储层参数岩石物理反演在“甜点”储层预测中应用研究——以W17油田为例
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摘要
乌石凹陷流砂港组地层岩石粒度变化大,低孔、低渗目标占比近50%,"甜点"储层预测是实现油田经济开发的关键因素,而储层孔隙度、黏土杂积含量评价是"甜点"储层预测的核心问题.本文应用一种新的直接求解包体理论岩石物理方程的储层参数反演方法来进行"甜点"储层评价,该反演方法基于约束最小二乘与信赖域算法直接求解有效介质包体理论岩石物理方程,能够关联弹性参数与储层参数之间的高阶变化,可反演地质体孔隙度、黏土含量空间细节变化特征,通过孔隙度、黏土含量双参数约束实现"甜点"储层分布评价.本文以W17油田为例,首先通过岩石物理分析明确常规储层与"甜点"储层的岩石物理规律;然后运用相控叠前地质统计学反演技术得到高分辨率敏感弹性参数体;最后开展孔隙度、黏土含量储层参数岩石物理反演和"甜点"储层预测.通过与当前业界常用的基于统计关系的地质统计学协模拟储层参数评价方法结果进行对比得到,本次研究应用的储层参数岩石物理反演方法得到的地质体内部细节丰富,盲井预测孔隙度及黏土含量参数精度提高,具有精细刻度储层内部的参数变化,保持弹性反演的分辨精度等优势,有利于解决"甜点"储层连通性及非均质性评价等难点问题.
The main Liushagang formation rock of Wushi geology structure has the feature of wide particle size distribution, low porosity and low permeability, whereas those kind of reservoir rock is accounted nearly 50 percent in the whole. "Sweet Spot" prediction is the most important factor to realize this oilfield's development economically. Reservoir porosity and clay volume evaluation are the key questions to establish "Sweet Spot" prediction successfully. A new rock physics inversion method was applied to "Sweet Spot" prediction in this paper. This method solves effective media inclusion model function directly by constrained least squares and trust region approach, and can link the elastic parameters with reservoir parameters' high order changers, has the ability to invert geobodies' porosity and clay volume details in 3 D space directly, and then with the constrain of those 2 parameters, "Sweet Spot" prediction was achieved. With the example of W17 oilfield, this paper clarify the difference on rock physics discipline between conventional and "Sweet Spot" type reservoirs first. Then a facies control pre-stack geostatistical inversion was carried out to get high resolution elastic parameters volume. On the basis of previous rock physics forward modeling and seismic inversion research, rock physics inversion study was applied to invert porosity and clay volume directly, and the result was compared with geostatistical co-simulation output which is used popularly in industry before. It shows that the internal details of geobodies from direct rock physics inversion are more abundant. Blind well test show that the precision of inverted porosity and clay volume is improved by comparing the pseudo logs on well point location. In the whole, reservoir parameters rock physics inversion has the benefit of describe reservoir internal properties elaborately and accurately, keeping the final resolution equivalence with the geostatistical elastic inversion solutions, but not going down straightly such as based on geostatistical co-simulation multi realization average method. Those progress has the capability to solve or in favor to evaluate "Sweet Spot" reservoir connectivity and heterogeneity such tough geology problem.
The main Liushagang formation rock of Wushi geology structure has the feature of wide particle size distribution, low porosity and low permeability, whereas those kind of reservoir rock is accounted nearly 50 percent in the whole. "Sweet Spot" prediction is the most important factor to realize this oilfield's development economically. Reservoir porosity and clay volume evaluation are the key questions to establish "Sweet Spot" prediction successfully. A new rock physics inversion method was applied to "Sweet Spot" prediction in this paper. This method solves effective media inclusion model function directly by constrained least squares and trust region approach, and can link the elastic parameters with reservoir parameters' high order changers, has the ability to invert geobodies' porosity and clay volume details in 3 D space directly, and then with the constrain of those 2 parameters, "Sweet Spot" prediction was achieved. With the example of W17 oilfield, this paper clarify the difference on rock physics discipline between conventional and "Sweet Spot" type reservoirs first. Then a facies control pre-stack geostatistical inversion was carried out to get high resolution elastic parameters volume. On the basis of previous rock physics forward modeling and seismic inversion research, rock physics inversion study was applied to invert porosity and clay volume directly, and the result was compared with geostatistical co-simulation output which is used popularly in industry before. It shows that the internal details of geobodies from direct rock physics inversion are more abundant. Blind well test show that the precision of inverted porosity and clay volume is improved by comparing the pseudo logs on well point location. In the whole, reservoir parameters rock physics inversion has the benefit of describe reservoir internal properties elaborately and accurately, keeping the final resolution equivalence with the geostatistical elastic inversion solutions, but not going down straightly such as based on geostatistical co-simulation multi realization average method. Those progress has the capability to solve or in favor to evaluate "Sweet Spot" reservoir connectivity and heterogeneity such tough geology problem.
