The shale oil reservoir within the Yanchang Formations of Ordos Basin harbors substantial oil and gas resources and has recently emerged as the primary focus of unconventional oil and gas exploration and development.D...The shale oil reservoir within the Yanchang Formations of Ordos Basin harbors substantial oil and gas resources and has recently emerged as the primary focus of unconventional oil and gas exploration and development.Due to its complex pore and throat structure,pronounced heterogeneity,and tight reservoir characteristics,the techniques for conventional oil and gas exploration and production face challenges in comprehensive implementation,also indicating that as a vital parameter for evaluating the physical properties of a reservoir,permeability cannot be effectively estimated.This study selects 21 tight sandstone samples from the Q area within the shale oil formations of Ordos Basin.We systematically conduct the experiments to measure porosity,permeability,ultrasonic wave velocities,and resistivity at varying confining pressures.Results reveal that these measurements exhibit nonlinear changes in response to effective pressure.By using these experimental data and effective medium model,empirical relationships between P-and S-wave velocities,permeability and resistivity and effective pressure are established at logging and seismic scales.Furthermore,relationships between P-wave impedance and permeability,and resistivity and permeability are determined.A comparison between the predicted permeability and logging data demonstrates that the impedance–permeability relationship yields better results in contrast to those of resistivity–permeability relationship.These relationships are further applied to the seismic interpretation of shale oil reservoir in the target layer,enabling the permeability profile predictions based on inverse P-wave impedance.The predicted results are evaluated with actual production data,revealing a better agreement between predicted results and logging data and productivity.展开更多
基金supports from the National Natural Science Foundation of China(42104110,41974123,42174161,and 12334019)the Natural Science Foundation of Jiangsu Province(BK20210379,BK20200021)+1 种基金the Postdoctoral Science Foundation of China(2022M720989)the Fundamental Research Funds for the Central Universities(B210201032).
文摘The shale oil reservoir within the Yanchang Formations of Ordos Basin harbors substantial oil and gas resources and has recently emerged as the primary focus of unconventional oil and gas exploration and development.Due to its complex pore and throat structure,pronounced heterogeneity,and tight reservoir characteristics,the techniques for conventional oil and gas exploration and production face challenges in comprehensive implementation,also indicating that as a vital parameter for evaluating the physical properties of a reservoir,permeability cannot be effectively estimated.This study selects 21 tight sandstone samples from the Q area within the shale oil formations of Ordos Basin.We systematically conduct the experiments to measure porosity,permeability,ultrasonic wave velocities,and resistivity at varying confining pressures.Results reveal that these measurements exhibit nonlinear changes in response to effective pressure.By using these experimental data and effective medium model,empirical relationships between P-and S-wave velocities,permeability and resistivity and effective pressure are established at logging and seismic scales.Furthermore,relationships between P-wave impedance and permeability,and resistivity and permeability are determined.A comparison between the predicted permeability and logging data demonstrates that the impedance–permeability relationship yields better results in contrast to those of resistivity–permeability relationship.These relationships are further applied to the seismic interpretation of shale oil reservoir in the target layer,enabling the permeability profile predictions based on inverse P-wave impedance.The predicted results are evaluated with actual production data,revealing a better agreement between predicted results and logging data and productivity.
