Pub Date : 2021-09-08DOI: 10.3997/2214-4609.202183041
F. Neves, João Marcos Domingues Dias, C. Ribeiro, P. Coelho, G. Raitz, H. Santos, J. Santos, D. Silva, M. Arena, J. Favoreto, L. Borghi
Summary The Lower Cretaceous Barra Velha (BVE) unit is the main reservoir in our area of study, which consists of heterogeneous carbonates beneath a thick salt layer. Pre-Salt wells have shown that underneath the BVE reservoir, there could be several non-reservoir rocks (e.g., microporous carbonates, shales, volcanics) embedded in different formations that are hard to predict pre-drill. This poses a challenge, as BVE reservoir thickness and quality could be affected by a variety of underlying geological formations with distinct lithologies and facies. The Aptian BVE Formation consists of several hundred meters thick dolomitized limestones and shales. The mud-poor section is the main reservoir interval. The Itapema Fm. consists of thick (hundreds of meters) limestones (including coquinas) and organic rich shales. The Barremian Picarras Fm. is mostly made up of clastic and carbonate rocks, that contain conglomerates, with clasts of basalt and quartz and talc-stevensite shales. Finally, the lowermost and oldest Camboriu Fm. consists mainly of basalts. Despite efforts to understand the main factors driving the BVE reservoir elastic and seismic behavior for 3D and 4D interpretations and reservoir characterization, we still miss advanced geophysical analysis of the interfaces between different geological units that are important for quantitative seismic interpretation.
{"title":"Characterization of Barra Velha Reservoir-Non Reservoir Interfaces in a Pre-Salt Field in Santos Basin-Brazil Using Seismic AVO Modelling.","authors":"F. Neves, João Marcos Domingues Dias, C. Ribeiro, P. Coelho, G. Raitz, H. Santos, J. Santos, D. Silva, M. Arena, J. Favoreto, L. Borghi","doi":"10.3997/2214-4609.202183041","DOIUrl":"https://doi.org/10.3997/2214-4609.202183041","url":null,"abstract":"Summary The Lower Cretaceous Barra Velha (BVE) unit is the main reservoir in our area of study, which consists of heterogeneous carbonates beneath a thick salt layer. Pre-Salt wells have shown that underneath the BVE reservoir, there could be several non-reservoir rocks (e.g., microporous carbonates, shales, volcanics) embedded in different formations that are hard to predict pre-drill. This poses a challenge, as BVE reservoir thickness and quality could be affected by a variety of underlying geological formations with distinct lithologies and facies. The Aptian BVE Formation consists of several hundred meters thick dolomitized limestones and shales. The mud-poor section is the main reservoir interval. The Itapema Fm. consists of thick (hundreds of meters) limestones (including coquinas) and organic rich shales. The Barremian Picarras Fm. is mostly made up of clastic and carbonate rocks, that contain conglomerates, with clasts of basalt and quartz and talc-stevensite shales. Finally, the lowermost and oldest Camboriu Fm. consists mainly of basalts. Despite efforts to understand the main factors driving the BVE reservoir elastic and seismic behavior for 3D and 4D interpretations and reservoir characterization, we still miss advanced geophysical analysis of the interfaces between different geological units that are important for quantitative seismic interpretation.","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87399812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-08DOI: 10.3997/2214-4609.202183011
Nayara Mendes Cruz, J. N. Cruz, M. Costa, E. Urasaki, L. Teixeira, M. H. Grochau
Summary PETROBRAS concluded in 2020 the pioneering seismic project for monitoring Pre-Salt reservoirs, known as the Tupi Nodes Pilot project, using the time-lapse technique. The project involved 4D feasibility studies, two ocean-bottom-nodes (OBN) surveys and 4D seismic interpretation. Particularly for the Tupi field, but with the promise of serving as a field test for the entire Pre-Salt section, these 4D OBN surveys and studies will hopefully assist to identify oil-bypassed targets for infill wells, optimize the use of intelligent completion valves to improve the reservoir overall sweep and calibrate the water-alternating-gas (WAG) injection cycles to increase oil recovery. Given the technological character of this pilot, it is a huge achievement that time-lapse images reveal the capability of 4D seismic to correctly distinguish discrete fluid variations and its paths through the stiff carbonate reservoirs of Tupi field. The technical-entrepreneurial success of Tupi Nodes Pilot has become a reference for the entire oil industry and already underpins new 4D projects for the Brazilian Pre-Salt. This success reflects the interdisciplinary engagement of geophysicists, geologists and engineers from PETROBRAS Exploration and Reservoir Development areas.