引文
Avseth P,Mukerji T,Mavko G,et al.2009.Quantitative seismic interpretation:Applying rockphysics tools to reduce interpretation risk [M].Beijing:Petroleum Industry Press.
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Bernal F.2016.Trust-region methods for nonlinear elliptic equations with radial basis functions [J].Computers & Mathematics with Applications,72(7):1743-1763.
Deng Ji-xin,Wang Shang-xu.2009.Joint Inversion of Saturation and Porosity in Gas Reservoirs Based on Statistical Rock Physics [J].Journal of Oil and Gas Technology (in Chinese),31(1):48-52.
Ebrahim Z,Inderwildi O R,King D A.2014.Macroeconomic impacts of oil price volatility:mitigation and resilience [J].Frontiers in Energy,8(1):9-24.
Gary M,Tapan M,Jack D.2009.The rock physics handbook:tools for seismic analysis of porous media [M].United Kindom:Cambridge University Press.
Gautier D L,Mast R F.1995.US geological survey methodology for the 1995 national assessment [J].AAPG Bulletin,78(1):1-10.
Gunning J,Glinsky M E.2007.Detection of reservoir quality using Bayesian seismic inversion [J].Geophysics,72(3):R37-R49.
HE Wei,MA Shi-zhong,YUAN Jiang-ru,et al.2017.Modeling method of the multi-scale and multiple medium unconventional tight oil-reservoir:a case study of the upper reservoir in Lucaogou formation of Junggar basin [J].Progress in Geophysics (in Chinese),32(2):618- 625,doi:10.6038/pg20170223.
HU Hua-feng,Yin Xing-yao,Wu Guo-chen.2012.Joint inversion of petrophysical parameters based on Bayesian classification [J].Geophysical Prospecting for Petroleum(in Chinese),51(3):225-232.
LIN Tian,MENG Xiao-Hong,ZHANG Zhi-Fu.2017.The petrophysical parameter inversion method based on constrained least squares and trust region approach [J].Chinese Journal of Geophysics (in Chinese),60(10):3969-3983,doi:10.6038/cjg20171024.
LIU Xiang-Jun,ZHU Hong-Lin,LIANG Li-Xi.2014.Digital rock physics of sandstone based on micro-CT technology [J].Chinese Journal of Geophysics (in Chinese),57(4):1133-1140,doi:10.6038/cjg20140411.
Liu Zeng-qin,Wang Ying-min,Bai Guang-chen,et al.2010.Application of sweetness and its fusion attribute in the research of Deep-water Reservoir[J].OGP.(in Chinese),45(S1):158-162.
LUO Zuo-xian,LIANG Hui,LU Xue-mei,et al.2014.The development strategy of international oil companies under the new situation [J].International Petroleum Economics (in Chinese),22(11):50-56.
Lü Qi-biao,SUN Zuo-xing.2012.Application of rockphysics chart to quantitative reservoir interpretation [J].Progress in Geophysics (in Chinese),27(2):610- 618,doi:10.6038/j.issn.1004-2903.2012.02.025.
Mukerji T,J?rstad A,Avseth P,et al.2001.Mapping lithofacies and pore-fluid probabilities in a North Sea reservoir:Seismic inversions and statistical rock physics [J].Geophysics,66(4):988-1001.
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Sharma R K,Chopra S.2015.Identification of thin sweet spots in the Duvernay Formation of north central Alberta [C].Seg Technical Program Expanded.
SI Chao-nian,WU Xing-wei,XIA Dong-ling,et al.2015.The research of “sweet spot”prediction technologyfor tight sandstone reservoir—a case study of Chang 3 reservoir of Yanchangformation in Weibei Oilfield [J].Progress in Geophysics,30(2):664- 671,doi:10.6038/pg20150225.
SONG Zi-qi,TANG Chang-jiu,LIU Xiao-juan,et al.2008.Determination of favorable oil-bearing areas with extra low-permeability reservoir by “dessert” of petro-physical facies [J].Acta Petrolei Sinica (in Chinese),29(5):711-716.
