Background Noise Imaging-based Monitoring of Water-driven Leading Edges

Authors

  • Feng Yang

DOI:

https://doi.org/10.54097/39ew9m03

Keywords:

Water Drive Leading Edge Monitoring, Passive Source Time-shift Imaging, Background Noise Imaging, Autocorrelation Seismic Interferometry, Dynamic Monitoring, Microseismic Monitoring

Abstract

This paper investigates the necessity of monitoring the leading edge of water drive in the process of compression drive, and points out the limitations of the existing technology, among which the microseismic monitoring method is less costly and widely used but less accurate. Tracer tracking is reliable, and water injection effect can be judged by monitoring tracers in production wells, but the operation and interpretation are more cumbersome. Four-dimensional time-shifted seismic monitoring is reliable and can determine the location of water-driven front and predict the distribution of residual oil in long-term water-driven reservoirs, but the cost is high, the cycle time is long and the acquisition is inconsistent. And a new technique based on passive source time-shift imaging is proposed, which is based on background noise imaging with autocorrelation seismic interferometry to realize low-cost and long-time water-drive leading edge monitoring. The experimental results show that the way and number of geophones are deployed directly affect the imaging effect, in which the performance of the wire-bundle-like observation system is better than that of the ring-like system, and the more the number of geophones, the better the imaging effect. Effective dynamic monitoring of the water-driven leading edge was carried out in two mines using this technology, confirming its stability and reliability in practical application. The study provides a complete set of monitoring process, which brings the possibility of technology optimization for future oilfield development, and suggests combining with microseismic monitoring to improve the imaging accuracy and monitoring effect.

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Published

10 May 2024

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Articles

How to Cite

Yang, F. (2024). Background Noise Imaging-based Monitoring of Water-driven Leading Edges. International Journal of Energy, 4(3), 20-26. https://doi.org/10.54097/39ew9m03