The phase velocity of seismic waves varies with the propagation frequency, and thus frequency-dependent phenomena appear when CO2 gas is injected into a reservoir. By dynamically considering these phenomena with reser...The phase velocity of seismic waves varies with the propagation frequency, and thus frequency-dependent phenomena appear when CO2 gas is injected into a reservoir. By dynamically considering these phenomena with reservoir conditions it is thus feasible to extract the frequency-dependent velocity factor with the aim of monitoring changes in the reservoir both before and after CO2 injection. In the paper, we derive a quantitative expression for the frequency-dependent factor based on the Robinson seismic convolution model. In addition, an inversion equation with a frequency-dependent velocity factor is constructed, and a procedure is implemented using the following four processing steps： decomposition of the spectrum by generalized S transform, wavelet extraction of cross-well seismic traces, spectrum equalization processing, and an extraction method for frequency-dependent velocity factor based on the damped least-square algorithm. An attenuation layered model is then established based on changes in the Q value of the viscoelastic medium, and spectra of migration profiles from forward modeling are obtained and analyzed. Frequency-dependent factors are extracted and compared, and the effectiveness of the method is then verified using a synthetic data. The frequency-dependent velocity factor is finally applied to target processing and oil displacement monitoring based on real seismic data obtained before and after CO2 injection in the G89 well block within Shengli oilfield. Profiles and slices of the frequency-dependent factor determine its ability to indicate differences in CO2 flooding, and the predicting results are highly consistent with those of practical investigations within the well block.展开更多
In order to build a model for the Chang-8 low permeability sandstone reservoir in the Yanchang formation of the Xifeng oil field,we studied sedimentation and diagenesis of sandstone and analyzed major factors controll...In order to build a model for the Chang-8 low permeability sandstone reservoir in the Yanchang formation of the Xifeng oil field,we studied sedimentation and diagenesis of sandstone and analyzed major factors controlling this low permeability reservoir.By doing so,we have made clear that the spatial distribution of reservoir attribute parameters is controlled by the spatial distribution of various kinds of sandstone bodies.By taking advantage of many coring wells and high quality logging data,we used regression analysis for a single well with geological conditions as constraints,to build the interpretation model for logging data and to calculate attribute parameters for a single well,which ensured accuracy of the 1-D vertical model.On this basis,we built a litho-facies model to replace the sedimentary facies model.In addition,we also built a porosity model by using a sequential Gaussian simulation with the lithofacies model as the constraint.In the end,we built a permeability model by using Markov-Bayes simula-tion,with the porosity attribute as the covariate.The results show that the permeability model reflects very well the relative differences between low permeability values,which is of great importance for locating high permeability zones and forecasting zones favorable for exploration and exploitation.展开更多
Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionl...Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.展开更多
Dynamic exploration for oil and gas requires careful monitoring of reservoir contents for safety and efficiency of oil extraction. This paper proposes a multi-source and multi-azimuth walk-around vertical electromagne...Dynamic exploration for oil and gas requires careful monitoring of reservoir contents for safety and efficiency of oil extraction. This paper proposes a multi-source and multi-azimuth walk-around vertical electromagnetic profiling （MM-VEP） technique for surface-to-borehole electromagnetic surveying. Based on the difference in conductivities between reservoirs with different concentrations of oil and water, MM-VEP can be used to monitor reservoirs as they are injected with water. The MM-VEP response in five azimuth planes is modeled with three-dimensional （3D） integral equation calculations. The progress of waterflooding in four stages for enhanced oil recovery is shown to be indicated by field anomalies MM-VEP caused by variations in the reservoir resistivity. Numerical modeling demonstrates that MM-VEP measurements provides enough quantitative information from an underground reservoir to accurately detect oil deposits and monitor the progress of waterflooding.展开更多
基金supported by the Pilot Project of Sinopec(P14085)
文摘The phase velocity of seismic waves varies with the propagation frequency, and thus frequency-dependent phenomena appear when CO2 gas is injected into a reservoir. By dynamically considering these phenomena with reservoir conditions it is thus feasible to extract the frequency-dependent velocity factor with the aim of monitoring changes in the reservoir both before and after CO2 injection. In the paper, we derive a quantitative expression for the frequency-dependent factor based on the Robinson seismic convolution model. In addition, an inversion equation with a frequency-dependent velocity factor is constructed, and a procedure is implemented using the following four processing steps： decomposition of the spectrum by generalized S transform, wavelet extraction of cross-well seismic traces, spectrum equalization processing, and an extraction method for frequency-dependent velocity factor based on the damped least-square algorithm. An attenuation layered model is then established based on changes in the Q value of the viscoelastic medium, and spectra of migration profiles from forward modeling are obtained and analyzed. Frequency-dependent factors are extracted and compared, and the effectiveness of the method is then verified using a synthetic data. The frequency-dependent velocity factor is finally applied to target processing and oil displacement monitoring based on real seismic data obtained before and after CO2 injection in the G89 well block within Shengli oilfield. Profiles and slices of the frequency-dependent factor determine its ability to indicate differences in CO2 flooding, and the predicting results are highly consistent with those of practical investigations within the well block.
基金Project 50374048 supported by the National Natural Science Foundation of China
文摘In order to build a model for the Chang-8 low permeability sandstone reservoir in the Yanchang formation of the Xifeng oil field,we studied sedimentation and diagenesis of sandstone and analyzed major factors controlling this low permeability reservoir.By doing so,we have made clear that the spatial distribution of reservoir attribute parameters is controlled by the spatial distribution of various kinds of sandstone bodies.By taking advantage of many coring wells and high quality logging data,we used regression analysis for a single well with geological conditions as constraints,to build the interpretation model for logging data and to calculate attribute parameters for a single well,which ensured accuracy of the 1-D vertical model.On this basis,we built a litho-facies model to replace the sedimentary facies model.In addition,we also built a porosity model by using a sequential Gaussian simulation with the lithofacies model as the constraint.In the end,we built a permeability model by using Markov-Bayes simula-tion,with the porosity attribute as the covariate.The results show that the permeability model reflects very well the relative differences between low permeability values,which is of great importance for locating high permeability zones and forecasting zones favorable for exploration and exploitation.
基金Project(2011ZX05009-004)supported by the National Science and Technology Major Projects of China
文摘Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.
基金supported by the National Science and Technology Major Project(No.2011ZX05019-007)National Natural Science Foundation of China(No.41604097)+1 种基金China Postdoctoral Science Foundation(No.2016M592611)Project(Nos.002401003503 and 002401003514)from Guilin University of Technology
文摘Dynamic exploration for oil and gas requires careful monitoring of reservoir contents for safety and efficiency of oil extraction. This paper proposes a multi-source and multi-azimuth walk-around vertical electromagnetic profiling （MM-VEP） technique for surface-to-borehole electromagnetic surveying. Based on the difference in conductivities between reservoirs with different concentrations of oil and water, MM-VEP can be used to monitor reservoirs as they are injected with water. The MM-VEP response in five azimuth planes is modeled with three-dimensional （3D） integral equation calculations. The progress of waterflooding in four stages for enhanced oil recovery is shown to be indicated by field anomalies MM-VEP caused by variations in the reservoir resistivity. Numerical modeling demonstrates that MM-VEP measurements provides enough quantitative information from an underground reservoir to accurately detect oil deposits and monitor the progress of waterflooding.
