Quantitative interpretation of sweet spots in low-permeability limestone reservoirs in thin reef beach with few offshore wells:A case study of A oilfield in Pearl River Mouth Basin
Abstract：The reef-beach limestone reservoir in A oilfield in Pearl River Mouth Basin has an ultra-thin thickness, rapid lateral change, strong heterogeneity, and complex porosity-permeability relationship. In addition, limited offshore drilling data and low vertical and lateral resolution of seismic data make it difficult to evaluate sweet spots in low-permeability reservoirs. Therefore, we propose a technical strategy for quantitatively interpreting sweet spots in low-permeability limestone reservoirs with thin layers by integrating geophysical prospecting, logging, and geology. For complex oil and gas reservoirs with abnormal velocity in limestone, small thickness, and rapid lateral change, we combine the shallow-middle layer velocity modeling method of full waveform inversion and the middle-deep layer velocity modeling method of grid tomography and use the energy of reflected and refracted waves to update the velocity model, so as to reduce the velocity error, improve the imaging quality effectively, and ensure facies division accuracy. The porosity-permeability relationship of complex limestones is optimized based on pore-morphology factor correction technology, and the stable elastic parameters of seismic inversion are directly used to interpret the permeability, which thus expands the permeability interpretation model to the three-dimensional space. For seismic inversion with thin layers and few wells, the multi-stage facies-controlled pre-stack seismic inversion technique with high resolution, which combines comprehensive nesting constraints of one-dimensional logging lithofacies and two-dimensional planar facies, is used for the first time to quantitatively characterize the sweet spots in low-permeability limestone reservoirs in the reef beach. According to the seismic data and inversion results, the strata of the reef beach are explained in detail, and the limestone strata are divided into four research units:tight carbonate rock platform, organic bank, lower organic reef, and upper organic reef. The sweet spots in low-permeability limestone reservoirs are locally developed and are mainly distributed in the main reef beach part in the north of Well 1 and south of Well 2.
郭飞, 李黎, 董政, 蒋玉婷, 沈水荣, 张永江. 海上少井条件下低渗薄礁滩灰岩储层甜点定量解释——以珠江口盆地A油田为例[J]. 石油地球物理勘探, 2023, 58(2): 381-391.
GUO Fei, LI Li, DONG Zheng, JIANG Yuting, SHEN Shuirong, ZHANG Yongjiang. Quantitative interpretation of sweet spots in low-permeability limestone reservoirs in thin reef beach with few offshore wells:A case study of A oilfield in Pearl River Mouth Basin. Oil Geophysical Prospecting, 2023, 58(2): 381-391.
吴婷婷,周小康,张丽丽.东沙隆起珠江组礁滩相储层主要成岩作用及演化模式[J].中国海上油气,2021,33(1):42-49.WU Tingting,ZHOU Xiaokang,ZHANG Lili.Main diagenesis and evolution model of reef flat facies reser-voir in Zhujiang Formation,Dongsha uplift[J].China Offshore Oil and Gas,2021,33(1):42-49.
[2]
梁卫,周小康,卫哲,等.珠江口盆地东沙隆起珠江组碳酸盐岩储层特征及主控因素[J].成都理工大学学报(自然科学版),2015,42(2):169-179.LIANG Wei,ZHOU Xiaokang,WEI Zhe,et al.Chara-cteristics and key controlling factors of Zhujiang Formation carbonate rock reservoir in Pearl River Mouth Basin,China[J].Journal of Chengdu University of Technology (Science & Technology Edition),2015,42(2):169-179.
[3]
邵先杰,王彩凤,黄伟,等.苏北盆地金湖凹陷碳酸盐岩沉积特征及演化模式[J].石油学报,2013,34(4):701-711.SHAO Xianjie,WANG Caifeng,HUANG Wei,et al.Sedimentary characteristics and evolutionary patterns of carbonates in Jinhu depression,Subei Basin[J].Acta Petrolei Sinica,2013,34(4):701-711.
[4]
陈端新,吴时国,施和生,等.珠江口盆地流花碳酸盐台地灰岩坑的地震反射特征及成因探讨[J].吉林大学学报(地球科学版),2012,42(6):1935-1943.CHEN Duanxin,WU Shiguo,SHI Hesheng,et al.Seismic characteristics and generations of sinkholes in the Liuhua carbonate platform,Pearl River Mouth Basin[J].Journal of Jilin University(Earth Science Edition),2012,42(6):1935-1943.
