The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. De...The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.展开更多
塔河油田奥陶系油气藏储层非均质性极强,烃源岩长期生排烃、多期充注成藏及混合改造,导致油气性质变化大,给流体识别带来巨大挑战。通过模型正演,分析缝洞型储层厚度、孔隙度、含流体性质对AVO特征的影响,明确气藏、轻质油藏、重质油藏...塔河油田奥陶系油气藏储层非均质性极强,烃源岩长期生排烃、多期充注成藏及混合改造,导致油气性质变化大,给流体识别带来巨大挑战。通过模型正演,分析缝洞型储层厚度、孔隙度、含流体性质对AVO特征的影响,明确气藏、轻质油藏、重质油藏三种不同类型油气藏的AVO特征及敏感参数;在此基础上,开展叠前反演,获得地下不同流体纵波阻抗及纵横波速度比特征,然后基于实际测井数据,建立三种不同类型油气藏岩石物理量版,在岩石物理量版指导下,利用双参数进行流体概率分析,获得缝洞储层流体定量识别结果。对塔河A区(气藏)、B区(轻质油藏)和C区(重质油藏),各50 km 2三维地震资料开展基于叠前AVO反演的流体识别应用研究,将识别结果用于盲井检验,气藏识别符合率为80%,轻质油藏符合率为76%,重质油藏符合率为72%。研究结果为塔河碳酸盐岩储层流体识别提供了参考依据。展开更多
AVO (Amplitude variation with offset) technology is widely used in gas hydrate research. BSR (Bottom simulating reflector), caused by the huge difference in wave impedance between the hydrate reservoir and the underly...AVO (Amplitude variation with offset) technology is widely used in gas hydrate research. BSR (Bottom simulating reflector), caused by the huge difference in wave impedance between the hydrate reservoir and the underlying free gas reservoir, is the bottom boundary mark of the hydrate reservoir. Analyzing the AVO attributes of BSR can evaluate hydrate reservoirs. However, the Zoeppritz equation which is the theoretical basis of conventional AVO technology has inherent problems: the Zoeppritz equation does not consider the influence of thin layer thickness on reflection coefficients;the approximation of the Zoeppritz equation assumes that the difference of wave impedance between the two sides of the interface is small. These assumptions are not consistent with the occurrence characteristics of natural gas hydrate. The Brekhovskikh equation, which is more suitable for thin-layer reflection coefficient calculation, is used as the theoretical basis for AVO analysis. The reflection coefficients calculated by the Brekhovskikh equation are complex numbers with phase angles. Therefore, attributes of the reflection coefficient and its phase angle changing with offset are used to analyze the hydrate reservoir's porosity, saturation, and thickness. Finally, the random forest algorithm is used to predict the reservoir porosity, hydrate saturation, and thickness of the hydrate reservoir. In the synthetic data, the inversion results based on the four attributes of the Brekhovskikh equation are better than the conventional inversion results based on the two attributes of Zoeppritz, and the thickness can be accurately predicted. The proposed method also achieves good results in the application of Blake Ridge data. According to the method proposed in this paper, the hydrate reservoir in the area has a high porosity (more than 50%), and a medium saturation (between 10% and 20%). The thickness is mainly between 200m and 300m. It is consistent with the previous results obtained by velocity analysis.展开更多
Recently,the great potential of seismic dispersion attributes in oil and gas exploration has attracted extensive attention.The frequency-dependent amplitude versus offset(FAVO)technology,with dispersion gradient as a ...Recently,the great potential of seismic dispersion attributes in oil and gas exploration has attracted extensive attention.The frequency-dependent amplitude versus offset(FAVO)technology,with dispersion gradient as a hydrocarbon indicator,has developed rapidly.Based on the classical AVO theory,the technology works on the assumption that elastic parameters are frequency-dependent,and implements FAVO inversion using spectral decomposition methods,so that it can take dispersive effects into account and effectively overcome the limitations of the classical AVO.However,the factors that affect FAVO are complicated.To this end,we construct a unified equation for FAVO inversion by combining several Zoeppritz approximations.We study and compare two strategies respectively with(strategy 1)and without(strategy 2)velocity as inversion input data.Using theoretical models,we investigate the influence of various factors,such as the Zoeppritz approximation used,P-and S-wave velocity dispersion,inversion input data,the strong reflection caused by non-reservoir interfaces,and the noise level of the seismic data.Our results show that FAVO inversion based on different Zoeppritz approximations gives similar results.In addition,the inversion results of strategy 2 are generally equivalent to that of strategy 1,which means that strategy 2 can be used to obtain dispersion attributes even if the velocity is not available.We also found that the existence of non-reservoir strong reflection interface may cause significant false dispersion.Therefore,logging,geological,and other relevant data should be fully used to prevent this undesirable consequence.Both the P-and S-wave related dispersion obtained from FAVO can be used as good indicators of a hydrocarbon reservoir,but the P-wave dispersion is more reliable.In fact,due to the mutual coupling of P-and S-wave dispersion terms,the P-wave dispersion gradient inverted from PP reflection seismic data has a stronger hydrocarbon detection ability than the S-wave dispersion gradient.Moreover,there is little difference in using post-stack data or pre-stack angle gathers as inversion input when only the P-wave dispersion is desired.The real application examples further demonstrate that dispersion attributes can not only indicate the location of a hydrocarbon reservoir,but also,to a certain extent,reveal the physical properties of reservoirs.展开更多
文摘The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.