Ulvmoen M,Omre H.2010.Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations:Part 1-Methodology [J].Geophysics,75(2):R21-R35.
Wang Jia-hua,Zhao Wei.2010.Direct rock physics inversion based on statistical rock physics [J].Complex Hydrocarbon Reservoirs (in Chinese),03(4):6-9.
WU Mei,FU Li-Yun,LI Wei-Xin.2008.A high-resolution nonlinear inversion method of reservoir parameters and its application to oil/gas exploration [J].Chinese Journal of Geophysics (in Chinese),51(2):546-557,doi:10.3321/j.issn:0001-5733.2008.02.027.
Xu S,White R E.1995.A new velocity model for clay-sand mixtures [J].Geophysical Prospecting,43(1):91-118.
YANG Pei-Jie.2018.Porosity and water saturation simultaneous inversion for sand-mudstone reservoir [J].Chinese Journal of Geophysics (in Chinese),61(2):673- 682,doi:10.6038/cjg2018K0714.
YIN Xing-Yao,CUI Wei,ZONG Zhao-Yun,et al.2014.Petrophysical property inversion of reservoirs based on elastic impedance [J].Chinese Journal of Geophysics (in Chinese),57(12):4132- 4140,doi:10.6038/cjg20141224.
YOU Li,ZHANG Ying-chao,LI Cai,et al.2014.Based on analysis of sedimentary-diagenetic reservoir facies to determine “sweet spots” distribution in low permeability from wenchang 9 area [J].Journal of Jilin University:Earth Science Edition (in Chinese),44(5):1432-1440.
YOU Li,ZHAO Zhan-jie,LI Cai,et al.2015.Reservoir physical properties and favorable reservoirs in Liushagang formation in Wushi sag [J].Journal of Northeast Petroleum University (in Chinese),39(6):95-101.
ZENG Qing-cai,CHEN Sheng,HE Pei,et al.2018.Quantitative seismic prediction of shale gas sweet spots in Lower Silurian Longmaxi Formation,Weiyuan area,Sichuan Basin,SW China [J].Petroleum Exploration and Development (in Chinese),45(3):406- 414.
Zhang Lin-qing,Zhang Hui-xing,Jiang Xiao-dian,et al.2017.Application of elastic parameters inversion and attribute fusion technology in the “sweet spot” prediction [J].Nature Gas Geoscience (in Chinese),28(4):582-589.
ZHAO Jian-zhang,ZHANG Jin-duo,LI Wen-ge,et al.2009.Application and effect of reservoir parameters inversion technique at Mobei area [J].Petroleum Geology and Engineering (in Chinese),23(4):38- 40,45.
Avseth P,Mukerji T,Mavko G,等.2009.定量地震解释:应用岩石物理工具降低解释风险[M].北京:石油工业出版社.
邓继新,王尚旭.2009.基于统计岩石物理的含气储层饱和度与孔隙度联合反演[J].石油天然气学报,31(1):48-52.
何伟,马世忠,袁江如,等.2017.致密油储层不同尺度、多重介质建模方法研究——以吉木萨尔凹陷芦草沟组上甜点为例[J].地球物理学进展,32(2):618- 625,doi:10.6038/pg20170223.
胡华锋,印兴耀,吴国忱.2012.基于贝叶斯分类的储层物性参数联合反演方法[J].石油物探,51(3):225-232.
林恬,孟小红,张致付.2017.基于约束最小二乘与信赖域的储层参数反演方法[J].地球物理学报,60(10):3969-3983,doi:10.6038/cjg20171024.
刘向君,朱洪林,梁利喜.2014.基于微CT技术的砂岩数字岩石物理实验[J].地球物理学报,57(4):1133-1140,doi:10.6038/cjg20140411.
刘曾勤,王英民,白广臣,等.2010.甜点及其融合属性在深水储层研究中的应用[J].石油地球物理勘探,45(S1):158-162.
罗佐县,梁慧,卢雪梅,等.2014.新形势下国际大石油公司发展战略[J].国际石油经济,22(11):50-56.
吕其彪,孙作兴.2012.岩石物理模版在储层定量解释中的应用[J].地球物理学进展,27(2):610- 618,doi:10.6038/j.issn.1004-2903.2012.02.025.
