基于能谱-时间谱耦合脉冲中子测井的深层潜山低孔储层流体识别方法OA

This work addresses the challenge of fluid identification in complex low-porosity buried-hill reservoirs in the Bohai Sea by developing a fluid identification method based on the coupled responses of energy spectra and time spectra.First,a regularized spectral decomposition algorithm is employed to analyze pulsed neutron gamma-ray spectra and obtain the carbon-to-oxygen(C/O)yield ratio,enhancing the capability of quantitatively characterizing differences in oil and water signal responses under low-porosity conditions.Second,an oil-water identification method is established by integrating energy-spectrum and time-spectrum parameters,improving the accuracy of oil-water discrimination in complex lithological environments.Finally,a gas layer identification parameter is introduced to distinguish gas-bearing zones and fluid-bearing zones,which is then combined with the oil and water identification results to form a three-phase fluid identification workflow.Field applications in drilled wells penetrating granite gneiss buried hills and carbonate buried-hill reservoirs in the Bohai Sea demonstrate that the proposed method significantly enhances the response contrast between oil and water under low-porosity conditions,substantially reduces the uncertainty of single-parameter interpretation,and enables accurate discrimination among oil,gas,and water.The method provides an effective solution for fluid identification in complex low-porosity buried-hill reservoirs in the Bohai Sea.