The travel time and amplitude of ground-penetrating radar （GPR） waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, ...The travel time and amplitude of ground-penetrating radar （GPR） waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, which are mostly based on wave velocity, are not suitable for real complex media because of limited resolution. Impedance inversion uses the reflection coefficient of radar waves to directly calculate GPR impedance and other parameters of subsurface media. We construct a 3D multiscale stochastic medium model and use the mixed Gaussian and exponential autocorrelation function to describe the distribution of parameters in real subsurface media. We introduce an elliptical Gaussian function to describe local random anomalies. The tapering function is also introduced to reduce calculation errors caused by the numerical simulation of discrete grids. We derive the impedance inversion workflow and test the calculation precision in complex media. Finally, we use impedance inversion to process GPR field data in a polluted site in Mongolia. The inversion results were constrained using borehole data and validated by resistivity data.展开更多
Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoi...Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoing and upgoing waves can be accurately separated, we propose a method of predicting the impedance below the borehole in front of the bit using VSP data. First, the method of nonlinear iterative inversion is adopted to invert for impedance using the VSP corridor stack. Then, by modifying the damping factor in the iteration and using the preconditioned conjugate gradient method to solve the equations, the stability and convergence of the inversion results can be enhanced. The results of theoretical models and actual data demonstrate that the method is effective for pre-drilling prediction using VSP data.展开更多
Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven method...Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.展开更多
The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth...The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain.It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain.We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet.The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations.Incorporating the weighted superposition principle,a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain.An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm,which avoids additional data conversions between the time and depth domains.The impedance inversions of the synthetic and field seismic data in the depth domain show good results,which demonstrates that seismic inversion in the depth domain is feasible.The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data.It is advantageous for further studies concerning the stability,accuracy,and efficiency of seismic inversions in the depth domain.展开更多
Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geoph...Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.展开更多
The origin and distribution of formation overpressure have effect not only on hydrocarbon migration and accumulation, but also on technique of drilling well. The study and prediction of overpressure are very important...The origin and distribution of formation overpressure have effect not only on hydrocarbon migration and accumulation, but also on technique of drilling well. The study and prediction of overpressure are very important in basin analysis. At present, overpressure is mostly predicted by stack velocity. The process in calculating inter-velocity from stack velocity is very complex and inevitably leads to errors. Especially, this method is not available in the case that structural compression contribution to overpressure occurred. This paper introduces a new method, impedance inversion, to predict overpressure, and the principle is discussed. This method is used to predict the overpressure in Kuqa depression, Tarim basin and as a result, the absolute errors are less than 0.1, and relative errors are less than 5 % for predicted fluid pressure coefficients to the drill stem test (DST) measurements. It suggests that this method can be widely used to predict overpressure in foreland basins.展开更多
The conventional poststack inversion uses standard recursion formulas to obtain impedance in a single trace.It cannot allow for lateral regularization.In this paper,ID edge-preserving smoothing(EPS)fi lter is extended...The conventional poststack inversion uses standard recursion formulas to obtain impedance in a single trace.It cannot allow for lateral regularization.In this paper,ID edge-preserving smoothing(EPS)fi lter is extended to 2D/3D for setting precondition of impedance model in impedance inversion.The EPS filter incorporates a priori knowledge into the seismic inversion.The a priori knowledge incorporated from EPS filter preconditioning relates to the blocky features of the impedance model,which makes the formation interfaces and geological edges precise and keeps the inversion procedure robust.Then,the proposed method is performed on two 2D models to show its feasibility and stability.Last,the proposed method is performed on a real 3D seismic work area from Southwest China to predict reef reservoirs in practice.展开更多
