Daily production well estimates are a cornerstone of the oil and gas industry, providing critical insights into well performance and productivity. These estimates drive decision-making for production allocations, field operations, and investments.

The Quadface Well Estimation Template (QWET), developed by Quadface and EnergySys, revolutionizes well estimation with its Advanced Comparative Regression (ACR) Model and innovative ‘Best Fit Automatic’ feature, delivering unmatched accuracy and efficiency.

Harnessing the EnergySys cloud platform, QWET offers tailored, adaptable solutions for the oil and gas sector. Its advanced architecture provides reliable estimates, actionable insights, and production efficiency while addressing traditional systems’ challenges.

What makes QWET stand out?

Competitive Advantage

QWET’s standout features include:

1. ACR Model and ‘Best Fit Automatic’ Feature: Employs advanced regression algorithms for precise IPR curve modeling, ensuring optimal accuracy.
2. Integrated Data Analysis: Provides comprehensive insights into well performance for trend analysis and informed decisions.
3. Industry-Tailored Interface: Simplifies processes with user-friendly designs specific to oil and gas needs.

Why QWET Outperforms Traditional Systems?

QWET surpasses traditional software by offering:

1. Superior Accuracy: Advanced regression modeling and the ‘Best Fit Automatic’ feature ensure precision and minimize estimation errors.
2. Actionable Insights: The integrated data analysis generates a detailed ‘Curve Report’, expediting decision-making.
3. High Efficiency: Intuitive design and automated workflows enhance productivity.

QWET Architecture and System Design

The Power of Three: Triangulating Accuracy

QWET employs a triple-pronged approach for well estimation:

1. Real-Time Measured Data: Ensures reliability with VFM/MFM device data.
2. Well Test Insights: Guides calculations with thorough performance analysis.
3. Advanced Curve Estimation: Applies the ACR Model to precisely forecast well behavior.

Do you think only AI can do predictive models? – Deep dive into QWET’s Curve Estimation Process

When set to ‘Best Fit Automatic,’ QWET utilizes AI-driven regression analysis on multiple curve types—linear, inverse second-order, and up to fourth-order polynomial. The ACR Model selects the optimal curve based on performance metrics, enabling predictive intelligence while remaining user-friendly and cost-effective.

QWET also caters to diverse user needs with flexible calculation options like Interpolation, Best Fit for Curve Type, and Manual Curve Fit.

Benefits of having a strong Technological Foundation – EnergySys

QWET’s foundation on the EnergySys cloud platform delivers:

• Seamless Integration: Pulls real-time production and well test data.
• Scalability: Handles vast datasets efficiently.
• Customizable Calculations: Allows configuration of regression models tailored to well-specific characteristics.
• Automation of Well Curve Updates: Provides dynamic updates with minimal intervention.

Addressing Traditional Challenges

QWET resolves critical challenges, including:

• Data Silos and Integration: Centralizes data from multiple sources for holistic analysis.
• Manual Processes and Errors: Automates workflows, reducing human error.
• Handling Large Datasets: Scales operations without bottlenecks.
• Slow Decision-Making: Delivers real-time updates for quicker responses.
• Regulatory Compliance: Ensures data integrity with built-in validation and audit trails.

Conclusion

The Quadface Well Estimation Template (QWET) redefines well estimation by integrating advanced regression techniques and the EnergySys platform. With its unique features and robust capabilities, QWET enhances accuracy, efficiency, and decision-making, empowering businesses to stay ahead in the oil and gas sector.