地质统计学反演方法及其在薄层砂体预测中的应用
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摘要
地质统计学反演首先应用确定性反演方法得到波阻抗体,以了解储层的大致分布,并用于求取水平变差函数;然后从井点出发,井间遵从原始地震数据,通过随机模拟产生井间波阻抗,再将波阻抗转换成反射系数并与确定性反演方法求得的子波进行褶积产生合成地震道,通过反复迭代直至合成地震道与原始地震道达到一定程度的匹配.该方法有效地综合了地质、测井和三维地震数据,反演结果是多个等概率的波阻抗数据体实现,符合输入数据的地质统计学特征并受地质模型的约束,具有测井数据的垂向分辨率高和地震数据的横向分辨率高的优势,可用于不确定性评价.
In geostatistical inversion,first,wave impedance is obtained by using deterministic inversion methods in order to understand the general distribution of reservoirs and to get horizontal variogram;then,interwell wave impendence is produced by stochastic simulation based on original seismic data;third,the interwell wave impendence is transformed into reflection factor,the compose seismic traces are produced by the convolution of the wave impendence with the wavelets obtained by the deterministic inversion methods,the proper matching of the compose seismic traces with original seismic traces is reached by iterating again and again.The geostatistical inversion method integrates geologic,logging and 3D seismic data,and it combines the higher vertical resolution of logging data with the higher horizontal resolution of seismic data.The inversion result accords with the geostatictical characteristics of the input data and is restrained by geologic model.The several implementations of the inversion result are used for the non-deterministic assessment of the reservoirs.The applied result of the inversion method in Fuyu Oilfield in Jilin Province shows that,the geostatistical inversion method can effectively predict reservoirs,especially thinner reservoirs by integrating geologic,logging and 3D seismic data.
In geostatistical inversion,first,wave impedance is obtained by using deterministic inversion methods in order to understand the general distribution of reservoirs and to get horizontal variogram;then,interwell wave impendence is produced by stochastic simulation based on original seismic data;third,the interwell wave impendence is transformed into reflection factor,the compose seismic traces are produced by the convolution of the wave impendence with the wavelets obtained by the deterministic inversion methods,the proper matching of the compose seismic traces with original seismic traces is reached by iterating again and again.The geostatistical inversion method integrates geologic,logging and 3D seismic data,and it combines the higher vertical resolution of logging data with the higher horizontal resolution of seismic data.The inversion result accords with the geostatictical characteristics of the input data and is restrained by geologic model.The several implementations of the inversion result are used for the non-deterministic assessment of the reservoirs.The applied result of the inversion method in Fuyu Oilfield in Jilin Province shows that,the geostatistical inversion method can effectively predict reservoirs,especially thinner reservoirs by integrating geologic,logging and 3D seismic data.
引文
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[2]Dubrule O,Thibaut M,Lamy P,et al.Haas,Geostatisticalreservoir aracterization constrained by 3d seismic data[J].Petroleum science,1998(4):121-128.
[3]Rothman D H.Geostatistical inversion of 3-D seismic data forthin-sand delineation[J].Geophysics,1998,51(2):332-346.
[4]Carlos TV,Raghu K,Chunduru A.Integrated Interpretationof Wireline and 3D Seismic Data To Delineate Thin Oil-Pro-ducing Sands in San Jorge Basin[C].SPE87304,2003.
[5]Claire Sullivan,Eric Ekstrand,Tom Byrd,et al.Quantifyinguncertainty in reservoir properties using Geostatistical Inver-sion at the Holstein Field,Deepwater Gulf of Mexico[C]//SEG Int’l Exposition and 74th Annual MeetingDenver.Col-orado,2004:10-15.
[6]Artun E,Toro J,Wilson T.Reservoir Characterization Usinggeostatistical Inversion[C].SPE98012,2005.
[7]Agustin Medina,Jesus Carrera.Geostatistical inversion of cou-pled problems:dealing with computational burden and differ-ent types of data[J].Journal of Hydrology,2005,281:251-264.(下转第48页)
[8]Torres-Verdin C,Victoria M.Trace-based and Geostatis-tical inversion of 3-D seismic data for thin-sand delin-eation:An application in San Jorge Basin,Argentina[J].The Leading Edge,1999,18(9):1070-1077.
[9]John Pendrel,Miles Leggett,Peter Mesdag.GeostatisticalSimulation for Reservoir Characterization[C]//2004CSEG National Convention.2004:1-4.
[10]Torres-Verdín C,Grijalba-Cuenca A,Debeye H.A com-parison between geostatistical inversion and conventionalgeostatistical simulation practices for reservoir delineation[C]//AAPG Hedberg Research Conference on AppliedReservoir Characterization UsingGeostatistics.Wood-lands,2005,3-16.
[11]Rowbotham P S,Lamy P,Swaby P A.Geostatistical in-version for reservoir characterization[C]//2005 SEG Ex-panded Abstracts.2005:11-14.
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