder
 end-points are more expensive
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© 2006 Gregory Finn
Characteristics of the Internet
• Packet switched
• Freely available standards (IETF)
• End-to-end
– intelligence and control in the end-points (dumb middle)
– critical to allowing deployment of new services
• Distributed (no central point of control)
• But security becomes harder
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© 2006 Gregory Finn
Commercial Activity Today
Development of …
•
•
•
•
networks (wireless and wired)
low-power CPUs
sensors
applications
– centralized or stand-alone
• smart devices
– wireless monitor/control
• intrinsically safe hardware
Stage is set, however …
smart area development is still research.
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© 2006 Gregory Finn
Missing: Software Infrastructure
Domain representations
–
facility & process models
Spatial directories
–
people, sensors, devices and objects
Standards & protocols
–
data interchange and naming
Security
Applications
–
processes and procedures
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© 2006 Gregory Finn
Still … We Can Assume
In a few years …
… pervasive communication & computation
• wireless networking
– 802.11, UWB, sensors
• pocket computers
– 1 GHz, 1600x1200 head-mounted displays
– ‘spatial awareness’
• ‘smart’ areas
– sensors, staff, devices, processes
in continuous contact
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© 2006 Gregory Finn
Lecture Plan
• Background & motivation
• Wireless sensors
– overview & potential applications
• Wearable computers
– overview & potential applications
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© 2006 Gregory Finn
Why Sensors?
To know what is happening …
To visualize what is happening …
– Measurement: temp., pressure, flow rate, mixture
– Safety: monitor hazards … H2S, forbidden states
– Structure: stress/corrosion in downhole & surface
equipment, pipelines, refineries
– Reservoir: geology, current status of reserves, etc.
– Security: monitor position and intrusion
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© 2006 Gregory Finn
Sensor Challenges
Cost
– Use thousands of sensors of many types
• RFID … passive ~ $0.10 … active ~ $5
• Motes ~ $50
Power consumption
– solar + battery may be expensive or inappropriate
– battery life needed > 1 year
Networking
– provide robust data interchange
– allow low power consumption
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© 2006 Gregory Finn
Why Network?
Networking:
Ability of computers to exchange data …
Communicate what is known elsewhere …
– distance education
– remote control
– share information and files
• distributed management
– enable autonomous operation
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© 2006 Gregory Finn
Challenges
Security
– still largely ignored
Power consumption
– given distributed computers & sensors with limited power
it’s very important
Bandwidth (speed)
Interaction
– hardware / protocols: work pretty well today
– software & cooperation
• danger of application Balkanization
• no standards or competing standards
• need agreements …ex: POSC and XML for oilfield data
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© 2006 Gregory Finn
Why Sensor Networking?
Want to ‘see’ everywhere ‘visualize’ everything
– wellhead, surface facilities, control rooms
– enable autonomous monitoring
Want to combine data
– different information from different places reveals things
– ex: ability to see bigger picture can make a big difference
– reveal previously unobserved phenomena
Decrease cost
– better information, more precise control
Increase safety
– prevent dangerous actions
– detect dangerous situations
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© 2006 Gregory Finn
Result
Lots of computers interacting within the world
– physically distributed, sensing, different perspectives
Lots of computers interacting within the world
– enough that they’re near what’s sensed, 100s-1000s
– enough that some can be off and overall system still runs
Lots of computers interacting within the world
– intelligent: able to decide what’s important, collaborate
Lots of computers interacting within the world
– sensing, responding, acting
– make the area smart
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© 2006 Gregory Finn
What’s New About Sensor Nets?
Many devices => treat devices as interchangeable
– generic vs. dedicated to specific task
– benefits: trade density for robustness, longevity, accuracy
Small wireless devices => resource constraints
– limited energy, low bandwidth, higher latency
– benefits: low price means sensors can be everywhere
challenges spur new technical approaches
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© 2006 Gregory Finn
Current Sensor Nets: SCADA Systems
SCADA: Supervisory Control and Data Acquisition
– remote control of equipment
– since 1980s
General focus:
– dumb instruments (vs. being able to compute in field)
– often custom networks
– data sent to central computer or database
Very important today!
