Image-based fracture hit warning system with distributed acoustic sensing

Ning, Ivan Lim Chen; Németh, Tamás; Zhang, Zhishuai; Tan, Yunhui; Bevc, Dimitri; Bartel, David C.; Hughes, Kelly; Stefani, Joe; DiSiena, James

doi:10.1190/segam2021-3587266.1

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…In addition, Ivan Lim Chen Ning et al [17] utilized a neural network-based image recognition algorithm (CNN) to detect low-frequency signals in distributed acoustic sensing (DAS) data, aiming to identify precursor events of sand blockage and make predictions.…”

Section: Introductionmentioning

confidence: 99%

New Method for Monitoring and Early Warning of Fracturing Construction

Hu,

Fu,

et al. 2024

Processes

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During fracturing operations, special situations are often encountered. For example, the insufficient proppant-carrying capacity of fracturing fluid can cause quartz sand or ceramsite to settle near the wellbore and form a sand plug. Alternatively, excessive sand injection intensity can lead to severe accumulation of injected sand near the wellbore and also form a sand plug. These special situations are reflected in the fracturing operation curve as an abnormal increase in oil pressure over a short period of time. If not handled promptly, they can have unimaginable consequences. Sand plugs in fracturing operations, characterized by their speed and unpredictability, often form rapidly, within about 20 s. Conventional methods for on-site sand-plug warnings during fracturing include the oil pressure–time double logarithmic slope method and the net pressure–time double logarithmic slope method. Although these methods respond quickly, their warning results are unstable and vary significantly during actual operations. This is mainly because the fluctuations in the actual fracturing operation curve are often large, and there can be sudden pressure rises and drops even during stable periods, albeit less pronounced. To address the identification of anomalies in conventional fracturing operation monitoring and warning methods, a sand-plug warning index method has been proposed for sand-plug identification. This method combines the oil pressure–time double logarithmic slope with the oil pressure increment within 5 s, the rate of change in the oil pressure–time double logarithmic slope, and the fitted oil pressure intercept as indicators. The method has been validated using Well A in Fuling as an example. The validation results show that the dynamic analysis method can predict sand plugs while reducing warning fluctuations without affecting sensitivity. Compared to conventional methods, the warning time can be advanced by about 10 s.

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Section: Introductionmentioning

confidence: 99%