The reflection coefficient solved by using the traditional impedance inversion method cannot reflect low-frequency information sufficiently and its continuity and resolution are limited,so the quality and resolution o...The reflection coefficient solved by using the traditional impedance inversion method cannot reflect low-frequency information sufficiently and its continuity and resolution are limited,so the quality and resolution of impedance inversion are impacted seriously.In this paper,the advantages of rich low-frequency signals were discussed with the theoretical synthetic seismogram and wavelet simulation as the fulcrum.Then,the low-frequency sparse double-constrained reflection coefficient method was introduced to modify the sparse optimization item,and thus a new method was formed.Finally,based on the broadband data and non-broadband data of the actual work area,the reflection coefficient and impedance inversion solved by the traditional basis-pursuit reflection coefficient inversion were compared and then the calculation results of low-frequency sparse double-constrained reflection coefficient inversion were compared to verify the effect of the modified method.And the following research results were obtained.First,the broadband data with rich low-frequency information is less affected by the side lobe,and its seismic data resolution is higher,which is more favorable for the improvement of inversion accuracy and resolution.Second,in the new method,the L2 norm low-frequency model is added on the basis of the BPDN basis-pursuit denoising problem to constrain the residual,so as to realize the direct solution of the reflection coefficient with low-frequency information.Third,the reflection coefficient and wave impedance solved by using the new method have better continuity and resolution than those solved by using the traditional method and they are in good agreement with the well data.In conclusion,the new method achieves higher resolution on the impedance inversion of broadband data and non-broadband data and the accuracy of impedance inversion is increased,so it has higher application values in predicting the distribution of thin reservoirs.展开更多
Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain M...Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo （MCMC） method is proposed in this paper, combining conventional MCMC method based on global optimization with a preconditioned conjugate gradient （PCG） algorithm based on local optimization, so this method does not depend strongly on the initial model. It converges to the global optimum quickly and efficiently on the condition that effi- ciency and stability of inversion are both taken into consid- eration at the same time. The test data verify the feasibility and robustness of the method, and based on this method, we extract the effective pore-fluid bulk modulus, which is applied to reservoir fluid identification and detection, and consequently, a better result has been achieved.展开更多
The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution....The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the Ll-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.展开更多
The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocit...The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocity, S-velocity, and density data directly and the elastic impedance at different incidence angles are not at the same scale, which makes comparison difficult. We propose a new elastic impedance equation based on the Gray et al. （1999） Zoeppritz approximation using Lamé parameters to address the conventional inversion method＇s deficiencies. This equation has been normalized to unify the elastic impedance dimensions at different angles and used for inversion. Lamé parameters can be extracted directly from the elastic impedance data obtained from inversion using the linear relation between Lamé parameters and elastic impedance. The application example shows that the elastic parameters extracted using this new method are more stable and correct and can recover the reservoir information very well. The new method is an improvement on the conventional method based on Connolly＇s equation.展开更多
Accurate estimation of fracture density and orientation is of great significance for seismic characterization of fractured reservoirs.Here,we propose a novel methodology to estimate fracture density and orientation fr...Accurate estimation of fracture density and orientation is of great significance for seismic characterization of fractured reservoirs.Here,we propose a novel methodology to estimate fracture density and orientation from azimuthal elastic impedance(AEI)difference using singular value decomposition(SVD).Based on Hudson's model,we first derive the AEI equation containing fracture density in HTI media,and then obtain basis functions and singular values from the normalized AEI difference utilizing SVD.Analysis shows that the basis function changing with azimuth is related to fracture orientation,fracture density is the linearly weighted sum of singular values,and the first singular value contributes the most to fracture density.Thus,we develop an SVD-based fracture density and orientation inversion approach constrained by smooth prior elastic parameters.Synthetic example shows that fracture density and orientation can be stably estimated,and the correlation coefficient between the true value and the estimated fracture density is above 0.85 even when an S/N ratio of 2.Field data example shows that the estimated fracture orientation is consistent with the interpretation of image log data,and the estimated fracture density reliably indicates fractured gas-bearing reservoir,which could help to guide the exploration and development of fractured reservoirs.展开更多
The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained...The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.展开更多
