M. Molina Camargo, G. F. Chinelatto, M. Basso, A. C. Vidal
{"title":"巴西桑托斯盆地盐下层序下白垩统barra velha组碳酸盐岩储层电相定义与分带","authors":"M. Molina Camargo, G. F. Chinelatto, M. Basso, A. C. Vidal","doi":"10.1111/jpg.12827","DOIUrl":null,"url":null,"abstract":"<p>Lower Cretaceous carbonates in the pre-salt succession in the Santos Basin, eastern Brazil, are highly heterogeneous in terms of their reservoir characteristics as a result of depositional and diagenetic factors. Electrofacies have widely been used for reservoir zonation and, when allied with computer-based methods such as neural networks, may help with the study of such complex reservoir rocks and with the identification of high-quality reservoir zones. In this work, an unsupervised artificial neural network known as a self-organizing map (SOM) was used to carry out a zonation of the pre-salt carbonates in the Aptian Barra Velha Formation, the main reservoir unit in the Santos Basin. Available data included gramma-ray, neutron porosity, resistivity deep, sonic, density, photoelectric factor, total porosity and effective porosity profiles from 21 wells together with mineralogical models. Core descriptions and thin section images were used as additional data for the lithological characterization of the electrofacies and consequently for reservoir zonation. A total of four electrofacies were defined from the SOM application, and five reservoir zones were identified.</p><p>The characterization of the reservoir zones also considered the structural locations of the wells based on the relative depth to top- Barra Velha Formation; well locations were classified as structurally high, intermediate or low. Based on the reservoir zone characteristics, the results could be correlated with zonations in previous studies. A general tendency was noted for there to be an increase of finer-grained sediments in the formation in wells located in structural lows; packstone and mudstone facies were prevalent in these wells and were in general characterized as poor-quality reservoir rocks. By contrast, the shrubstones and grainstones which were more frequent in structurally high wells comprised higher quality reservoir rocks.</p><p>The basal reservoir zone showed wide lithological variation compared to the overlying reservoir zones. Grainstone-dominated facies were identified in the middle of the formation, and the uppermost reservoir zones were characterized by an upward increase in shrubstones and reworked grainstones which in general pointed to better quality reservoirs.</p>","PeriodicalId":16748,"journal":{"name":"Journal of Petroleum Geology","volume":"45 4","pages":"439-459"},"PeriodicalIF":1.8000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ELECTROFACIES DEFINITION AND ZONATION OF THE LOWER CRETACEOUS BARRA VELHA FORMATION CARBONATE RESERVOIR IN THE PRE-SALT SEQUENCE OF THE SANTOS BASIN, SE BRAZIL\",\"authors\":\"M. Molina Camargo, G. F. Chinelatto, M. Basso, A. C. Vidal\",\"doi\":\"10.1111/jpg.12827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Lower Cretaceous carbonates in the pre-salt succession in the Santos Basin, eastern Brazil, are highly heterogeneous in terms of their reservoir characteristics as a result of depositional and diagenetic factors. Electrofacies have widely been used for reservoir zonation and, when allied with computer-based methods such as neural networks, may help with the study of such complex reservoir rocks and with the identification of high-quality reservoir zones. In this work, an unsupervised artificial neural network known as a self-organizing map (SOM) was used to carry out a zonation of the pre-salt carbonates in the Aptian Barra Velha Formation, the main reservoir unit in the Santos Basin. Available data included gramma-ray, neutron porosity, resistivity deep, sonic, density, photoelectric factor, total porosity and effective porosity profiles from 21 wells together with mineralogical models. Core descriptions and thin section images were used as additional data for the lithological characterization of the electrofacies and consequently for reservoir zonation. A total of four electrofacies were defined from the SOM application, and five reservoir zones were identified.