The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the o...The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.展开更多
Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex str...Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.展开更多
Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppr...Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.展开更多
Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results ...Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.展开更多
Pre-stack seismic inversion is an important method for fluid identification and reservoir characterization in exploration geophysics. In this study, an effective fluid factor is initially established based on Biot por...Pre-stack seismic inversion is an important method for fluid identification and reservoir characterization in exploration geophysics. In this study, an effective fluid factor is initially established based on Biot poroelastic theory, and a pre-stack seismic inversion method based on Bayesian framework is used to implement the fluid identification. Compared with conventional elastic parameters, fluid factors are more sensitive to oil and gas. However, the coupling effect between rock porosity and fluid content is not considered in conventional fluid factors, which may lead to fuzzy fluid identification results. In addition,existing fluid factors do not adequately consider the physical mechanisms of fluid content, such as squirt flow between cracks and pores. Therefore, we propose a squirt fluid factor(SFF) that minimizes the fluid and pore mixing effects and takes into account the squirt flow. On this basis, a novel P-wave reflection coefficient equation is derived, and the squirt fluid factor is estimated by amplitude variation with offset(AVO) inversion method. The new reflection coefficient equation has sufficient accuracy and can be utilized to estimate the parameters. The effectiveness and superiority of the proposed method in fluid identification are verified by the synthetic and field examples.展开更多
To establish the relationship among reservoir characteristics and rock physical parameters,we construct the well-bore rock physical models firstly,considering the influence factors,such as mineral composition,shale co...To establish the relationship among reservoir characteristics and rock physical parameters,we construct the well-bore rock physical models firstly,considering the influence factors,such as mineral composition,shale content,porosity,fluid type and saturation.Then with analyzing the change rules of elastic parameters along with the above influence factors and the cross-plots among elastic parameters,the sensitive elastic parameters of tight sandstone reservoir are determined,and the rock physics template of sweet spot is constructed to guide pre-stack seismic inversion.The results show that velocity ratio and Poisson impedance are the most sensitive elastic parameters to indicate the lithologic and gas-bearing properties of sweet spot in tight sandstone reservoir.The high-quality sweet spot is characterized by the lower velocity ratio and Poisson impedance.Finally,the actual seismic data are selected to predict the sweet spots in tight sandstone gas reservoirs,so as to verify the validity of the rock physical simulation results.The significant consistency between the relative logging curves and inversion results in different wells implies that the utilization of well-bore rock physical simulation can guide the prediction of sweet spot in tight sandstone gas reservoirs.展开更多
基金supported by National Basic Research Program(2006CB202304)of Chinaco-supported by the National Basic Research Program of China(Grant No.2011CB201103)the National Science and Technology Major Project of China(Grant No.2011ZX05004003)
文摘The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.
基金We would like to acknowledge the sponsorship of the National Natural Science Foundation of China(42004092,42030103,41974119)Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001-6)Young Elite Scientists Sponsorship Program by CAST(2021QNRC001).
文摘Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.
基金supported by Fundamental Research Funds for the Central Universities,CHD300102264715National Key Research and Development Program of China under Grant 2021YFA0716902Natural Science Basic Research Program of Shaanxi 2024JCYBMS-199。
文摘Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.
基金supported by NSFC(41930425)Science Foundation of China University of Petroleum,Beijing(No.2462020YXZZ008)+1 种基金R&D Department of China National Petroleum Corporation(Investigations on fundamental experiments and advanced theoretical methods in geophysical prospecting applications(2022DQ0604-01)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-03)and NSFC(42274142).
文摘Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.
基金the sponsorship of National Natural Science Foundation of China (41974119, 42030103)Science Foundation from Innovation and Technology Support Program for Young Scientists in Colleges of Shandong Province and Ministry of Science and Technology of China (2019RA2136)Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) (2021QNLM020001-6)。
文摘Pre-stack seismic inversion is an important method for fluid identification and reservoir characterization in exploration geophysics. In this study, an effective fluid factor is initially established based on Biot poroelastic theory, and a pre-stack seismic inversion method based on Bayesian framework is used to implement the fluid identification. Compared with conventional elastic parameters, fluid factors are more sensitive to oil and gas. However, the coupling effect between rock porosity and fluid content is not considered in conventional fluid factors, which may lead to fuzzy fluid identification results. In addition,existing fluid factors do not adequately consider the physical mechanisms of fluid content, such as squirt flow between cracks and pores. Therefore, we propose a squirt fluid factor(SFF) that minimizes the fluid and pore mixing effects and takes into account the squirt flow. On this basis, a novel P-wave reflection coefficient equation is derived, and the squirt fluid factor is estimated by amplitude variation with offset(AVO) inversion method. The new reflection coefficient equation has sufficient accuracy and can be utilized to estimate the parameters. The effectiveness and superiority of the proposed method in fluid identification are verified by the synthetic and field examples.
基金supported by the National Key R&D Program of China(Grant No.2018YFC1405900)the Major Projects of National Science and Technology(Grant Nos.2016ZX05011-002,2016ZX05027-002-005)+3 种基金the National Natural Science Foundation of China(Grant No.41806073)the Natural Science Foundation of Shandong Province(Grant No.ZR2017BD014)Shandong Provincial Key Laboratory of Depositional Mineralization and Sedimentary Minerals,Shandong University of Science and Technology(Grant No.DMSM2017042)the Fundamental Research Funds for the Central Universities(Grant No.201964016)
文摘To establish the relationship among reservoir characteristics and rock physical parameters,we construct the well-bore rock physical models firstly,considering the influence factors,such as mineral composition,shale content,porosity,fluid type and saturation.Then with analyzing the change rules of elastic parameters along with the above influence factors and the cross-plots among elastic parameters,the sensitive elastic parameters of tight sandstone reservoir are determined,and the rock physics template of sweet spot is constructed to guide pre-stack seismic inversion.The results show that velocity ratio and Poisson impedance are the most sensitive elastic parameters to indicate the lithologic and gas-bearing properties of sweet spot in tight sandstone reservoir.The high-quality sweet spot is characterized by the lower velocity ratio and Poisson impedance.Finally,the actual seismic data are selected to predict the sweet spots in tight sandstone gas reservoirs,so as to verify the validity of the rock physical simulation results.The significant consistency between the relative logging curves and inversion results in different wells implies that the utilization of well-bore rock physical simulation can guide the prediction of sweet spot in tight sandstone gas reservoirs.
