A fluid discrimination method based on Gassmann-Brie-Patchy Equation full waveform simulations and time-frequency analysis

Yuhang Guo, Baozhi Pan, Lihua Zhang, Qiang Lai, Yuyu Wu, Ruhan A, Xinru Wang, Pengji Zhang, Naiyu Zhang and Yan Li

Energy, 2023, vol. 275, issue C

Abstract: In recent years, igneous reservoirs have been the focus of natural gas exploration and development, which can help solve the energy demand, and in addition, when oil and gas reservoirs are depleted, volcanic reservoirs provide good storage space, transport channels and storage capacity, and this is very beneficial for CO2 storage. For reservoir prediction and CO2 storage monitoring, fluid discrimination techniques are very important. For igneous rock, the lithology and mineral composition, porosity, and pore structural characteristics are known to all affect the distribution patterns and saturation of fluid. The presence of high resistivity water layers and low resistivity gas layers will affect the accuracy of fluid discrimination using resistivity data. In this study, based on core experiments, the G-B-P (Gassmann-Brie-Patchy)equation was adopted to describe the relationships between the acoustic velocity and fluid saturation values. Then, finite element acoustic logging numerical simulations of wells were carried out to obtain the array logging full waveforms of the different lithology, porosity, and saturation. Finally, the ICEEMDAN(Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) mode decomposition method and SPWVD were used to analyze the time-frequency characteristics of the simulated waveforms, and a fluid discrimination chart of gas layer was established. The results of the synthetic and field data experiments using the proposed method demonstrated that it was a good approach for fluid discrimination processes in igneous gas reservoirs.

Keywords: Gas reservoirs; Fluid discrimination; CO2 storage; Mode decomposition method; Gassmann-Brie-patchy equation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:275:y:2023:i:c:s0360544223007004

DOI: 10.1016/j.energy.2023.127306

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