In the conditions of low Signal-to-Noise Ratio(SNR) of seismic data and a small quality of log information,the consequences of seismic interpretation through the impedance inversion of seismic data could be more preci...In the conditions of low Signal-to-Noise Ratio(SNR) of seismic data and a small quality of log information,the consequences of seismic interpretation through the impedance inversion of seismic data could be more precise. Constrained sparse spike inversion(CSSI) has advantage in oil and gas reservoir predication because it does not rely on the original model. By analyzing the specific algorithm of CSSI,the accuracy of inversion is controlled. Oriente Basin in South America has the low amplitude in geological structure and complex lithologic trap. The well predication is obtained by the application of CSSI.展开更多
A sedimentary geological model is established in order to study the seismic reflection characteristics of channel sand bodies. Synthetic seismic shot gathers are simulated using the acoustic wave equation and then are...A sedimentary geological model is established in order to study the seismic reflection characteristics of channel sand bodies. Synthetic seismic shot gathers are simulated using the acoustic wave equation and then are prestack time migrated. On the imaged data, the reflection characteristics and instantaneous attributes are analyzed and log-constrained impedance inversion is tested. Because of wave field interference, the experimental results show that seismic events do not definitely correspond to the channel sand bodies and that seismic modes of occurrence do not represent the actual ones. The seismic events formed by wave interference may lead to errors and pitfalls in sand body interpretation. The corresponding relations between instantaneous seismic attributes and sedimentary sands are not well established. Log-constrained impedance inversion improves the resolution of channel sands. However, if the inverted resolution is forced to be too high, artifacts related to the initial model may occur.展开更多
The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which ...The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which are suitable for fractured and caved carbonate reservoir prediction is discussed,including amplitude,coherence analysis,spectra decomposition,seismic absorption attenuation analysis and impedance inversion.Moreover,3-D optimization of these attributes is achieved by integration of multivariate discriminant analysis and principle component analysis,where the logging data are taken as training samples.Using the optimized results,the spatial distribution and configuration features of the caved reservoirs can be characterized in detail.This technique not only improves the understanding of the spatial distribution of current reservoirs but also provides a significant basis for the discovery and production of carbonate reservoirs in the Tarim Basin.展开更多
The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, ne...The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, near sources and intensive tectonic activity. This work was focused on the sedimentary feature of the glutenite segment to conduct the seismic sedimentology research. The near-shore subaqueous fans and its relative gravity channel and slump turbidite fan depositions were identified according to observation and description of cores combining with the numerous data of seismic and logging. Then, the depositional model was built depending on the analysis of palaeogeomorphology. The seismic attributes which are related to the hydrocarbon but relative independent were chosen to conduct the analysis, the reservoir area of the glutenite segment was found performing a distribution where the amplitude value is relatively higher, and finally the RMS amplitude attribute was chosen to conduct the attribute predicting. At the same time, the horizontal distribution of the sedimentary facies was analyzed qualitatively. At last, the sparse spike inversion method was used to conduct the acoustic impedance inversion, and the inversion result can distinguish glutenite reservoir which is greater than 5 m. This method quantitatively characterizes the distribution area of the favorable reservoir sand.展开更多
基金supported by the Doctoral Fund Project of the Ministry of Education(No.20130061110060 class tutors)the Post-Doctoral Fund Project(No.2015M571366)+1 种基金the National Natural Science Foundation of China(No.41174097)US DoD ARO Project"Advanced Mathematical Algorithm"(No.W911NF-11-2-0046)
文摘The travel time and amplitude of ground-penetrating radar （GPR） waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, which are mostly based on wave velocity, are not suitable for real complex media because of limited resolution. Impedance inversion uses the reflection coefficient of radar waves to directly calculate GPR impedance and other parameters of subsurface media. We construct a 3D multiscale stochastic medium model and use the mixed Gaussian and exponential autocorrelation function to describe the distribution of parameters in real subsurface media. We introduce an elliptical Gaussian function to describe local random anomalies. The tapering function is also introduced to reduce calculation errors caused by the numerical simulation of discrete grids. We derive the impedance inversion workflow and test the calculation precision in complex media. Finally, we use impedance inversion to process GPR field data in a polluted site in Mongolia. The inversion results were constrained using borehole data and validated by resistivity data.