秦德文,姜勇,侯志强,等.2015.叠前同步反演技术在西湖凹陷低孔渗储层“甜点”预测中的应用[J].油气藏评价与开发,5(6):12-15.
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Avseth P A,Odegaard E..2004.Well log and seismic data analysis using rock physics templates [J].First Break,22(10):37- 43.
Bernal F.2016.Trust-region methods for nonlinear elliptic equations with radial basis functions [J].Computers & Mathematics with Applications,72(7):1743-1763.
Deng Ji-xin,Wang Shang-xu.2009.Joint Inversion of Saturation and Porosity in Gas Reservoirs Based on Statistical Rock Physics [J].Journal of Oil and Gas Technology (in Chinese),31(1):48-52.
Ebrahim Z,Inderwildi O R,King D A.2014.Macroeconomic impacts of oil price volatility:mitigation and resilience [J].Frontiers in Energy,8(1):9-24.
Gary M,Tapan M,Jack D.2009.The rock physics handbook:tools for seismic analysis of porous media [M].United Kindom:Cambridge University Press.
Gautier D L,Mast R F.1995.US geological survey methodology for the 1995 national assessment [J].AAPG Bulletin,78(1):1-10.
Gunning J,Glinsky M E.2007.Detection of reservoir quality using Bayesian seismic inversion [J].Geophysics,72(3):R37-R49.
HE Wei,MA Shi-zhong,YUAN Jiang-ru,et al.2017.Modeling method of the multi-scale and multiple medium unconventional tight oil-reservoir:a case study of the upper reservoir in Lucaogou formation of Junggar basin [J].Progress in Geophysics (in Chinese),32(2):618- 625,doi:10.6038/pg20170223.
HU Hua-feng,Yin Xing-yao,Wu Guo-chen.2012.Joint inversion of petrophysical parameters based on Bayesian classification [J].Geophysical Prospecting for Petroleum(in Chinese),51(3):225-232.
LIN Tian,MENG Xiao-Hong,ZHANG Zhi-Fu.2017.The petrophysical parameter inversion method based on constrained least squares and trust region approach [J].Chinese Journal of Geophysics (in Chinese),60(10):3969-3983,doi:10.6038/cjg20171024.
LIU Xiang-Jun,ZHU Hong-Lin,LIANG Li-Xi.2014.Digital rock physics of sandstone based on micro-CT technology [J].Chinese Journal of Geophysics (in Chinese),57(4):1133-1140,doi:10.6038/cjg20140411.
Liu Zeng-qin,Wang Ying-min,Bai Guang-chen,et al.2010.Application of sweetness and its fusion attribute in the research of Deep-water Reservoir[J].OGP.(in Chinese),45(S1):158-162.
LUO Zuo-xian,LIANG Hui,LU Xue-mei,et al.2014.The development strategy of international oil companies under the new situation [J].International Petroleum Economics (in Chinese),22(11):50-56.
Lü Qi-biao,SUN Zuo-xing.2012.Application of rockphysics chart to quantitative reservoir interpretation [J].Progress in Geophysics (in Chinese),27(2):610- 618,doi:10.6038/j.issn.1004-2903.2012.02.025.
Mukerji T,J?rstad A,Avseth P,et al.2001.Mapping lithofacies and pore-fluid probabilities in a North Sea reservoir:Seismic inversions and statistical rock physics [J].Geophysics,66(4):988-1001.
QIN De-wen,JIANG Yong,HOU Zhi-qiang,et al.2015.Application of prestack synchronous inversion technology in “sweet spot” prediction of low porosity and permeability reservoir in Xihu sag [J].Reservoir evaluation and development (in Chinese),5(6):12-15.
Sena A,Castillo G,Chesser K,et al.2011.Seismic reservoir characterization in resource shale plays:stress analysis and sweet spot discrimination[J].The Leading Edge,30(7):758-764.
Sharma R K,Chopra S.2015.Identification of thin sweet spots in the Duvernay Formation of north central Alberta [C].Seg Technical Program Expanded.
SI Chao-nian,WU Xing-wei,XIA Dong-ling,et al.2015.The research of “sweet spot”prediction technologyfor tight sandstone reservoir—a case study of Chang 3 reservoir of Yanchangformation in Weibei Oilfield [J].Progress in Geophysics,30(2):664- 671,doi:10.6038/pg20150225.
