0

Sand Production Detection

In the Oil and Gas sector, maintaining operational efficiency, asset integrity, and safety is crucial. However, a persistent challenge is sand production, where fine particles migrating with fluids can damage equipment, causing erosion, decreased productivity, and costly downtimes. Effectively managing this issue is vital for the long-term reliability of assets in the ever-changing Oil and Gas industry.

ABOUT THE PRODUCT

Adressing the importance of identifying and managing sand production, AiQum introduces a cutting-edge automated solution designed to accurately detect sand production in the Oil and Gas industry.

Our methodology is designed to provide an in-depth sand probability curve, serving as a valuable resource for Petroleum Engineers aiming to enhance the accuracy and effectiveness of decision-making in well management. Utilizing this technology empowers industry professionals to conduct informed evaluations, facilitating strategic planning and resource allocation. This data-driven method enhances operational efficiency, minimizes risks related to sand production, and plays a key role in ensuring the ongoing success of petroleum projects.

KEY BENEFITS

• Integrated approach: AiQum is based on fiber optic data and active ultrasonic sensing, which allows to detect not only sand particles that hit the pipe wall on the wellhead, but also sand particles traveling within the flow.

• Heightened Precision: Usage of spatial and time-frequency data together with well parameters allows the algorithm to accurately detect sand particles during well operation.

• Enhanced Decision-making: The real-time monitoring system for sand production offers engineers valuable insights, bolstering their ability to optimize production, mitigate risks, and enhance cost efficiency.

METHODOLOGY

AiQum incorporates sophisticated machine learning techniques to deliver optimal results by utilizing fiber optic technology and active ultrasonic sensing as a primary data source. The data acquisition is performed on the well’s outer side of the flowline that allows to avoid interventions to the well operation during data acquisition equipment installation.

The methodology is based on both spatial and time-frequency data which allows to achieve the detection of sand production with heightened precision.

Our methodology also utlizes different well parameters such as downhole and wellhead pressures, choke position and others to achieve the most optimal results.