文摘Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoing and upgoing waves can be accurately separated, we propose a method of predicting the impedance below the borehole in front of the bit using VSP data. First, the method of nonlinear iterative inversion is adopted to invert for impedance using the VSP corridor stack. Then, by modifying the damping factor in the iteration and using the preconditioned conjugate gradient method to solve the equations, the stability and convergence of the inversion results can be enhanced. The results of theoretical models and actual data demonstrate that the method is effective for pre-drilling prediction using VSP data.
基金financially supported by the Important National Science&Technology Specific Project of China(Grant No.2017ZX05018-005)
文摘Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.
基金supported by the National Natural Science Foundation of China(No.41574130,41874143 and 41374134)the National Science and Technology Major Project of China(No.2016ZX05014-001-009)the Sichuan Provincial Youth Science&Technology Innovative Research Group Fund(No.2016TD0023)
文摘The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain.It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain.We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet.The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations.Incorporating the weighted superposition principle,a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain.An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm,which avoids additional data conversions between the time and depth domains.The impedance inversions of the synthetic and field seismic data in the depth domain show good results,which demonstrates that seismic inversion in the depth domain is feasible.The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data.It is advantageous for further studies concerning the stability,accuracy,and efficiency of seismic inversions in the depth domain.
基金funded by R&D Department of China National Petroleum Corporation(2022DQ0604-04)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-03)the Science Research and Technology Development of PetroChina(2021DJ1206).
文摘Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.
文摘The origin and distribution of formation overpressure have effect not only on hydrocarbon migration and accumulation, but also on technique of drilling well. The study and prediction of overpressure are very important in basin analysis. At present, overpressure is mostly predicted by stack velocity. The process in calculating inter-velocity from stack velocity is very complex and inevitably leads to errors. Especially, this method is not available in the case that structural compression contribution to overpressure occurred. This paper introduces a new method, impedance inversion, to predict overpressure, and the principle is discussed. This method is used to predict the overpressure in Kuqa depression, Tarim basin and as a result, the absolute errors are less than 0.1, and relative errors are less than 5 % for predicted fluid pressure coefficients to the drill stem test (DST) measurements. It suggests that this method can be widely used to predict overpressure in foreland basins.
基金The National Key S&T Special Projects (No. 2017ZX05008004-008)the National Natural Science Foundation of China (No. 41874146)+2 种基金the National Natural Science Foundation of China (No. 41704134)the Innovation Team of Youth Scientific and Technological in Southwest Petroleum University (No. 2017CXTD08)the Initiative Projects for Ph.Din China West Normal University (No. 19E063)
文摘The conventional poststack inversion uses standard recursion formulas to obtain impedance in a single trace.It cannot allow for lateral regularization.In this paper,ID edge-preserving smoothing(EPS)fi lter is extended to 2D/3D for setting precondition of impedance model in impedance inversion.The EPS filter incorporates a priori knowledge into the seismic inversion.The a priori knowledge incorporated from EPS filter preconditioning relates to the blocky features of the impedance model,which makes the formation interfaces and geological edges precise and keeps the inversion procedure robust.Then,the proposed method is performed on two 2D models to show its feasibility and stability.Last,the proposed method is performed on a real 3D seismic work area from Southwest China to predict reef reservoirs in practice.
基金supported by the National Natural Science Foundation of China“Fluid Identification and Fluid Mobility Prediction Based on Frequency-Variable Information”(No.41774142)“Extraction of Frequency-Variable Information and Its Application in Reservoir Prediction”(No.4167040416).