[5]
熊晓军,贺振华,黄德济.生物礁地震响应特征的数值模拟[J].石油学报,2009,30(1):75-79.XIONG Xiaojun,HE Zhenhua,HUANG Deji.Numeri-cal simulation on seismic response features of reef[J].Acta Petrolei Sinica,2009,30(1):75-79.
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文晓涛,黄德济,等.礁滩储层地震识别[M].北京:科学出版社,2014.
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曾驿,汪瑞良,刘军,等.东沙隆起碳酸盐岩储层特征及预测[J].石油天然气学报(江汉石油学院学报),2011,33(6):69-73.ZENG Yi,WANG Ruiliang,LIU Jun,et al.Carbonate reservoir characteristics and its prediction of Dongsha massif[J].Journal of Oil and Gas Technology,2011,33(6):69-73.
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熊晓军,张鑫,张本健,等.裂缝融合分析的窄方位叠前裂缝预测技术[J].石油地球物理勘探,2021,56(5):1150-1156.XIONG Xiaojun,ZHANG Xin,ZHANG Benjian,et al.Fracture prediction technology on prestack narrow azimuth data with fracture fusion analysis[J].Oil Geo-physical Prospecting,2021,56(5):1150-1156.
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闫星宇,李宗杰,顾汉明,等.基于深度卷积神经网络的地震数据溶洞识别[J].石油地球物理勘探,2022,57(1):1-11.YAN Xingyu,LI Zongjie,GU Hanming,et al.Identification of Karst caves in seismic data based on deep convolutional neural network[J].Oil Geophysical Prospecting,2022,57(1):1-11.
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张涛,王小卫,王孝,等.特殊岩性体的速度-深度建模方法[J].石油地球物理勘探,2020,55(增刊):49-55.ZHANG Tao,WANG Xiaowei,WANG Xiao,et al.The velocity-depth modeling method of special litho-logic bodies[J].Oil Geophysical Prospecting,2020,55(S):49-55.
[11]
HA W,PYUN S,YO J,et al.Acoustic full waveform inversion of synthetic land and marine data in the Laplace domain[J].Geophysical Prospecting,2010,58(6):1033-1048.
[12]
邵祥奇,何兵寿,史才旺.基于分频编码的弹性波全波形反演[J].石油地球物理勘探,2020,55(6):1321-1329.SHAO Xiangqi,HE Bingshou,SHI Caiwang,et al.Elastic full inversion based on frequency division encoding[J].Oil Geophysical Prospecting,2020,55(6):1321-1329.
[13]
CHOI Y,ALKHALIFAH T.Application of multi-source waveform inversion to marine streamer data using the global correlation norm[J].Geophysical Prospecting,2012,60(4):748-758.
[14]
胡光辉,李熙盛,郭丽,等.构造约束全波形反演及其海上资料应用[J].石油物探,2018,57(4):592-596.HU Guanghui,LI Xisheng,GUO Li,et al.Structure-constrained full waveform inversion and its application in marine seismic data[J].Geophysical Prospecting for Petroleum,2018,57(4):592-596.
[15]
张凤生,隋秀英,段朝伟,等.高孔隙度低渗透率碳酸盐岩储层岩心核磁共振实验研究[J].测井技术,2018,42(5):497-502,529.ZHANG Fengsheng,SUI Xiuying,DUAN Chaowei,et al.NMR experimental study on carbonate reservoirs with high porosity and low permeability[J].Well Logging Technology,2018,42(5):497-502,529.
[16]
甘利灯,王峣钧,罗贤哲,等.基于孔隙结构参数的相控渗透率地震预测方法[J].石油勘探与开发,2019,46(5):883-890.GAN Lideng,WANG Yaojun,LUO Xianzhe,et al.A permeability prediction method based on pore structure and lithofacies[J].Petroleum Exploration and Development,2019,46(5):883-890.
[17]
李雄炎,秦瑞宝,曹景记,等.复杂储层连通孔隙度评价与渗透率定量计算方法[J].石油地球物理勘探,2022,57(2):377-385.LI Xiongyan,QIN Ruibao,CAO Jingji,et al.Method of connected porosity evaluation and quantitative permeability calculation for complex reservoirs[J].Oil Geophysical Prospecting,2022,57(2):377-385.
[18]
HASS A,DUBRULE O.Geostatistical inversion:a sequential method of stochastic reservoir modeling constrained by seismic data[J].First Break,1994,12(11):561-569.
