casemark/analyzing-midstream-infrastructure-assets

Analyzing Midstream Infrastructure Assets

Evaluates midstream assets with throughput analysis, fee-based vs commodity-exposed revenue, and contract structure assessment.

When To Use

• Underwriting a pipeline, gathering system, processing plant, or terminal acquisition
• Evaluating an MLP or midstream C-corp equity or debt investment
• Assessing dropdown candidates within a sponsor/MLP structure
• Benchmarking contract quality across a midstream portfolio
• Reviewing counterparty concentration and basin-level production risk

Inputs To Gather

• Asset description: asset type (pipeline, gathering, processing, fractionation, terminal), diameter/capacity, geography, interconnects
• Throughput data: historical monthly/quarterly volumes (Mcf/d, bbl/d), capacity utilization rates, and seasonal patterns
• Contract book: shipper agreements, acreage dedications, MVCs (minimum volume commitments), fee schedules, escalators, and remaining tenor
• Revenue breakdown: fee-based vs. percent-of-proceeds vs. keep-whole vs. commodity-exposed components with historical mix
• Financial statements: EBITDA, distributable cash flow (DCF), maintenance capex, growth capex, and leverage ratios
• Counterparty data: shipper/producer credit profiles, production forecasts for dedicated acreage, and rig count trends in connected basins
• Regulatory/permits: FERC tariff status (interstate vs. intrastate), right-of-way agreements, environmental permits [VERIFY: jurisdiction-specific permitting requirements]

Workflow

1. Classify the asset and revenue model

   • Identify asset type and position in the midstream value chain (wellhead gathering → processing → long-haul transport → fractionation → terminal/export)
   • Categorize revenue: pure fee-based, fee with escalators, percent-of-proceeds, percent-of-index, keep-whole, or hybrid structures
   • Quantify the fee-based vs. commodity-exposed revenue split; flag any commodity margin exceeding 20% of gross margin as material exposure

2. Analyze throughput and utilization

   • Chart historical throughput against nameplate capacity to derive utilization rates
   • Identify volume trends: declining basin production, ramp-up from new well connections, or plateau behavior
   • Compare throughput to MVC floors — volumes consistently at or below MVCs signal producer stress or over-contracted capacity
   • Assess organic growth potential: available capacity headroom, pending interconnects, expansion optionality

3. Evaluate the contract book

   • Map weighted-average contract life (WACL) and remaining MVC tenor; flag contracts with <3 years remaining
   • Assess acreage dedication quality: size of dedicated area, drilling activity on dedicated acreage, decline rates of existing wells
   • Review fee escalation mechanisms (CPI-linked, fixed annual step-up, or redetermination) and historical realized escalation
   • Identify recontracting risk: contracts rolling off in any single year exceeding 20% of revenue warrant detailed recontracting assumptions

4. Stress-test counterparty and basin risk

   • Evaluate top-5 shipper/producer concentration — a single counterparty above 30% of revenue is a concentration flag
   • Cross-reference producer credit ratings, hedging programs, and breakeven economics against current commodity prices
   • Assess basin-level risks: regulatory moratoriums, water disposal constraints, takeaway bottlenecks, and competing infrastructure [VERIFY: state-level regulatory environment for target basin]
   • Model a downside case: reduce throughput 15-25% below base, apply MVC deficiency payment mechanics, and recalculate coverage

5. Build the financial profile

   • Calculate EBITDA, DCF, and distribution coverage ratio under base, upside, and stress scenarios
   • Separate maintenance capex (integrity, compliance, cathodic protection) from growth capex (looping, compression additions, new laterals)
   • Compute leverage (Debt/EBITDA) and compare to midstream sector benchmarks (typically 3.0x–4.5x for investment-grade)
   • Assess dropdown economics if asset sits within a sponsor/MLP structure: dropdown multiple vs. market trading multiple, IDR burden

6. Synthesize findings and flag risks

   • Summarize asset quality tier: core infrastructure with long-dated fee-based contracts vs. basin-dependent gathering with commodity exposure
   • Rank key risks: commodity sensitivity, recontracting cliff, counterparty concentration, regulatory, and volumetric decline
   • Identify value levers: expansion capex opportunities, fee escalator upside, recontracting at market rates, operational efficiency gains

Output

Produce an Analysis Report containing:

• Executive summary: asset description, investment thesis (1-2 paragraphs), and key metrics table (EBITDA, DCF, coverage, leverage, WACL, utilization)
• Revenue and contract analysis: fee-based/commodity split, contract tenor waterfall chart, MVC coverage analysis, top counterparty table
• Throughput analysis: historical volume trends, utilization rates, basin production outlook
• Financial projections: base/upside/downside EBITDA and DCF with key assumptions stated
• Risk matrix: ranked risks with probability/impact assessment and mitigants
• Valuation context: implied EV/EBITDA vs. comparable midstream transactions and trading comps

Quality Checks

• Confirm revenue split percentages reconcile to reported financials (fee-based + commodity-exposed = 100% of gross margin)
• Verify MVC volumes against actual throughput — flag any period where actuals fell below MVCs and confirm deficiency payment treatment
• Cross-check WACL calculation against individual contract expiry dates
• Ensure stress-test assumptions are internally consistent (e.g., volume decline should flow through to reduced variable O&M)
• Confirm all commodity price assumptions are dated and sourced (strip pricing with as-of date)
• Mark any regulatory or permitting assumptions with [VERIFY] where state or FERC-specific rules apply
• Validate that maintenance capex assumptions align with asset age, integrity management plan, and recent inspection data