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www.lawiq.com Law I Q Harnessing Analytics For Energy Infrastructure 660 Pennsylvania Ave., SE Washington, DC 20003 Gas Infrastructure Trends and Impacts Downstream American Gas Association FRC Committee October 27, 2017

Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

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Page 1: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

www.lawiq.com

LawIQHarnessing Analytics For Energy Infrastructure

660 Pennsylvania Ave., SEWashington, DC 20003

Gas Infrastructure Trends and Impacts Downstream

American Gas AssociationFRC Committee

October 27, 2017

Page 2: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Our Discussion

1) Pipeline Regulatory Trends

2) Case Study: Marcellus / Utica Takeaway Capacity

3) Shipper and Project Sponsor Trends

Page 3: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Industry Silos Engineering/Environmental

Financial/CorporateRegulatory/Legal

Actionable analyticsfrom regulatory activity for gas pipeline & end user decision makers.

Project modeling

Contract & Rate Analytics

Search, track, analyze !!

Competitive and FERC alerting

• Plan better• Negotiate stronger• Operate confidently

Page 4: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Machine Learning - Data Inputs

We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts.Our modeling automatically adjusts weighting and calculations of data as they’re ingested.

StakeholderEntities

Energy CompaniesProject Developer, MLP, Construction

Contractor

Anchor ShippersE&P, Utilities, Local

Distribution Co’s, Marketers

Federal / State Regulators

FERC, State Agencies, ACE, Historic Pres.

ProtestorsNational Environmental,

Native Tribes, Law Firms

ProjectAttributes

Regulatory FilingsData Requests, Agency cooperation, Developer

supplements

Company FilingsEnvironmental studies, Asset financials, tree

clearingProject

CharacteristicsTotal Costs, Pipe

Diameter, Compression

Protestor ImpactLegal actions,

Regulator appeals, volume and timing

Data Sources

Federal AgencyData requests,

comments

Legal DocketsAppeals, rehearings

State AgenciesApproval times

OtherCommercial terms,

seasonality

Page 5: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Trends in Pipeline Permitting –Lasting Longer with More Uncertainty

Page 6: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

FERC Certificate Trends

For Pre-filed projects, the trend in time to obtain a certificate has accelerated since 2012.For non Pre-filed projects that trend didn’t emerge until 2015.

~ 250 days

~ 500 days

Page 7: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

FERC Certificate Duration

Obtaining a FERC certificate is taking from about 40% longer.

Includes Greenfield and Facility/Laterals

Page 8: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Company versus Actual Dates

There is a large variation between the date requested and the actual FERC certificate date.Many projects have received FERC certificates before the date requested (early).

Page 9: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Pinpointing the Delays -Environmental, Protesters,

FERC Date Request

Page 10: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Issuing the Certificate

Project slippage occurs after completion of environmental review.Since 2013 there is a greater uncertainty in the time between EA/FEIS and certificate.

Page 11: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Protestor Involvement

Among similar projects, big disparities exist regarding the number of entities and issues.

Page 12: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Volume of Data Requests

FERC has issued a greater number of data requests before issuing the EA/FEIS.Not only for complex, greenfield projects, but also more routine pipeline expansions.

Page 13: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Case Study: Marcellus / Utica Takeaway

Page 14: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

M/U Takeaway

Public sentiment stems from owner-company public comments.How often do they reflect practical events in project development?

Project VolumeGarden State Exp Phase 1 20,000

2017 Expansion 61,000Birdsboro Pipeline Project 79,000

New Market 112,000New York Bay Expansion 115,000

CPV Valley Lateral Project 130,000Atlantic Bridge 133,000Orion Pipeline 135,000

Susquehanna West Project 145,000Leidy South 155,000

Garden State Exp Phase 2 160,000Triad Expansion 180,000

Broad Run Expansion 200,000Eastern System Upgrade 200,000

Virginia Southside II 250,000Northeast Supply Enhancement 400,000

PennEast Pipeline 1,075,000Leach XPress 1,500,000

Atlantic Coast Pipeline 1,500,000Atlantic Sunrise 1,700,000

Mountain Valley Pipeline 2,000,000Nexus 2,000,000

Mountaineer Xpress 2,700,000Rover 3,250,000

24projects

8projects(>1B)

Page 15: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Forecasting Capacity and Supply

Delays are hitting all projects. Magnitude of delay are project-specific and regional in nature.

Project VolumeGarden State Exp Phase 1 20,000

2017 Expansion 61,000Birdsboro Pipeline Project 79,000

New Market 112,000New York Bay Expansion 115,000

CPV Valley Lateral Project 130,000Atlantic Bridge 133,000Orion Pipeline 135,000

Susquehanna West Project 145,000Leidy South 155,000

Garden State Exp Phase 2 160,000Triad Expansion 180,000

Broad Run Expansion 200,000Eastern System Upgrade 200,000

Virginia Southside II 250,000Northeast Supply Enhancement 400,000

PennEast Pipeline 1,075,000Leach XPress 1,500,000

Atlantic Coast Pipeline 1,500,000Atlantic Sunrise 1,700,000

Mountain Valley Pipeline 2,000,000Nexus 2,000,000

Mountaineer Xpress 2,700,000Rover 3,250,000

LeachRover

AS

NEXUSACP

PennEastMXPMVP

Page 16: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

How long to 10B?

Cumulative delays may mean significant constraints for M/U takeaway capacity.Extent of delay relies on confidence in regulatory progress (federal & state).

6monthdelay

12 monthdelay

18 monthdelay

Page 17: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Shipper Trends

Page 18: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Shifting Markets

Regional trends may be part basin-driven and part market-driven.

Page 19: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

76% 50% 40% 41%

83%

24% 50% 60% 59%

17%

2013 2014 2015 2016 2017

Precedent Agreement Shippers% of Total Contracted Firm Capacity

EndUser/Downstream' Producer/Upstream

Supply to Demand

Market developments and pricing have adjusted appetite for those considering commitments to new projects.

Page 20: Gas Infrastructure Trends and Impacts Downstream...Machine Learning -Data Inputs We incorporate hundreds of discreet features (inputs) that update our dynamic forecasts. Our modeling

Thank You

[email protected]

LawIQ