文摘The reflection coefficient solved by using the traditional impedance inversion method cannot reflect low-frequency information sufficiently and its continuity and resolution are limited,so the quality and resolution of impedance inversion are impacted seriously.In this paper,the advantages of rich low-frequency signals were discussed with the theoretical synthetic seismogram and wavelet simulation as the fulcrum.Then,the low-frequency sparse double-constrained reflection coefficient method was introduced to modify the sparse optimization item,and thus a new method was formed.Finally,based on the broadband data and non-broadband data of the actual work area,the reflection coefficient and impedance inversion solved by the traditional basis-pursuit reflection coefficient inversion were compared and then the calculation results of low-frequency sparse double-constrained reflection coefficient inversion were compared to verify the effect of the modified method.And the following research results were obtained.First,the broadband data with rich low-frequency information is less affected by the side lobe,and its seismic data resolution is higher,which is more favorable for the improvement of inversion accuracy and resolution.Second,in the new method,the L2 norm low-frequency model is added on the basis of the BPDN basis-pursuit denoising problem to constrain the residual,so as to realize the direct solution of the reflection coefficient with low-frequency information.Third,the reflection coefficient and wave impedance solved by using the new method have better continuity and resolution than those solved by using the traditional method and they are in good agreement with the well data.In conclusion,the new method achieves higher resolution on the impedance inversion of broadband data and non-broadband data and the accuracy of impedance inversion is increased,so it has higher application values in predicting the distribution of thin reservoirs.
基金the sponsorship of the National Basic Research Program of China (973 Program,2013CB228604,2014CB239201)the National Oil and Gas Major Projects of China (2011ZX05014-001-010HZ,2011ZX05014-001-006-XY570) for their funding of this research
文摘Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo （MCMC） method is proposed in this paper, combining conventional MCMC method based on global optimization with a preconditioned conjugate gradient （PCG） algorithm based on local optimization, so this method does not depend strongly on the initial model. It converges to the global optimum quickly and efficiently on the condition that effi- ciency and stability of inversion are both taken into consid- eration at the same time. The test data verify the feasibility and robustness of the method, and based on this method, we extract the effective pore-fluid bulk modulus, which is applied to reservoir fluid identification and detection, and consequently, a better result has been achieved.
基金Projects(U1562215,41674130,41404088)supported by the National Natural Science Foundation of ChinaProjects(2013CB228604,2014CB239201)supported by the National Basic Research Program of China+1 种基金Projects(2016ZX05027004-001,2016ZX05002006-009)supported by the National Oil and Gas Major Projects of ChinaProject(15CX08002A)supported by the Fundamental Research Funds for the Central Universities,China
文摘The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the Ll-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.
文摘The Connolly （1999） elastic impedance （EI） equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocity, S-velocity, and density data directly and the elastic impedance at different incidence angles are not at the same scale, which makes comparison difficult. We propose a new elastic impedance equation based on the Gray et al. （1999） Zoeppritz approximation using Lamé parameters to address the conventional inversion method＇s deficiencies. This equation has been normalized to unify the elastic impedance dimensions at different angles and used for inversion. Lamé parameters can be extracted directly from the elastic impedance data obtained from inversion using the linear relation between Lamé parameters and elastic impedance. The application example shows that the elastic parameters extracted using this new method are more stable and correct and can recover the reservoir information very well. The new method is an improvement on the conventional method based on Connolly＇s equation.
基金sponsorship of the National Natural Science Foundation of China(41674130,U19B2008)the Postgraduate Innovation Project in China University of Petroleum(East China)(YCX2021016)for their funding this research。
文摘Accurate estimation of fracture density and orientation is of great significance for seismic characterization of fractured reservoirs.Here,we propose a novel methodology to estimate fracture density and orientation from azimuthal elastic impedance(AEI)difference using singular value decomposition(SVD).Based on Hudson's model,we first derive the AEI equation containing fracture density in HTI media,and then obtain basis functions and singular values from the normalized AEI difference utilizing SVD.Analysis shows that the basis function changing with azimuth is related to fracture orientation,fracture density is the linearly weighted sum of singular values,and the first singular value contributes the most to fracture density.Thus,we develop an SVD-based fracture density and orientation inversion approach constrained by smooth prior elastic parameters.Synthetic example shows that fracture density and orientation can be stably estimated,and the correlation coefficient between the true value and the estimated fracture density is above 0.85 even when an S/N ratio of 2.Field data example shows that the estimated fracture orientation is consistent with the interpretation of image log data,and the estimated fracture density reliably indicates fractured gas-bearing reservoir,which could help to guide the exploration and development of fractured reservoirs.
