Decline Curve Analysis in the Cloud: Faster Forecasting for Independent Operators

You need to forecast production for budgeting, reserves reporting, workover planning, and acquisition analysis.

The traditional approach? Export data to Excel. Fit decline curves manually. Hours per well.

For 100 wells, that's 100-200 hours of work. Most operators do this once per year (if at all) because it's so time-consuming.

Cloud-based automation changes everything: Analyze all wells in minutes. Update monthly. Better accuracy. More insights.

Here's how it works and why it matters.

Why Decline Curve Analysis Matters

Use Case 1: Production Forecasting

The Question: What will my production be in 6 months? 12 months? 3 years?

Why It Matters:

• Budgeting (revenue projections)
• Cash flow planning
• Reserves reporting (SEC, bank requirements)
• Valuation (buying or selling assets)

Traditional Approach:

• Fit decline curves manually in Excel
• Update annually (too painful to do more often)
• Forecasts quickly become outdated

Cloud Approach:

• Automated curve fitting
• Update monthly (or weekly)
• Always current forecasts

Use Case 2: Identifying Underperformers

The Question: Which wells are declining faster than expected?

Why It Matters:

• Early identification of problems
• Workover candidates
• Production optimization opportunities

Traditional Approach:

• Compare actual production to... what?
• No good baseline (because decline curves outdated)
• Problems discovered months late

Cloud Approach:

• Compare actual vs. forecast daily
• Automatic alerts when wells underperform
• Immediate investigation

Example: Well 15H forecast: 45 bbl/day. Actual: 38 bbl/day (15% below). Alert: "Well 15H underperforming." Investigation: Pump efficiency issue. Fix: Optimize pump settings. Result: Production back to 44 bbl/day.

Value: Catch problems weeks earlier.

Use Case 3: Reserves Estimation

The Requirement: Banks and SEC require reserves estimates.

Traditional Approach:

• Hire reserves engineer
• They perform decline curve analysis
• Cost: $5K-$20K annually
• Update annually only

Cloud Approach:

• Automated decline curves
• Reserves calculated continuously
• Internal team can do it
• Annual engineer review for certification

Value:

• Lower cost ($2K vs. $20K)
• More frequent updates
• Better internal understanding

Use Case 4: Acquisition Analysis

The Scenario: Evaluating 50-well acquisition.

Questions:

• What's the production forecast?
• What's the EUR (estimated ultimate recovery)?
• What's the value at different price scenarios?

Traditional Approach:

• Manual decline curves: 50-100 hours
• By the time analysis done, deal is over

Cloud Approach:

• Upload production data
• Analyze all 50 wells: 30 minutes
• Run multiple price scenarios: 5 minutes
• Make informed bid quickly

Value:

• Better deals (thorough analysis)
• Faster decisions (win competitive bids)

Use Case 5: Workover Justification

The Question: Is this workover worth it?

Analysis Required:

• Current production and forecast
• Post-workover production estimate
• NPV calculation

Traditional Approach: Manual decline curve + NPV spreadsheet: 2-3 hours per well.

Cloud Approach: Automated analysis: 5 minutes.

Result: Analyze more workover candidates. Pick the best ones.

How Decline Curve Analysis Works

The Math (Simplified)

Basic Concept: Production declines over time. Decline curves model this mathematically.

Common Decline Types:

1. Exponential Decline:

• Most common for mature wells
• Constant percentage decline
• Formula: q = qi × e^(-D × t)

2. Hyperbolic Decline:

• Common for unconventional wells (shale)
• Decline rate decreases over time
• Formula: q = qi / (1 + b × D × t)^(1/b)

3. Harmonic Decline:

• Special case of hyperbolic (b = 1)
• Very gradual decline
• Formula: q = qi / (1 + D × t)

Where:

• q = current production rate
• qi = initial production rate
• D = decline rate
• b = hyperbolic exponent
• t = time

The Challenge: Determining which model fits best and what parameters to use.

