Arps Decline Forecast

Decline curve analysis using the Arps hyperbolic decline equation. Calculates rate and cumulative production over time for production forecasting.

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DCA Auto-Fit Model Comparison

Auto-fit Arps hyperbolic and Duong decline models to the same production data, then compare R² and EUR to select the best model. Arps works well for conventional reservoirs; Duong is better for unconventional (tight/shale) with linear flow.

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Decline Diagnostics Analysis

Diagnostic analysis for decline curve interpretation using derivative-based methods. These tools help identify flow regimes and validate decline model selection.

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Decline Model Comparison

Compare multiple decline curve models for the same well. Different models may be more appropriate depending on reservoir type and flow regime. Arps is standard for conventional, Duong for unconventional transient, and PLE for tight/shale.

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Decline Rate Conversions

Convert between different decline rate representations. Understanding the difference between nominal and effective decline rates, and between different time bases, is essential for consistent decline analysis.

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Duong Decline Forecast

Decline curve forecast using the Duong model, specifically designed for unconventional reservoirs exhibiting transient linear flow. The Duong model captures the power-law behavior common in tight oil and shale gas wells.

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EUR Calculator

Calculate Estimated Ultimate Recovery (EUR) for different economic limits and decline parameters. Essential for reserves estimation and economic analysis.

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EUR Sensitivity Analysis

Sensitivity analysis of Estimated Ultimate Recovery (EUR) to Arps decline parameters. Understanding parameter uncertainty impact on EUR is critical for reserves estimation and economic analysis.

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Modified Hyperbolic Decline

Modified Hyperbolic decline model that transitions from hyperbolic to exponential decline at a specified terminal decline rate. This addresses the unrealistic EUR predictions from pure hyperbolic decline with high b-factors.

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Production Data QC

Clean production data before decline curve analysis by detecting and removing outliers using a rolling-window Z-score method. Compare raw vs cleaned data and show the impact on Arps curve fitting — noisy data produces unreliable decline parameters.

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