基金supported by the National Key R&D Program of China (No.2021YFC2801202)the National Natural Science Foundation of China (No.42076224)the Fundamental Research Funds for the Central Universities (No.202262012)。
文摘The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.
基金Supported by the Fundamental Research Funds for the Central Universities(No.2011PY0186)
文摘In the conditions of low Signal-to-Noise Ratio(SNR) of seismic data and a small quality of log information,the consequences of seismic interpretation through the impedance inversion of seismic data could be more precise. Constrained sparse spike inversion(CSSI) has advantage in oil and gas reservoir predication because it does not rely on the original model. By analyzing the specific algorithm of CSSI,the accuracy of inversion is controlled. Oriente Basin in South America has the low amplitude in geological structure and complex lithologic trap. The well predication is obtained by the application of CSSI.
基金National 973 Key Basic Research Development Program(No.2007CB209608)National 863 High Technology Research Development Program(No.2007AA06Z218)
文摘A sedimentary geological model is established in order to study the seismic reflection characteristics of channel sand bodies. Synthetic seismic shot gathers are simulated using the acoustic wave equation and then are prestack time migrated. On the imaged data, the reflection characteristics and instantaneous attributes are analyzed and log-constrained impedance inversion is tested. Because of wave field interference, the experimental results show that seismic events do not definitely correspond to the channel sand bodies and that seismic modes of occurrence do not represent the actual ones. The seismic events formed by wave interference may lead to errors and pitfalls in sand body interpretation. The corresponding relations between instantaneous seismic attributes and sedimentary sands are not well established. Log-constrained impedance inversion improves the resolution of channel sands. However, if the inverted resolution is forced to be too high, artifacts related to the initial model may occur.
基金co-supported by the National Basic Resarch Program of China (Grant No.2011CB201103)the National Scince and Technology Major Project (Grant No.2011ZX05004003)
文摘The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which are suitable for fractured and caved carbonate reservoir prediction is discussed,including amplitude,coherence analysis,spectra decomposition,seismic absorption attenuation analysis and impedance inversion.Moreover,3-D optimization of these attributes is achieved by integration of multivariate discriminant analysis and principle component analysis,where the logging data are taken as training samples.Using the optimized results,the spatial distribution and configuration features of the caved reservoirs can be characterized in detail.This technique not only improves the understanding of the spatial distribution of current reservoirs but also provides a significant basis for the discovery and production of carbonate reservoirs in the Tarim Basin.
基金Project(41172109)supported by the National Natural Science Foundation of ChinaProject(20110003110014)supported by the ResearchFoundation for the Doctoral Program of Higher Education,China
文摘The sand-conglomerate fans are the major depositional systems in the lower third member of Shahejie Formation in Shengtuo area, which formed in the deep lacustrine environment characterized by steep slope gradient, near sources and intensive tectonic activity. This work was focused on the sedimentary feature of the glutenite segment to conduct the seismic sedimentology research. The near-shore subaqueous fans and its relative gravity channel and slump turbidite fan depositions were identified according to observation and description of cores combining with the numerous data of seismic and logging. Then, the depositional model was built depending on the analysis of palaeogeomorphology. The seismic attributes which are related to the hydrocarbon but relative independent were chosen to conduct the analysis, the reservoir area of the glutenite segment was found performing a distribution where the amplitude value is relatively higher, and finally the RMS amplitude attribute was chosen to conduct the attribute predicting. At the same time, the horizontal distribution of the sedimentary facies was analyzed qualitatively. At last, the sparse spike inversion method was used to conduct the acoustic impedance inversion, and the inversion result can distinguish glutenite reservoir which is greater than 5 m. This method quantitatively characterizes the distribution area of the favorable reservoir sand.
