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The integrity of a well system is crucial for ensuring optimized and safe flow. However, current methods and technologies used to assess well system integrity face limitations due to well design, barriers, and completion elements. This method demonstrates how specific acoustic, temperature and fingerprinting technologies can be utilized to identify tubular-annuli communications. By correlating downhole data with surface and fluid samples from each annulus, researchers confidently determine the source of Sustained Annulus Pressure (SAP) in multiple annuli. This discovery can lead to precise well workover decisions. To identify suspected areas of concern, this methodology employs Spectral Acoustic Logging (SNL) and High-Precision Temperature (HPT) sensors under both static and dynamic conditions. Shut-in survey serves as a reference point for interpretation, while disruptions in noise and temperature fields during various survey regimes pinpoint potential leak points or anomalies. Prior to logging, actions involve bleeding off the Tubing to Casing Annulus (TCA) and 1st Casing to Casing Annulus (CCA1) and pumping liquid into TCA while keeping CCA1 valve opened as a contingent part to activate potential leak points. The acoustic sensor records fluid movement noises while stationary during the up-pass. Simultaneously, HPT sensor helps to identify zones associated with crossflows, lateral flows, inflow or injection zones, and leak points. Subsequent fluid sampling from all affected annuli allows for geochemical analysis to ascertain the hydrocarbons' origin. The proposed technique provides a comprehensive understanding of flow paths and successfully identifies origin of the SAP. The interpretation results for an example well, determined communication among tubing, TCA and CCA1 annuli. Fluid samples analyzed for their isotopic signatures. After measuring carbon isotopes from the target example, it can be compared with suspected hydrocarbons signatures from adjacent areas. Carbon isotopes can be measured from the target example and compared with suspected hydrocarbons signatures from adjacent areas. The results demonstrate that carbon isotopic signatures exhibited a clear similarity between the target example and the hydrocarbons derived from the known origin and different from shallow sources. The interpretation results obtained from the noise and HPT data align with the surface pressure data collected before and during the survey. The described technologies are proved effective in identifying undesired occurrences within the complex flow geometry of the well system. The survey results match the surface pressure and annuli samples data. The proposed tools do not involve any external mechanical components, allowing logging to be conducted with a minimal footprint and reduced risk to the well. The suggested approach and methodology for leak detection offered a comprehensive evaluation of well integrity, enabling appropriate workover measures.
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Kalwar et al. (2024) studied this question.
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