– remote control and monitoring
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© 2006 Gregory Finn
Comparing SCADA and Sensor Nets
SCADA vs sensor networks
mainframes vs PCs
(expensive, centralized, inflexible) vs cheap, distributed, versatile
Where is the data?
– SCADA typically moves raw data to a central site
– sensor nets focus on keeping and processing raw data at smart sensor
Where is the control?
– SCADA typically leaves control decisions to central site
– sensor nets focus on shifting control to smart edges
Who defines them?
– SCADA systems are often proprietary protocols
– sensor networks are today typically research protocols
Probably both areas will converge.
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© 2006 Gregory Finn
Applications of Sensor Nets
Scientific: micro-habitat monitoring
Government: vehicle monitoring
(UCLA/CENS at James Reserve)
(USC/SPPD & ISI)
Industry: equipment monitoring and control
Military: vehicle tracking
(ISI at DARPA SensIT SITEX)
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© 2006 Gregory Finn
Structural Health Monitoring
• Goal: Design sensor networks for
improving the safety of structures
(buildings, bridges, ships, aircraft,
spacecraft)
• Research focuses:
– Local excitation-based damage
identification
– System components for finegrain structural monitoring
• Multi-disciplinary effort:
– John Caffrey (CE), Ramesh
Govindan (CS), Erik Johnson
(CE), Bhaskar Krishnamachari
(EE), Sami Masri (CE),
Gaurav Sukhatme (CS)
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© 2006 Gregory Finn
Oilfield Safety Monitoring
Use sensor net to detect
and warn about leaks.
Challenges:
–
–
–
–
long-lived
easy deployment
self-configuration
condition-based maint.
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© 2006 Gregory Finn
Downhole Sensors for Control
Goal:
see what’s happening downhole
sensors monitor return mixture
cut off side-wells at sign of water
Technical challenge:
severe operating environment,
communication and control
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© 2006 Gregory Finn
Virtual Reality?
Virtualizing operations …
– sufficient timely data
– models of operation
… allows video-game like treatment
– remote observation
– remote participation
– ‘game’ the operation
Fanciful? Perhaps.
– requires lots of development
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© 2006 Gregory Finn
Lecture Plan
• Background & motivation
• Wireless sensors
– overview & potential applications
• Wearable computers
– overview & potential applications
38
© 2006 Gregory Finn
Recap: Staff & Smart Areas
Smart area is networked …
Smart area has lots of sensors …
– Devices, sensors & processes communicate via networks
– But people cannot
Solution: Provide staff with wearable, wireless computer
– Acts as eyes and ears in smart areas
– Monitors smart area for its wearer
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© 2006 Gregory Finn
Wearable Computer
Hands-free use
– In pocket or on hip
– Normally on (PDA is normally off)
Common examples:
– PDA, Cell phone, iPod
– Dedicated application, not general-purpose
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© 2006 Gregory Finn
Ideal Wearable Characteristics
Mediates between smart area and user
–
–
–
–
–
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Unmonopolizing
Unrestrictive
Observable
Controllable
Attentive
Communicative
Courtesy: Steve Mann, Univ. Toronto
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© 2006 Gregory Finn
PDAs Today
Blackberry 8700g
•
•
•
•
CPU: 312 MHz
Wireless: GSM cell phone, Bluetooth
Memory: 64 MB flash/16 MB ram
Display: 320x240 pixels
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© 2006 Gregory Finn
Video iPod
•
•
•
•
CPU: 200 MHz
Storage: 60 GB hard drive
Display: 320 x 240 pixels
Battery: 3 hrs playback
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© 2006 Gregory Finn
PDA of Today
•
•
•
CPU: 300 MHz
Memory: 1 GB
Storage: 60 GB
•
•
•
Display: 320 x 240
Communication
Interaction
High-end workstation in 1998
Weaknesses
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© 2006 Gregory Finn
Addressing Weaknesses
Display
– Resolution too low
– Screen too small
– Power hungry
Approach
Head-mounts
– 800 x 400 (DVD-quality)
– 3m view seen from 1.5m
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© 2006 Gregory Finn
