View source for Saudi arabian oil company (20240254875). METHOD AND SYSTEM FOR PREDICTING FLOW RATE DATA USING MACHINE LEARNING simplified abstract

=METHOD AND SYSTEM FOR PREDICTING FLOW RATE DATA USING MACHINE LEARNING=


==Organization Name==

[[:Category:saudi arabian oil company|saudi arabian oil company]]


[[Category:saudi arabian oil company]]

==Inventor(s)==

[[:Category:Mohammed H. Al Madan of Al Qatif (SA)|Mohammed H. Al Madan of Al Qatif (SA)]][[Category:Mohammed H. Al Madan of Al Qatif (SA)]]

==METHOD AND SYSTEM FOR PREDICTING FLOW RATE DATA USING MACHINE LEARNING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240254875 titled 'METHOD AND SYSTEM FOR PREDICTING FLOW RATE DATA USING MACHINE LEARNING

**Simplified Explanation:**
The patent application describes a method that involves using machine-learning models to predict pressure, pressure gradient, and flow rate data for wells in a geological region based on acquired pressure, pressure gradient, and temperature data.

**Key Features and Innovation:**
* Obtaining acquired pressure data and pressure gradient data for wells in a geological region.
* Using machine-learning models to predict pressure, pressure gradient, and flow rate data for the wells.
* Incorporating acquired temperature data into the prediction process.

**Potential Applications:**
This technology could be used in the oil and gas industry for optimizing well production and reservoir management.

**Problems Solved:**
The technology helps in predicting key parameters for well operations, which can improve efficiency and decision-making in the oil and gas sector.

**Benefits:**
* Enhanced well performance prediction.
* Improved reservoir management.
* Increased operational efficiency.

**Commercial Applications:**
Potential commercial applications include oil and gas exploration and production companies looking to optimize their well operations and maximize production.

**Prior Art:**
Readers can explore prior art related to machine-learning applications in the oil and gas industry to understand the evolution of similar technologies.

**Frequently Updated Research:**
Stay updated on advancements in machine-learning models for predicting well parameters in the oil and gas sector to leverage the latest innovations.

**Questions about the Technology:**
1. How does machine learning improve the accuracy of predicting pressure and flow rate data for wells?
2. What are the potential challenges in implementing this technology in real-world oil and gas operations?


==Original Abstract Submitted==

a method may include obtaining acquired pressure data for various wells in a geological region of interest. the method may further include obtaining acquired pressure gradient data for the wells. the acquired pressured gradient data may correspond to a pressure difference based on vertical depth at one or more wells among the wells. the method may further include obtaining acquired temperature data regarding the wells. the method may further include determining predicted pressure data for a well in the geological region of interest using a first machine-learning model and the acquired pressure data. the method may further include determining predicted pressure gradient data for the well using a second machine-learning model and the acquired pressure gradient data. the method may further include determining predicted flow rate data for the well using a third machine-learning model, the predicted pressure data, the predicted pressure gradient data, and the acquired temperature data.



[[Category:E21B47/07]]
[[Category:G06N3/08]]
[[Category:CPC_E21B47/07]]