20240026778. SYSTEMS AND METHODS FOR APPLICATION OF STATISTICAL CLASSIFICATION AND PATTERN RECOGNITION FOR COMPARTMENT DESIGN IN HORIZONTAL OIL WELLS simplified abstract (Saudi Arabian Oil Company)

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SYSTEMS AND METHODS FOR APPLICATION OF STATISTICAL CLASSIFICATION AND PATTERN RECOGNITION FOR COMPARTMENT DESIGN IN HORIZONTAL OIL WELLS

Organization Name

Saudi Arabian Oil Company

Inventor(s)

Raheel R. Baig of Dhahran (SA)

SYSTEMS AND METHODS FOR APPLICATION OF STATISTICAL CLASSIFICATION AND PATTERN RECOGNITION FOR COMPARTMENT DESIGN IN HORIZONTAL OIL WELLS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240026778 titled 'SYSTEMS AND METHODS FOR APPLICATION OF STATISTICAL CLASSIFICATION AND PATTERN RECOGNITION FOR COMPARTMENT DESIGN IN HORIZONTAL OIL WELLS

Simplified Explanation

The patent application describes systems and methods for using statistical classification and pattern recognition techniques to design compartments in horizontal oil wells. The invention includes a drill for drilling the well and a computing device with a memory component that stores logic for processing data related to the well.

  • The computing device receives input parameters for the target well and performs a log transformation on the permeability log data.
  • The transformed data is used to calculate the mean and standard deviation.
  • A classification flag is generated based on the standard deviation, which helps classify the permeability log and identify noise.
  • The noise is then transformed using a predefined pattern library.
  • A final transformed signal is created from the classification flag and the transformed noise.
  • The final transformed signal is used to generate a compartment design, which provides recommended compartment intervals based on the measured depth of the target well.

Potential applications of this technology:

  • Improved compartment design in horizontal oil wells.
  • Enhanced understanding of permeability log data and noise classification.
  • More accurate identification of compartment intervals based on measured depth.

Problems solved by this technology:

  • Traditional compartment design methods may not effectively account for noise in permeability log data.
  • Inaccurate compartment design can lead to inefficient oil recovery and increased costs.
  • Difficulty in distinguishing noise from actual permeability data can impact decision-making in well design.

Benefits of this technology:

  • More precise compartment design can optimize oil recovery and increase production efficiency.
  • Improved understanding of permeability log data can lead to better decision-making in well design.
  • Reducing noise in the data can enhance the accuracy of reservoir characterization and modeling.


Original Abstract Submitted

systems and methods for application of statistical classification and pattern recognition for compartment design in horizontal oil wells. one embodiment includes a drill for drilling a target well and a computing device that includes a memory component that stores logic that causes the computing device to receive an input parameter for the target well, perform a log transformation on the permeability log to create transformed data, and calculate a mean and a standard deviation of the transformed data. some embodiments generate a classification flag that classifies the permeability log, based on the standard deviation, classify noise from the permeability log, and transform the noise based on a predefined pattern library. some embodiments create a final transformed signal from the classification flag and the noise and generate a compartment design from the final transformed signal that provides recommended compartment intervals versus measured depth of the target well.

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