[19]
黄捍东,罗群,付艳,等.地震相控非线性随机反演研究与应用[J].石油地球物理勘探,2007,42(6):694-698.HUANG Handong,LUO Qun,FU Yan,et al.Study and application of seismic phase-controlled non-liner random inversion[J].Oil Geophysical Prospecting,2007,42(6):694-698.
吴婷婷,周小康,张丽丽.东沙隆起珠江组礁滩相储层主要成岩作用及演化模式[J].中国海上油气,2021,33(1):42-49.WU Tingting,ZHOU Xiaokang,ZHANG Lili.Main diagenesis and evolution model of reef flat facies reser-voir in Zhujiang Formation,Dongsha uplift[J].China Offshore Oil and Gas,2021,33(1):42-49.
[2]
梁卫,周小康,卫哲,等.珠江口盆地东沙隆起珠江组碳酸盐岩储层特征及主控因素[J].成都理工大学学报(自然科学版),2015,42(2):169-179.LIANG Wei,ZHOU Xiaokang,WEI Zhe,et al.Chara-cteristics and key controlling factors of Zhujiang Formation carbonate rock reservoir in Pearl River Mouth Basin,China[J].Journal of Chengdu University of Technology (Science & Technology Edition),2015,42(2):169-179.
[3]
邵先杰,王彩凤,黄伟,等.苏北盆地金湖凹陷碳酸盐岩沉积特征及演化模式[J].石油学报,2013,34(4):701-711.SHAO Xianjie,WANG Caifeng,HUANG Wei,et al.Sedimentary characteristics and evolutionary patterns of carbonates in Jinhu depression,Subei Basin[J].Acta Petrolei Sinica,2013,34(4):701-711.
[4]
陈端新,吴时国,施和生,等.珠江口盆地流花碳酸盐台地灰岩坑的地震反射特征及成因探讨[J].吉林大学学报(地球科学版),2012,42(6):1935-1943.CHEN Duanxin,WU Shiguo,SHI Hesheng,et al.Seismic characteristics and generations of sinkholes in the Liuhua carbonate platform,Pearl River Mouth Basin[J].Journal of Jilin University(Earth Science Edition),2012,42(6):1935-1943.
[5]
熊晓军,贺振华,黄德济.生物礁地震响应特征的数值模拟[J].石油学报,2009,30(1):75-79.XIONG Xiaojun,HE Zhenhua,HUANG Deji.Numeri-cal simulation on seismic response features of reef[J].Acta Petrolei Sinica,2009,30(1):75-79.
[6]
文晓涛,黄德济,等.礁滩储层地震识别[M].北京:科学出版社,2014.
[7]
曾驿,汪瑞良,刘军,等.东沙隆起碳酸盐岩储层特征及预测[J].石油天然气学报(江汉石油学院学报),2011,33(6):69-73.ZENG Yi,WANG Ruiliang,LIU Jun,et al.Carbonate reservoir characteristics and its prediction of Dongsha massif[J].Journal of Oil and Gas Technology,2011,33(6):69-73.
[8]
熊晓军,张鑫,张本健,等.裂缝融合分析的窄方位叠前裂缝预测技术[J].石油地球物理勘探,2021,56(5):1150-1156.XIONG Xiaojun,ZHANG Xin,ZHANG Benjian,et al.Fracture prediction technology on prestack narrow azimuth data with fracture fusion analysis[J].Oil Geo-physical Prospecting,2021,56(5):1150-1156.
[9]
闫星宇,李宗杰,顾汉明,等.基于深度卷积神经网络的地震数据溶洞识别[J].石油地球物理勘探,2022,57(1):1-11.YAN Xingyu,LI Zongjie,GU Hanming,et al.Identification of Karst caves in seismic data based on deep convolutional neural network[J].Oil Geophysical Prospecting,2022,57(1):1-11.
[10]
张涛,王小卫,王孝,等.特殊岩性体的速度-深度建模方法[J].石油地球物理勘探,2020,55(增刊):49-55.ZHANG Tao,WANG Xiaowei,WANG Xiao,et al.The velocity-depth modeling method of special litho-logic bodies[J].Oil Geophysical Prospecting,2020,55(S):49-55.
[11]
HA W,PYUN S,YO J,et al.Acoustic full waveform inversion of synthetic land and marine data in the Laplace domain[J].Geophysical Prospecting,2010,58(6):1033-1048.
[12]
邵祥奇,何兵寿,史才旺.基于分频编码的弹性波全波形反演[J].石油地球物理勘探,2020,55(6):1321-1329.SHAO Xiangqi,HE Bingshou,SHI Caiwang,et al.Elastic full inversion based on frequency division encoding[J].Oil Geophysical Prospecting,2020,55(6):1321-1329.
