Cenovus Energy has been granted a patent for a system and method that uses artificial neural networks to analyze geological features of a hydrocarbon reservoir during different stages of production. The system utilizes data from 4D seismic studies to train the neural network to recognize changes in the reservoir over time. The neural network then creates a predictive model that can be used to increase reservoir production efficiency by generating actionable data to alter production methods. GlobalData’s report on Cenovus Energy gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
According to GlobalData’s company profile on Cenovus Energy, Wellbore drilling optimization was a key innovation area identified from patents. Cenovus Energy's grant share as of September 2023 was 51%. Grant share is based on the ratio of number of grants to total number of patents.
Analyzing reservoir changes during production to increase production efficiency
A recently granted patent (Publication Number: US11719844B2) describes a method and system for analyzing reservoir changes during production to increase reservoir production efficiency. The method involves obtaining a seismic baseline of the reservoir before production and acquiring at least one seismic monitor of the reservoir after production has started. The seismic monitor is aligned with the baseline to correlate geological features of the reservoir. A 3D seismic volume of differences is generated by subtracting the baseline from the aligned seismic monitor.
To analyze the reservoir changes, a sliding window is used to generate multiple 2D image slices from the 3D seismic volume of differences and a mask. An artificial neural network is then trained using these image slices to create a prediction model that can predict reservoir changes based on the seismic baseline and observed differences. This prediction model is used to generate actionable data that can be used to increase reservoir production efficiency. The actionable data is then utilized to alter production methods accordingly.
The method also includes additional features such as obtaining the seismic baseline by recording acoustic waves reflected by the geological features of the reservoir before production. The seismic monitor is obtained by periodically recording acoustic waves reflected by the changing geological features during production. The 2D image slices represent image planes derived from the 3D seismic volume of differences. A mask is generated by applying a threshold to identify the geological features of the reservoir, which can include steam chambers or heated zones.
The system described in the patent includes components and functionalities similar to the method. It obtains a seismic baseline, acquires seismic monitors, aligns them with the baseline, generates a 3D seismic volume of differences, utilizes a sliding window to generate 2D image slices, trains an artificial neural network, generates actionable data, and alters production methods to increase reservoir production efficiency.
Overall, this patent presents a method and system that utilize seismic data and artificial neural networks to analyze reservoir changes during production and improve reservoir production efficiency. By accurately predicting reservoir changes and providing actionable data, this technology has the potential to optimize production methods and enhance overall reservoir performance.
To know more about GlobalData’s detailed insights on Cenovus Energy, buy the report here.
Premium Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