</p><p>The characterization of the reservoir zones also considered the structural locations of the wells based on the relative depth to top- Barra Velha Formation; well locations were classified as structurally high, intermediate or low. Based on the reservoir zone characteristics, the results could be correlated with zonations in previous studies. A general tendency was noted for there to be an increase of finer-grained sediments in the formation in wells located in structural lows; packstone and mudstone facies were prevalent in these wells and were in general characterized as poor-quality reservoir rocks. By contrast, the shrubstones and grainstones which were more frequent in structurally high wells comprised higher quality reservoir rocks.</p><p>The basal reservoir zone showed wide lithological variation compared to the overlying reservoir zones. 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引用次数: 0
摘要
巴西东部桑托斯盆地下白垩统盐下碳酸盐岩受沉积和成岩因素影响,储层特征极不均匀。电相已被广泛用于储层划分,当与神经网络等基于计算机的方法相结合时,可以帮助研究这种复杂的储层岩石并识别优质储层。在这项工作中,一种被称为自组织图(SOM)的无监督人工神经网络被用于对Aptian Barra Velha组(Santos盆地的主要储层单元)的盐下碳酸盐岩进行分带。现有数据包括21口井的伽马、中子孔隙度、深部电阻率、声波、密度、光电系数、总孔隙度和有效孔隙度剖面以及矿物学模型。岩心描述和薄片图像被用作电相岩性表征的附加数据,从而用于储层分带。通过SOM应用,共确定了4个电相,并确定了5个储层。储层的表征还考虑了基于Barra Velha组顶部相对深度的井的构造位置;井位被划分为构造高、中、低。根据储层的区带特征,研究结果可以与前人的研究分区相关联。构造低洼井中,地层中细粒沉积物呈增加趋势;这些井以包岩和泥岩相为主,总体上属于劣质储层。而在构造高的井中较为常见的灌木岩和颗粒岩则构成了较优质的储集岩。与上覆储层相比,基底储层岩性差异较大。储层中部以颗粒岩为主,上部储层发育灌木岩和改造颗粒岩,储层质量总体较好。
ELECTROFACIES DEFINITION AND ZONATION OF THE LOWER CRETACEOUS BARRA VELHA FORMATION CARBONATE RESERVOIR IN THE PRE-SALT SEQUENCE OF THE SANTOS BASIN, SE BRAZIL
Lower Cretaceous carbonates in the pre-salt succession in the Santos Basin, eastern Brazil, are highly heterogeneous in terms of their reservoir characteristics as a result of depositional and diagenetic factors. Electrofacies have widely been used for reservoir zonation and, when allied with computer-based methods such as neural networks, may help with the study of such complex reservoir rocks and with the identification of high-quality reservoir zones. In this work, an unsupervised artificial neural network known as a self-organizing map (SOM) was used to carry out a zonation of the pre-salt carbonates in the Aptian Barra Velha Formation, the main reservoir unit in the Santos Basin. Available data included gramma-ray, neutron porosity, resistivity deep, sonic, density, photoelectric factor, total porosity and effective porosity profiles from 21 wells together with mineralogical models. Core descriptions and thin section images were used as additional data for the lithological characterization of the electrofacies and consequently for reservoir zonation. A total of four electrofacies were defined from the SOM application, and five reservoir zones were identified.
The characterization of the reservoir zones also considered the structural locations of the wells based on the relative depth to top- Barra Velha Formation; well locations were classified as structurally high, intermediate or low. Based on the reservoir zone characteristics, the results could be correlated with zonations in previous studies. A general tendency was noted for there to be an increase of finer-grained sediments in the formation in wells located in structural lows; packstone and mudstone facies were prevalent in these wells and were in general characterized as poor-quality reservoir rocks. By contrast, the shrubstones and grainstones which were more frequent in structurally high wells comprised higher quality reservoir rocks.
The basal reservoir zone showed wide lithological variation compared to the overlying reservoir zones. Grainstone-dominated facies were identified in the middle of the formation, and the uppermost reservoir zones were characterized by an upward increase in shrubstones and reworked grainstones which in general pointed to better quality reservoirs.
期刊介绍:
Journal of Petroleum Geology is a quarterly journal devoted to the geology of oil and natural gas. Editorial preference is given to original papers on oilfield regions of the world outside North America and on topics of general application in petroleum exploration and development operations, including geochemical and geophysical studies, basin modelling and reservoir evaluation.