Manual Approach (Excel)

Process:

1. Export production data for one well
2. Plot production over time
3. Try different decline models
4. Adjust parameters until curve fits
5. Extend curve into future (forecast)
6. Calculate EUR (area under curve)

Time: 1-2 hours per well (for someone who knows what they're doing)

Issues:

• Subjective (different analysts get different results)
• Time-consuming
• Easy to make mistakes
• Rarely updated

Automated Approach (Cloud)

Process:

1. Upload production data (all wells at once)
2. Cloud software analyzes each well:
   • Tests multiple decline models
   • Finds best-fit parameters automatically
   • Calculates forecast and EUR
   • Stores results
3. View results in dashboard

Time: 2-5 minutes for 100 wells

Benefits:

• Consistent (same methodology every time)
• Fast (analyze entire portfolio)
• Accurate (algorithms find optimal fit)
• Easy to update (re-run monthly)

What Cloud-Based Decline Curve Analysis Looks Like

Core Features

1. Automated Curve Fitting

How It Works:

• Upload production history (or sync from your system)
• ML algorithm analyzes each well
• Tests exponential, hyperbolic, harmonic models
• Finds best fit (lowest error)
• Generates forecast

Output:

• Decline curve (graphical)
• Forecast table (monthly production)
• EUR estimate
• Confidence interval

2. Bulk Analysis

Process:

• Analyze all wells simultaneously
• Results in dashboard
• Sort by forecast, EUR, decline rate, etc.
• Export to Excel or PDF

Use Case: Monthly production review. See all wells at once. Identify trends.

3. Comparison Views

What You See:

• Actual vs. forecast (are wells performing as expected?)
• Well-to-well comparison (which wells declining fastest?)
• Field-level aggregation (portfolio forecast)
• Peer well analysis (compare similar wells)

Value: Pattern recognition impossible in Excel.

4. Scenario Analysis

Questions:

• What if oil prices drop 20%?
• What if we workover 5 wells?
• What if we drill 10 new wells?

Cloud Tool:

• Adjust assumptions
• Re-run forecasts instantly
• Compare scenarios side-by-side

Use Case: Board presentation. Show multiple scenarios.

5. Integration with Economics

Combined Analysis:

• Production forecast
• × Price assumptions
• • Operating costs
• = Cash flow forecast

Then:

• NPV calculation
• Breakeven analysis
• Workover ROI

Value: Financial analysis in minutes, not hours.

Advanced Features

ML-Enhanced Forecasting:

• Traditional decline curves assume simple math
• ML considers more variables:
  • Well characteristics
  • Completion type
  • Offset well performance
  • Operational events (workovers, downtime)
• Result: 10-20% better forecast accuracy

Type Curve Generation:

• Analyze all wells by field, completion type, vintage
• Generate "type curve" (expected performance)
• Use for budgeting new wells

Anomaly Detection:

• Identify wells declining faster than forecast
• Alert when production drops below curve
• Prioritize for investigation

Automatic Updates:

• Re-run analysis monthly (automatically)
• Track forecast accuracy over time
• Refine models based on actual performance

Implementation: How to Get Started

Option 1: DIY Excel (Not Recommended)

What You Need:

• Production data
• Excel skills
• Decline curve templates (free online)
• Time and patience

Pros: Free (if your time is free)

Cons:

• Slow (hours per well)
• Subjective
• Not scalable
• Rarely updated

Verdict: OK for <10 wells. Not viable beyond that.

Option 2: Commercial Software

Examples:

• PHDWin (commercial decline curve software)
• Aries (petroleum economics)
• OFM (well analysis)

Pros:

• Industry standard
• Comprehensive features
• Proven methodology

Cons:

• Expensive ($5K-$20K+ annually)
• Complex (steep learning curve)
• Designed for reserves engineers (not operations staff)
• Requires local installation

Verdict: Overkill for independent operators unless you have reserves engineer on staff.

