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Tag: URTeC 2021

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[URTeC 2021 Paper] Are unconventional well performance gains exhausted?

[URTeC 2021 Paper] Are unconventional well performance gains exhausted?

What has driven the unconventional productivity gains over the past decade, and can we expect continued performance improvements?We use our machine learning ...

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[URTeC 2021 Paper] Use of Machine Learning Production Driver Cross-Sections for Regional Geologic Insights in the Bakken-Three Forks Play

[URTeC 2021 Paper] Use of Machine Learning Production Driver Cross-Sections for Regional Geologic Insights in the Bakken-Three Forks Play

Machine learning explainability tools like SHAP values provide a powerful tool to understand how geologic performance drivers vary across a play.   Talk Details:: Tuesday, ...

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[URTeC 2021 Paper] Quantifying the Diminishing Impact of Completions Over Time Across the Bakken, Eagle Ford, and Wolfcamp Using a Multi-Target Machine Learning Model and SHAP Values

[URTeC 2021 Paper] Quantifying the Diminishing Impact of Completions Over Time Across the Bakken, Eagle Ford, and Wolfcamp Using a Multi-Target Machine Learning Model and SHAP Values

  In this paper we use our models to evaluate how the impact of completions varies over the life of a well, across ...

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[URTeC 2021 Paper] Machine Learning Methods in the Williston: A Case Study in Productivity Decay and the Implications for Inventory Exhaustion

[URTeC 2021 Paper] Machine Learning Methods in the Williston: A Case Study in Productivity Decay and the Implications for Inventory Exhaustion

What does remaining inventory look like in the Bakken? This study examines how rock quality of remaining inventory varies around the basin, and ...

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[URTeC 2021] Autoregressive and Machine Learning Driven Production Forecasting – Midland Basin Case Study

[URTeC 2021] Autoregressive and Machine Learning Driven Production Forecasting – Midland Basin Case Study

This paper details the results of Pioneer’s pilot study with Novi on automated PDP forecasting, and their vision for a fully-automated, ML-based ...

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[Free Guide] The 11 Most Common Mistakes Oil & gas Operators Make While Building Machine Learning Capabilities

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