[13]
CHOI Y,ALKHALIFAH T.Application of multi-source waveform inversion to marine streamer data using the global correlation norm[J].Geophysical Prospecting,2012,60(4):748-758.
[14]
胡光辉,李熙盛,郭丽,等.构造约束全波形反演及其海上资料应用[J].石油物探,2018,57(4):592-596.HU Guanghui,LI Xisheng,GUO Li,et al.Structure-constrained full waveform inversion and its application in marine seismic data[J].Geophysical Prospecting for Petroleum,2018,57(4):592-596.
[15]
张凤生,隋秀英,段朝伟,等.高孔隙度低渗透率碳酸盐岩储层岩心核磁共振实验研究[J].测井技术,2018,42(5):497-502,529.ZHANG Fengsheng,SUI Xiuying,DUAN Chaowei,et al.NMR experimental study on carbonate reservoirs with high porosity and low permeability[J].Well Logging Technology,2018,42(5):497-502,529.
[16]
甘利灯,王峣钧,罗贤哲,等.基于孔隙结构参数的相控渗透率地震预测方法[J].石油勘探与开发,2019,46(5):883-890.GAN Lideng,WANG Yaojun,LUO Xianzhe,et al.A permeability prediction method based on pore structure and lithofacies[J].Petroleum Exploration and Development,2019,46(5):883-890.
[17]
李雄炎,秦瑞宝,曹景记,等.复杂储层连通孔隙度评价与渗透率定量计算方法[J].石油地球物理勘探,2022,57(2):377-385.LI Xiongyan,QIN Ruibao,CAO Jingji,et al.Method of connected porosity evaluation and quantitative permeability calculation for complex reservoirs[J].Oil Geophysical Prospecting,2022,57(2):377-385.
[18]
HASS A,DUBRULE O.Geostatistical inversion:a sequential method of stochastic reservoir modeling constrained by seismic data[J].First Break,1994,12(11):561-569.
[1]
吴婷婷,周小康,张丽丽.东沙隆起珠江组礁滩相储层主要成岩作用及演化模式[J].中国海上油气,2021,33(1):42-49.WU Tingting,ZHOU Xiaokang,ZHANG Lili.Main diagenesis and evolution model of reef flat facies reser-voir in Zhujiang Formation,Dongsha uplift[J].China Offshore Oil and Gas,2021,33(1):42-49.
[2]
梁卫,周小康,卫哲,等.珠江口盆地东沙隆起珠江组碳酸盐岩储层特征及主控因素[J].成都理工大学学报(自然科学版),2015,42(2):169-179.LIANG Wei,ZHOU Xiaokang,WEI Zhe,et al.Chara-cteristics and key controlling factors of Zhujiang Formation carbonate rock reservoir in Pearl River Mouth Basin,China[J].Journal of Chengdu University of Technology (Science & Technology Edition),2015,42(2):169-179.
[3]
邵先杰,王彩凤,黄伟,等.苏北盆地金湖凹陷碳酸盐岩沉积特征及演化模式[J].石油学报,2013,34(4):701-711.SHAO Xianjie,WANG Caifeng,HUANG Wei,et al.Sedimentary characteristics and evolutionary patterns of carbonates in Jinhu depression,Subei Basin[J].Acta Petrolei Sinica,2013,34(4):701-711.
[4]
陈端新,吴时国,施和生,等.珠江口盆地流花碳酸盐台地灰岩坑的地震反射特征及成因探讨[J].吉林大学学报(地球科学版),2012,42(6):1935-1943.CHEN Duanxin,WU Shiguo,SHI Hesheng,et al.Seismic characteristics and generations of sinkholes in the Liuhua carbonate platform,Pearl River Mouth Basin[J].Journal of Jilin University(Earth Science Edition),2012,42(6):1935-1943.
[5]
熊晓军,贺振华,黄德济.生物礁地震响应特征的数值模拟[J].石油学报,2009,30(1):75-79.XIONG Xiaojun,HE Zhenhua,HUANG Deji.Numeri-cal simulation on seismic response features of reef[J].Acta Petrolei Sinica,2009,30(1):75-79.
[6]
文晓涛,黄德济,等.礁滩储层地震识别[M].北京:科学出版社,2014.
[7]
曾驿,汪瑞良,刘军,等.东沙隆起碳酸盐岩储层特征及预测[J].石油天然气学报(江汉石油学院学报),2011,33(6):69-73.ZENG Yi,WANG Ruiliang,LIU Jun,et al.Carbonate reservoir characteristics and its prediction of Dongsha massif[J].Journal of Oil and Gas Technology,2011,33(6):69-73.