Eyetap
Computer modifies what you see
–
–
–
–
camera at eye position
display over eye
image to eye + computer
superimposed feedback
Steve Mann –
Univ. Toronto, wearable pioneer
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© 2006 Gregory Finn
Addressing Weaknesses
Communication
– Cell phone network is low speed
– Expensive infrastructure
Approach
Use more attractive alternatives: 802.11 …
– Higher speed (up to 24 Mb/s)
– Inexpensive infrastructure
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© 2006 Gregory Finn
Addressing Weaknesses
Interaction
– PDA or ‘phone-call’ model
– Blind to surroundings & non-collaborative
Approach
Move toward wearable ideal
– Multiple wireless interfaces (near/far)
– Monitor surroundings
– Collaborate with other hosts in area
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© 2006 Gregory Finn
Application – Tracking
Assume …
– wireless sensors
• uniformly at known positions around facility
• announce every 2 seconds
– wearables
• monitor sensors
• reports its ID & sensor IDs recently heard
Receiver can know where wearables are …
– precision determined by sensor/receiver range
– history provides tracking & heading
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© 2006 Gregory Finn
Scenario: Tracking
receiver
sensor zones
updates
?
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© 2006 Gregory Finn
Application – Avoidance
Assume same plus …
– administration
• announces/withdraws dangerous area descriptions
– wearables
• possess map: sensor ID  position
• monitor area announcements
Wearable knows what areas to avoid …
– monitors its location/heading
– warns wearer when approaching danger
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© 2006 Gregory Finn
Scenario: Approach Warning
S2
S3
S4
warning
region
S1
S5
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© 2006 Gregory Finn
Application – Virtual Gang Lock
Assume same plus …
– monitor
• receives task description, announces task area
• monitors task member positions
• controls device state
– wearables
• task members announce position to monitor
Monitor ensures safe practices …
– controls entry/exit
– controls shutdown/restart
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© 2006 Gregory Finn
Scenario 1: Gang Lock
monitor
device
work area
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© 2006 Gregory Finn
Scenario 2: Gang Lock
device
work area
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© 2006 Gregory Finn
Collaboration: Buddy System
If you rely on a wearable for safety, it better
be operating …
• wearables monitor each other’s health
– heartbeat protocol
• health implies functionality
Lack of health implies trouble …
– associated individual OK?
– need to suspend affected activity?
– need to find another buddy?
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© 2006 Gregory Finn
Looking Under the Hood
Much of this is in its infancy.
Serious work to be done on …
– Resource discovery
– Scenario description & communication
– Security
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© 2006 Gregory Finn
Resource Discovery
Routing finds hosts by their address.
How do wearables find resources?
– ex: buddy, device, process method
Three approaches:
– directory service (central or distributed)
– diffusion (broadcast or multicast)
– area search
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© 2006 Gregory Finn
XML Scenario Description
•
<!ELEMENT warning EMPTY >
<!ATTLIST warning
command CDATA #REQUIRED
message CDATA #REQUIRED>
•
<!ELEMENT group ( buddy* ) >
•
<!ELEMENT buddy EMPTY >
<!ATTLIST buddy
ident CDATA #REQUIRED>
•
<!ELEMENT region ( coord_system, sphere+ ) >
•
<!ELEMENT coord_system EMPTY >
<!ATTLIST coord_system
units CDATA #IMPLIED
coord_ref CDATA #IMPLIED>
•
<!ELEMENT sphere EMPTY >
<!ATTLIST sphere
x CDATA #REQUIRED
y CDATA #REQUIRED
z CDATA #REQUIRED
r CDATA #REQUIRED>
•
<!ELEMENT action ( warn_group ) >
•
<!ELEMENT warn_group ( group ) >
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© 2006 Gregory Finn
Security
Downside of remote control …
– attacks
• denial of service
• unauthorized access/use
• Eavesdropping
Encryption
– public key or traditional
Authentication
– biometric
– public key encryption
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© 2006 Gregory Finn