利用4D地震数据校正储层静态模型的集合卡尔曼滤波方法
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摘要
储层静态模型是利用已知数据,结合先验性认识对未知储层空间进行插值预测,由此得到的结果与实际生产观测数据以及4D地震观测数据之间存在较大差异。基于集合卡尔曼滤波方法,通过观测数据反推系统模型的状态向量,对储层静态模型加以校正使得校正后的储层静态模型和观测数据之间差异最小化。选择4D地震属性差异作为观测数据,通过合理地抽取观测点,提高了运算效率。模型试验表明,校正后的静态模型能够较好地反映储层非均质性,并且与4D地震数据有较好的一致性。
The unknown reservoir properties are usually interpolated by using known data and priori knowledge. The results of the static model from this process could not agree well with production history and 4D seismic response. Taking the observation data as state vector,ensemble Kalman Filter (EnKF)is able to update the model and to minimize the mismatch of observed data and simulated data. Selecting 4D seismic attributes difference as observation data,the calculated efficiency is improved by choosing rational observation point. The updated models can represent heterogeneity of the reservoir and match the 4D seismic data well.
The unknown reservoir properties are usually interpolated by using known data and priori knowledge. The results of the static model from this process could not agree well with production history and 4D seismic response. Taking the observation data as state vector,ensemble Kalman Filter (EnKF)is able to update the model and to minimize the mismatch of observed data and simulated data. Selecting 4D seismic attributes difference as observation data,the calculated efficiency is improved by choosing rational observation point. The updated models can represent heterogeneity of the reservoir and match the 4D seismic data well.
引文
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[5]LORENTZEN R J,NAEVDAL G,VALLES B,et al.A-nalysis of the Ensemble Kalman Filter for estimation of permeability and porosity in reservoir models[R].SPE96375,2005.
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[7]LIU Ning,OLIVER DEAN S.Ensemble Kalman filter for automatic history matching of geologic fades[J].Journal of Petroleum Science and Engineering,2005,47:147-161.
[8]LIU N,OLIVER D S,OKLAHOMA U.Critical evalua-tion of the Ensemble Kalman Filter on history matching of geologic facies[R].SPE92867,2005.
[9]ZAFARI M,REYNOLDS A C.Assessing the uncertainty in reservoir description and performance predictions with the Ensemble Kalman Filter[R].SPE95750,2005.
[10]WEN X H,CHEN W H.Real-time reservoir model up-dating using Ensemble Kalman Filter[R].SPE92991,2005.
[11]GAO G,REYNOLDS A C.Quantifying uncertainty for the PUNQ-S3problem in a bayesian setting with RML and EnKF[R].SPE93324,2005.
[12]KHAZANEHDARI J,CURTIS T Yi T.Combined seis-micand production history matching[R].SPE97100,2005.
[13]SKJERVHEIM J A,CIPR U,EVENSEN G,et al.In-corporating4D seismic data in reservoir simulation mod-els using Ensemble Kalman Filter[R].SPE95789,2005.
[2]EVENSON G.The combined parameter and state estima-tion problem[J].Computational Geosciences,2005,9(1):1-39.
[3]NAEVDAL G,D-IANNSETH T,VEFRING E H.Near-well reservoir monitoring through Ensemble Kalman Filter[R].SPE75235,2002.
[4]GU Y,OLIVER D S.History matching of the PUNQ-S3reservoir model using the Ensemble Kalman Filter[R].SPE89942,2004.
[5]LORENTZEN R J,NAEVDAL G,VALLES B,et al.A-nalysis of the Ensemble Kalman Filter for estimation of permeability and porosity in reservoir models[R].SPE96375,2005.
[6]NXVDAL G,JOHNSON L M,AANONSEN S L,et al.Reservoir monitoring and continuous model updating using Ensemble Kalman Filter[R].SPE84372,2005.
[7]LIU Ning,OLIVER DEAN S.Ensemble Kalman filter for automatic history matching of geologic fades[J].Journal of Petroleum Science and Engineering,2005,47:147-161.
[8]LIU N,OLIVER D S,OKLAHOMA U.Critical evalua-tion of the Ensemble Kalman Filter on history matching of geologic facies[R].SPE92867,2005.
[9]ZAFARI M,REYNOLDS A C.Assessing the uncertainty in reservoir description and performance predictions with the Ensemble Kalman Filter[R].SPE95750,2005.
[10]WEN X H,CHEN W H.Real-time reservoir model up-dating using Ensemble Kalman Filter[R].SPE92991,2005.
[11]GAO G,REYNOLDS A C.Quantifying uncertainty for the PUNQ-S3problem in a bayesian setting with RML and EnKF[R].SPE93324,2005.
[12]KHAZANEHDARI J,CURTIS T Yi T.Combined seis-micand production history matching[R].SPE97100,2005.
[13]SKJERVHEIM J A,CIPR U,EVENSEN G,et al.In-corporating4D seismic data in reservoir simulation mod-els using Ensemble Kalman Filter[R].SPE95789,2005.
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