[8]
熊晓军,张鑫,张本健,等.裂缝融合分析的窄方位叠前裂缝预测技术[J].石油地球物理勘探,2021,56(5):1150-1156.XIONG Xiaojun,ZHANG Xin,ZHANG Benjian,et al.Fracture prediction technology on prestack narrow azimuth data with fracture fusion analysis[J].Oil Geo-physical Prospecting,2021,56(5):1150-1156.
[9]
闫星宇,李宗杰,顾汉明,等.基于深度卷积神经网络的地震数据溶洞识别[J].石油地球物理勘探,2022,57(1):1-11.YAN Xingyu,LI Zongjie,GU Hanming,et al.Identification of Karst caves in seismic data based on deep convolutional neural network[J].Oil Geophysical Prospecting,2022,57(1):1-11.
[10]
张涛,王小卫,王孝,等.特殊岩性体的速度-深度建模方法[J].石油地球物理勘探,2020,55(增刊):49-55.ZHANG Tao,WANG Xiaowei,WANG Xiao,et al.The velocity-depth modeling method of special litho-logic bodies[J].Oil Geophysical Prospecting,2020,55(S):49-55.
[11]
HA W,PYUN S,YO J,et al.Acoustic full waveform inversion of synthetic land and marine data in the Laplace domain[J].Geophysical Prospecting,2010,58(6):1033-1048.
[12]
邵祥奇,何兵寿,史才旺.基于分频编码的弹性波全波形反演[J].石油地球物理勘探,2020,55(6):1321-1329.SHAO Xiangqi,HE Bingshou,SHI Caiwang,et al.Elastic full inversion based on frequency division encoding[J].Oil Geophysical Prospecting,2020,55(6):1321-1329.
[13]
CHOI Y,ALKHALIFAH T.Application of multi-source waveform inversion to marine streamer data using the global correlation norm[J].Geophysical Prospecting,2012,60(4):748-758.
[14]
胡光辉,李熙盛,郭丽,等.构造约束全波形反演及其海上资料应用[J].石油物探,2018,57(4):592-596.HU Guanghui,LI Xisheng,GUO Li,et al.Structure-constrained full waveform inversion and its application in marine seismic data[J].Geophysical Prospecting for Petroleum,2018,57(4):592-596.
[15]
张凤生,隋秀英,段朝伟,等.高孔隙度低渗透率碳酸盐岩储层岩心核磁共振实验研究[J].测井技术,2018,42(5):497-502,529.ZHANG Fengsheng,SUI Xiuying,DUAN Chaowei,et al.NMR experimental study on carbonate reservoirs with high porosity and low permeability[J].Well Logging Technology,2018,42(5):497-502,529.
[16]
甘利灯,王峣钧,罗贤哲,等.基于孔隙结构参数的相控渗透率地震预测方法[J].石油勘探与开发,2019,46(5):883-890.GAN Lideng,WANG Yaojun,LUO Xianzhe,et al.A permeability prediction method based on pore structure and lithofacies[J].Petroleum Exploration and Development,2019,46(5):883-890.
[17]
李雄炎,秦瑞宝,曹景记,等.复杂储层连通孔隙度评价与渗透率定量计算方法[J].石油地球物理勘探,2022,57(2):377-385.LI Xiongyan,QIN Ruibao,CAO Jingji,et al.Method of connected porosity evaluation and quantitative permeability calculation for complex reservoirs[J].Oil Geophysical Prospecting,2022,57(2):377-385.
[18]
HASS A,DUBRULE O.Geostatistical inversion:a sequential method of stochastic reservoir modeling constrained by seismic data[J].First Break,1994,12(11):561-569.
[19]
黄捍东,罗群,付艳,等.地震相控非线性随机反演研究与应用[J].石油地球物理勘探,2007,42(6):694-698.HUANG Handong,LUO Qun,FU Yan,et al.Study and application of seismic phase-controlled non-liner random inversion[J].Oil Geophysical Prospecting,2007,42(6):694-698.
王保丽,蔺营,张广智,等.非均匀介质特征参数地震随机反演方法[J].石油地球物理勘探,2021,56(6):1301-1310.WANG Baoli,LIN Ying,ZHANG Guangzhi,et al.Study on seismic stochastic inversion method based on characteristic parameters of inhomogeneous media[J].Oil Geophysical Prospecting,2021,56(6):1301-1310.