SONG Zi-qi,TANG Chang-jiu,LIU Xiao-juan,et al.2008.Determination of favorable oil-bearing areas with extra low-permeability reservoir by “dessert” of petro-physical facies [J].Acta Petrolei Sinica (in Chinese),29(5):711-716.
Ulvmoen M,Omre H.2010.Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations:Part 1-Methodology [J].Geophysics,75(2):R21-R35.
Wang Jia-hua,Zhao Wei.2010.Direct rock physics inversion based on statistical rock physics [J].Complex Hydrocarbon Reservoirs (in Chinese),03(4):6-9.
WU Mei,FU Li-Yun,LI Wei-Xin.2008.A high-resolution nonlinear inversion method of reservoir parameters and its application to oil/gas exploration [J].Chinese Journal of Geophysics (in Chinese),51(2):546-557,doi:10.3321/j.issn:0001-5733.2008.02.027.
Xu S,White R E.1995.A new velocity model for clay-sand mixtures [J].Geophysical Prospecting,43(1):91-118.
YANG Pei-Jie.2018.Porosity and water saturation simultaneous inversion for sand-mudstone reservoir [J].Chinese Journal of Geophysics (in Chinese),61(2):673- 682,doi:10.6038/cjg2018K0714.
YIN Xing-Yao,CUI Wei,ZONG Zhao-Yun,et al.2014.Petrophysical property inversion of reservoirs based on elastic impedance [J].Chinese Journal of Geophysics (in Chinese),57(12):4132- 4140,doi:10.6038/cjg20141224.
YOU Li,ZHANG Ying-chao,LI Cai,et al.2014.Based on analysis of sedimentary-diagenetic reservoir facies to determine “sweet spots” distribution in low permeability from wenchang 9 area [J].Journal of Jilin University:Earth Science Edition (in Chinese),44(5):1432-1440.
YOU Li,ZHAO Zhan-jie,LI Cai,et al.2015.Reservoir physical properties and favorable reservoirs in Liushagang formation in Wushi sag [J].Journal of Northeast Petroleum University (in Chinese),39(6):95-101.
ZENG Qing-cai,CHEN Sheng,HE Pei,et al.2018.Quantitative seismic prediction of shale gas sweet spots in Lower Silurian Longmaxi Formation,Weiyuan area,Sichuan Basin,SW China [J].Petroleum Exploration and Development (in Chinese),45(3):406- 414.
Zhang Lin-qing,Zhang Hui-xing,Jiang Xiao-dian,et al.2017.Application of elastic parameters inversion and attribute fusion technology in the “sweet spot” prediction [J].Nature Gas Geoscience (in Chinese),28(4):582-589.
ZHAO Jian-zhang,ZHANG Jin-duo,LI Wen-ge,et al.2009.Application and effect of reservoir parameters inversion technique at Mobei area [J].Petroleum Geology and Engineering (in Chinese),23(4):38- 40,45.
Avseth P,Mukerji T,Mavko G,等.2009.定量地震解释:应用岩石物理工具降低解释风险[M].北京:石油工业出版社.
邓继新,王尚旭.2009.基于统计岩石物理的含气储层饱和度与孔隙度联合反演[J].石油天然气学报,31(1):48-52.
何伟,马世忠,袁江如,等.2017.致密油储层不同尺度、多重介质建模方法研究——以吉木萨尔凹陷芦草沟组上甜点为例[J].地球物理学进展,32(2):618- 625,doi:10.6038/pg20170223.
胡华锋,印兴耀,吴国忱.2012.基于贝叶斯分类的储层物性参数联合反演方法[J].石油物探,51(3):225-232.
林恬,孟小红,张致付.2017.基于约束最小二乘与信赖域的储层参数反演方法[J].地球物理学报,60(10):3969-3983,doi:10.6038/cjg20171024.
刘向君,朱洪林,梁利喜.2014.基于微CT技术的砂岩数字岩石物理实验[J].地球物理学报,57(4):1133-1140,doi:10.6038/cjg20140411.
刘曾勤,王英民,白广臣,等.2010.甜点及其融合属性在深水储层研究中的应用[J].石油地球物理勘探,45(S1):158-162.
罗佐县,梁慧,卢雪梅,等.2014.新形势下国际大石油公司发展战略[J].国际石油经济,22(11):50-56.
吕其彪,孙作兴.2012.岩石物理模版在储层定量解释中的应用[J].地球物理学进展,27(2):610- 618,doi:10.6038/j.issn.1004-2903.2012.02.025.
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