Talk on how oil and energy professionals such as geoscientists, managers, drilling, reservoir, production, and facility engineers can leverage IIoT capabilities and their economic considerations

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2. CJ Ejimuda - EIT
Principal Engineer and Scientist
Msc. Petroleum Engineering - USC
BEngr. Electrical Electronics Engineering - FUTO
Msc. Advanced Control Systems and Robotics Engineering - CalPoly(*One quarter)
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A little about me...

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Outline
● Objectives
● O&G IIoT Process: Monitor, Control, Improve
● Design and Cost Considerations
● Edge computing
● Security
● Intelligence
● Conclusion

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Objectives
● Production grade IIoT technology and opportunities within the oil and energy industry

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What’s IIoT ?
● Use of network-connected devices, separated or embedded in an industrial equipment to record,
monitor, control and improve an existing industrial process or to enable a new capability
previously unrealized
Config. 1 Config. 2

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Exploration
● Task: Generate 3-D Image of the target reservoir
● Monitor / Record: Geophones , hydrophones
● Control: Vibrator trucks, airguns
● Improve: Estimate the likelihood of commercial hydrocarbon quantity

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Drilling
● Task: Safely hit target prospect quickly and cost effectively
● Monitor / Record: MWD tools
● Control: Top drive system
● Improve: Prevent kick, casing ballooning, torque and drag issues

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Production
● Task: Produce at maximum efficient rate possible
● Monitor / Record: PDHG, flow line
● Control: SCSSV wellhead valves
● Improve: Determine optimum choke, pressure, flow rate

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Facility
● Task: Enhance facility equipment useful life
● Monitor / Record: Pipeline, compressors
● Control: Valves, Main Oil Line Pump
● Improve: Increase MTBF , minimize scheduled and unscheduled downtime of equipments

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Design and Cost Considerations
● Serverless
- Database and Storage as a service
- Functions as a service
- IoT Device Management as a service
- Little to negligible upfront investment
- Advantages:
Infrequent transmission of data
Lower Total Cost of Ownership - Pay As You Go
Faster time to market
Converts CAPEX to OPEX
- Disadvantages:
Handling big data computations and algorithms are ineffective
Expensive for real time computation environment
Cloud provider lock in

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Design and Cost Considerations
● Microservices / Service Oriented Architecture
- Package all services as ONE - (Docker-compose, Kubernetes)
- High upfront investment
- Advantages:
Handle big data workloads
Easily deploy updates to all devices
Easily implement open source and customizable solutions
- Disadvantages:
Manage and maintain servers - CAPEX
Operational expenses
Longer time to market

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Edge Computing
● Optimizing cloud computing resources at device’s local network
● Performing data processing
● Deploying AI / ML algorithms

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Security
● Generate security certificate and encryption key for each physical and edge device
● Set up device logging profiles, define security policies, roles
● Edge Computation: Define user, group and generate associated certificate and key

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Security
● Set rules using AI algorithm to alert for DDoS attack
DDoS - Distributed Denial of Service

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Intelligence
● Supervised, Semi-Supervised and Unsupervised Learning Algorithms are IIoT-proof
- Exploration: Infer the likelihood of commercial hydrocarbon quantity
- Drilling: Kick, Casing Ballooning, Torque and drag issues
- Production: Determine optimum choke, pressure, flow rate
- Facility: Increase MTBF , minimize scheduled and unscheduled downtime of equipments

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Recap: Summary
● Enormous opportunity exist in monitor and control, let alone optimizing the process
● Skill set is highly transferable from Exploration → Drilling → Production → Facility
● Engineers will have to directly extract and work with big data generated as small data
opportunity becomes limited

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Questions?
Thank You!
Please fill out the survey:
http://bit.ly/iiot-srvy
e:cj@hybriData.us

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Back Up

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Hardware Considerations
● Functional inputs and outputs
- Value of recorded data or Action to be performed
- Networking environment
- Power consumption