文摘塔河油田奥陶系油气藏储层非均质性极强,烃源岩长期生排烃、多期充注成藏及混合改造,导致油气性质变化大,给流体识别带来巨大挑战。通过模型正演,分析缝洞型储层厚度、孔隙度、含流体性质对AVO特征的影响,明确气藏、轻质油藏、重质油藏三种不同类型油气藏的AVO特征及敏感参数;在此基础上,开展叠前反演,获得地下不同流体纵波阻抗及纵横波速度比特征,然后基于实际测井数据,建立三种不同类型油气藏岩石物理量版,在岩石物理量版指导下,利用双参数进行流体概率分析,获得缝洞储层流体定量识别结果。对塔河A区(气藏)、B区(轻质油藏)和C区(重质油藏),各50 km 2三维地震资料开展基于叠前AVO反演的流体识别应用研究,将识别结果用于盲井检验,气藏识别符合率为80%,轻质油藏符合率为76%,重质油藏符合率为72%。研究结果为塔河碳酸盐岩储层流体识别提供了参考依据。
基金The research is funded by the National Natural Science Foundation of China(No.12171455)the Original Innovation Research Program of the Chinese Academy of Sciences(CAS)under grant number ZDBS-LY-DQC003the Key Research Programs IGGCAS-2019031.
文摘AVO (Amplitude variation with offset) technology is widely used in gas hydrate research. BSR (Bottom simulating reflector), caused by the huge difference in wave impedance between the hydrate reservoir and the underlying free gas reservoir, is the bottom boundary mark of the hydrate reservoir. Analyzing the AVO attributes of BSR can evaluate hydrate reservoirs. However, the Zoeppritz equation which is the theoretical basis of conventional AVO technology has inherent problems: the Zoeppritz equation does not consider the influence of thin layer thickness on reflection coefficients;the approximation of the Zoeppritz equation assumes that the difference of wave impedance between the two sides of the interface is small. These assumptions are not consistent with the occurrence characteristics of natural gas hydrate. The Brekhovskikh equation, which is more suitable for thin-layer reflection coefficient calculation, is used as the theoretical basis for AVO analysis. The reflection coefficients calculated by the Brekhovskikh equation are complex numbers with phase angles. Therefore, attributes of the reflection coefficient and its phase angle changing with offset are used to analyze the hydrate reservoir's porosity, saturation, and thickness. Finally, the random forest algorithm is used to predict the reservoir porosity, hydrate saturation, and thickness of the hydrate reservoir. In the synthetic data, the inversion results based on the four attributes of the Brekhovskikh equation are better than the conventional inversion results based on the two attributes of Zoeppritz, and the thickness can be accurately predicted. The proposed method also achieves good results in the application of Blake Ridge data. According to the method proposed in this paper, the hydrate reservoir in the area has a high porosity (more than 50%), and a medium saturation (between 10% and 20%). The thickness is mainly between 200m and 300m. It is consistent with the previous results obtained by velocity analysis.
基金This work is supported by the National Natural Science Foundation of China(42304141,41574103 and 41974120)the Joint Funds of the National Natural Science Foundation of China(U20B2015).
文摘Recently,the great potential of seismic dispersion attributes in oil and gas exploration has attracted extensive attention.The frequency-dependent amplitude versus offset(FAVO)technology,with dispersion gradient as a hydrocarbon indicator,has developed rapidly.Based on the classical AVO theory,the technology works on the assumption that elastic parameters are frequency-dependent,and implements FAVO inversion using spectral decomposition methods,so that it can take dispersive effects into account and effectively overcome the limitations of the classical AVO.However,the factors that affect FAVO are complicated.To this end,we construct a unified equation for FAVO inversion by combining several Zoeppritz approximations.We study and compare two strategies respectively with(strategy 1)and without(strategy 2)velocity as inversion input data.Using theoretical models,we investigate the influence of various factors,such as the Zoeppritz approximation used,P-and S-wave velocity dispersion,inversion input data,the strong reflection caused by non-reservoir interfaces,and the noise level of the seismic data.Our results show that FAVO inversion based on different Zoeppritz approximations gives similar results.In addition,the inversion results of strategy 2 are generally equivalent to that of strategy 1,which means that strategy 2 can be used to obtain dispersion attributes even if the velocity is not available.We also found that the existence of non-reservoir strong reflection interface may cause significant false dispersion.Therefore,logging,geological,and other relevant data should be fully used to prevent this undesirable consequence.Both the P-and S-wave related dispersion obtained from FAVO can be used as good indicators of a hydrocarbon reservoir,but the P-wave dispersion is more reliable.In fact,due to the mutual coupling of P-and S-wave dispersion terms,the P-wave dispersion gradient inverted from PP reflection seismic data has a stronger hydrocarbon detection ability than the S-wave dispersion gradient.Moreover,there is little difference in using post-stack data or pre-stack angle gathers as inversion input when only the P-wave dispersion is desired.The real application examples further demonstrate that dispersion attributes can not only indicate the location of a hydrocarbon reservoir,but also,to a certain extent,reveal the physical properties of reservoirs.