Option 3: Cloud-Based Tools

Examples:

• WellPulse (our product)
• Combocurve (SaaS decline curves)
• Various others

Pros:

• Affordable ($1K-$5K/year typical)
• Easy to use
• Automated analysis
• Cloud accessible
• Regular updates

Cons:

• Less comprehensive than enterprise tools
• May not satisfy SEC requirements (depends on tool)

Verdict: Sweet spot for independent operators. Fast, affordable, sufficient for most needs.

Option 4: Consulting (Annual)

What It Is: Hire reserves engineer annually to perform analysis.

Pros:

• Professional analysis
• SEC compliant
• No software to buy

Cons:

• Expensive ($5K-$20K annually)
• Only updated once per year
• Not useful for day-to-day operations

Verdict: Good for compliance. Not useful for operational decision-making.

Hybrid Approach (Recommended)

Best Practice:

• Cloud tool for monthly operational analysis
• Annual reserves engineer for SEC/bank compliance

Why:

• Use cloud tool year-round (operational decisions)
• Engineer validates annually (compliance)
• Total cost: $3K-$10K/year (vs. $20K+ engineer-only)

Case Study: 100-Well Permian Operator

Starting Point:

• Annual decline curve analysis (hired consultant, $12K)
• No in-year updates
• Budgets based on outdated forecasts
• No systematic workover prioritization

Implementation:

• Subscribed to cloud decline curve tool
• Integrated with production database
• Trained operations manager (2 hours)

Investment: $3K/year + $8K annual engineer review = $11K total

Usage:

Monthly:

• Automated analysis of all wells (5 minutes)
• Review dashboard for underperformers
• Update budget forecast

Quarterly:

• Detailed review with management
• Scenario analysis for board

Annually:

• Engineer review for SEC compliance

Results Year 1:

Operational Improvements:

• Identified 8 underperforming wells (declined faster than forecast)
• Investigated all 8
• Found 5 with fixable issues (pump optimization, gas lift adjustment)
• Restored production: 120 bbl/day
• Value: $110K annually

Better Budgeting:

• Monthly forecast updates
• Caught production shortfall early (Q2)
• Adjusted spending to match revenue
• Avoided cash crunch

Workover Prioritization:

• Analyzed 15 workover candidates
• Ranked by forecast NPV
• Selected best 5 for budget
• Improved workover ROI: 30%

Total Value: $180K+ (production restoration + better decisions)

ROI: 1,536%

Time Savings: 40-50 hours annually (vs. doing manually)

Best Practices

1. Update Regularly Monthly updates keep forecasts current. Quarterly minimum.

2. Review Accuracy Compare forecasts to actual. Refine models over time.

3. Use for Decision-Making Don't just generate forecasts. Use them to:

• Prioritize workovers
• Identify underperformers
• Support budget decisions

4. Combine with Economics Production forecast alone isn't enough. Add prices and costs.

5. Validate with Engineer Cloud tools are great for operations. Have engineer validate for compliance.

6. Train Your Team Operations manager should be able to run analysis. Don't rely on outside experts.

7. Track Forecast Accuracy

• How often are forecasts accurate?
• Which decline models work best for your wells?
• Improve methodology over time

Take Action

Decline Curve Analysis in WellPulse:

• Automated analysis for all wells
• Multiple decline models tested automatically
• Monthly updates
• Integrated with well economics
• Scenario analysis
• Export reports

Pricing:

• Included in WellPulse platform ($10-30/well/month)
• Or standalone decline curve module ($200-$500/month)

Request WellPulse Demo →

Learn About Our Forecasting Solutions →

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About Strataga & WellPulse

We build production forecasting and analytics tools for independent operators. Our cloud-based decline curve analysis turns hours of Excel work into minutes of automated analysis.

Based in Midland, TX—we understand Permian Basin decline characteristics.

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