High oil production from the Proterozoic formation of Shen 229 block in Damingtun Depression, Liaohe Basin, China, indicates the presence of natural fractured reservoir whose production potential is dominated by the s...High oil production from the Proterozoic formation of Shen 229 block in Damingtun Depression, Liaohe Basin, China, indicates the presence of natural fractured reservoir whose production potential is dominated by the structural fracture. A con- sistent structural model and good knowledge of the fracture systems are therefore of key importance in reducing risk in the de- velopment strategies. So data from cores and image logs have been collected to account for the basic characteristics of fracture, and then the analyzed results were integrated with the structural model in order to restrict the fracture network development during the structural evolvement. The structural evolution of the Proterozoic reservoir with time forms the basis for understanding the de- velopment of the 3D fracture system. Seismic interpretation and formation correlation were used to build a 3D geological model. The fault blocks that compose the Proterozoic formation reservoir were subsequently restored to their pre-deformation. From here, the structures were kinematically modeled to simulate the structural evolution of the reservoirs. At each time step, the dilatational and cumulative strain was calculated throughout the modelling history. The total strain which records the total spatial variation in the reservoir due to its structural history, together with core data, well data and the lithology distribution, was used to simulate geologically realistic discrete fracture networks. The benefit of this technique over traditional curvature analysis is that the structural evolution is taken into account, a factor that mostly dominates fracture formation.展开更多
Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological b...Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.展开更多
The study on seepage flow passing through single fractures is essential and critical for understanding of the law of seepage flow passing through fracture networks and the coupling mechanisms of seepage field and stre...The study on seepage flow passing through single fractures is essential and critical for understanding of the law of seepage flow passing through fracture networks and the coupling mechanisms of seepage field and stress field in rock masses.By using the fractal interpolation to reconstruct a natural coarse fracture,as well as taking into account the microstructure of the fracture,the numerical simulation of seepage flow passing through the coarse fractures with two distinct vertical scaling factors is conducted based on the MRT-LBM model of the lattice Boltzmann method.Then,after obtaining the length of the preferential flow pathway,the permeability of the two kinds of fractures is estimated respectively.In view of difficulties in locating the preferential flow pathway of natural fracture networks,by numerical tests a transect permeability weighted algorithm for estimating the fracture network permeability is proposed.The algorithm is not specific to one or more particular preferential flow pathways,but considers the contribution of each section to hinder the fluid passing through the medium.In order to apply the new algorithm,by capturing the structure of fracture networks based on the image-processing technique,the numerical simulations of seepage flow passing through two groups of natural fracture networks is carried out,the permeability is forecasted and the partial flows are reproduced for both cases.It is found that the preferential flow pathway emerges at the beginning of evolution,then is strengthened subsequently,and finally reaches a steady status.Furthermore,by using the proposed method some details on local flow can be clearly observed such as backflows and vortices at local branches can exist simultaneously and so forth,suggesting the validness of the proposed method for multiscale simulations of seepage flow.展开更多
文摘High oil production from the Proterozoic formation of Shen 229 block in Damingtun Depression, Liaohe Basin, China, indicates the presence of natural fractured reservoir whose production potential is dominated by the structural fracture. A con- sistent structural model and good knowledge of the fracture systems are therefore of key importance in reducing risk in the de- velopment strategies. So data from cores and image logs have been collected to account for the basic characteristics of fracture, and then the analyzed results were integrated with the structural model in order to restrict the fracture network development during the structural evolvement. The structural evolution of the Proterozoic reservoir with time forms the basis for understanding the de- velopment of the 3D fracture system. Seismic interpretation and formation correlation were used to build a 3D geological model. The fault blocks that compose the Proterozoic formation reservoir were subsequently restored to their pre-deformation. From here, the structures were kinematically modeled to simulate the structural evolution of the reservoirs. At each time step, the dilatational and cumulative strain was calculated throughout the modelling history. The total strain which records the total spatial variation in the reservoir due to its structural history, together with core data, well data and the lithology distribution, was used to simulate geologically realistic discrete fracture networks. The benefit of this technique over traditional curvature analysis is that the structural evolution is taken into account, a factor that mostly dominates fracture formation.
基金The study was supported by Open Fund of State Key Laboratory of Coal Resources and Safe Mining(Grant No.SKLCRSM19ZZ02)the National Natural Science Foundation of China(No.41702173)。
文摘Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.
基金supported by the National Basic Research Program of China("973"Project)(Grant No.2011CB013505)the National Natural Science Funds for Distinguished Young Scholar(Grant No.50925933)
文摘The study on seepage flow passing through single fractures is essential and critical for understanding of the law of seepage flow passing through fracture networks and the coupling mechanisms of seepage field and stress field in rock masses.By using the fractal interpolation to reconstruct a natural coarse fracture,as well as taking into account the microstructure of the fracture,the numerical simulation of seepage flow passing through the coarse fractures with two distinct vertical scaling factors is conducted based on the MRT-LBM model of the lattice Boltzmann method.Then,after obtaining the length of the preferential flow pathway,the permeability of the two kinds of fractures is estimated respectively.In view of difficulties in locating the preferential flow pathway of natural fracture networks,by numerical tests a transect permeability weighted algorithm for estimating the fracture network permeability is proposed.The algorithm is not specific to one or more particular preferential flow pathways,but considers the contribution of each section to hinder the fluid passing through the medium.In order to apply the new algorithm,by capturing the structure of fracture networks based on the image-processing technique,the numerical simulations of seepage flow passing through two groups of natural fracture networks is carried out,the permeability is forecasted and the partial flows are reproduced for both cases.It is found that the preferential flow pathway emerges at the beginning of evolution,then is strengthened subsequently,and finally reaches a steady status.Furthermore,by using the proposed method some details on local flow can be clearly observed such as backflows and vortices at local branches can exist simultaneously and so forth,suggesting the validness of the proposed method for multiscale simulations of seepage flow.