{"title":"4D Seismic Applied to Pre-Salt Carbonate Reservoirs: Challenges and Results from Tupi Pilot, Santos Basin","authors":"Nayara Mendes Cruz, J. N. Cruz, M. Costa, E. Urasaki, L. Teixeira, M. H. Grochau","doi":"10.3997/2214-4609.202183011","DOIUrl":"https://doi.org/10.3997/2214-4609.202183011","url":null,"abstract":"Summary PETROBRAS concluded in 2020 the pioneering seismic project for monitoring Pre-Salt reservoirs, known as the Tupi Nodes Pilot project, using the time-lapse technique. The project involved 4D feasibility studies, two ocean-bottom-nodes (OBN) surveys and 4D seismic interpretation. Particularly for the Tupi field, but with the promise of serving as a field test for the entire Pre-Salt section, these 4D OBN surveys and studies will hopefully assist to identify oil-bypassed targets for infill wells, optimize the use of intelligent completion valves to improve the reservoir overall sweep and calibrate the water-alternating-gas (WAG) injection cycles to increase oil recovery. Given the technological character of this pilot, it is a huge achievement that time-lapse images reveal the capability of 4D seismic to correctly distinguish discrete fluid variations and its paths through the stiff carbonate reservoirs of Tupi field. The technical-entrepreneurial success of Tupi Nodes Pilot has become a reference for the entire oil industry and already underpins new 4D projects for the Brazilian Pre-Salt. This success reflects the interdisciplinary engagement of geophysicists, geologists and engineers from PETROBRAS Exploration and Reservoir Development areas.","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82093091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-08DOI: 10.3997/2214-4609.202183042
E. Lira, R. M. Mendes
Summary Several activities in geosciences are supported by hard data, which are represented by trustworthy information. However, not all wells offer basic logs such as sonic and density. This kind of information is significant for characterization in reservoir geophysics. This case study proposes a combination of Multilayer Perceptron (MLP) tools that constitute a type of Artificial Neural Network (ANN) and the Ensemble Machine Learning (EML) technique, in the prediction of missing or imputation log data based on the dataset of the Campos Basin. Such machine learning tools are considered robust, fast, and low cost, widely used in several areas. The study explores the combination of MLP and EML in the development of the learning algorithm. The use of MLP was “tuned” with optimal hyperparameters through GridSearch and the EML built through the Voting Estimator technique in a weighted way through the Scikit-learn library. It’s selected well logs like sonic, density, porosity, among other information for training. The velocity profile was selected as the prediction target. The best calculation parameters and errors of ensemble machine learners were generated, and thus, to analyze the generalizability of the algorithms. And finally, the EML Results were compared with the test samples.
{"title":"Case Study: Neural Network Implementation in Ensemble Machine Learning for Well Log Estimation, Case Applied in Campos Basin","authors":"E. Lira, R. M. Mendes","doi":"10.3997/2214-4609.202183042","DOIUrl":"https://doi.org/10.3997/2214-4609.202183042","url":null,"abstract":"Summary Several activities in geosciences are supported by hard data, which are represented by trustworthy information. However, not all wells offer basic logs such as sonic and density. This kind of information is significant for characterization in reservoir geophysics. This case study proposes a combination of Multilayer Perceptron (MLP) tools that constitute a type of Artificial Neural Network (ANN) and the Ensemble Machine Learning (EML) technique, in the prediction of missing or imputation log data based on the dataset of the Campos Basin. Such machine learning tools are considered robust, fast, and low cost, widely used in several areas. The study explores the combination of MLP and EML in the development of the learning algorithm. The use of MLP was “tuned” with optimal hyperparameters through GridSearch and the EML built through the Voting Estimator technique in a weighted way through the Scikit-learn library. It’s selected well logs like sonic, density, porosity, among other information for training. The velocity profile was selected as the prediction target. The best calculation parameters and errors of ensemble machine learners were generated, and thus, to analyze the generalizability of the algorithms. And finally, the EML Results were compared with the test samples.","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84578600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183004
J. Dias, J. Lopez, F. Perosi, L. Borghi
{"title":"A Workflow for 4D Seismic Analysis Based on Carbonate Rock Physics Applied to Brazil Pre-Salt","authors":"J. Dias, J. Lopez, F. Perosi, L. Borghi","doi":"10.3997/2214-4609.202183004","DOIUrl":"https://doi.org/10.3997/2214-4609.202183004","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81717118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183025
C. Gans, X. Li, Y. Cha, M. Fabijanić
{"title":"Innovative New Workflow for Rapid Salt Scenario Testing Through 3D Mesh Interpretation, FWI, and Tomography: Brazil Pre-Salt Case Study","authors":"C. Gans, X. Li, Y. Cha, M. Fabijanić","doi":"10.3997/2214-4609.202183025","DOIUrl":"https://doi.org/10.3997/2214-4609.202183025","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81466408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183023
O. P. Wennberg, F. De Oliveira Ramalho, M. V. Mafia, F. Lapponi, A. S. Chandler, L. G. Cartesio
{"title":"Fracture Characteristics and Some Controls on their Occurrence in the Barra Velha Formation in the Santos Basin","authors":"O. P. Wennberg, F. De Oliveira Ramalho, M. V. Mafia, F. Lapponi, A. S. Chandler, L. G. Cartesio","doi":"10.3997/2214-4609.202183023","DOIUrl":"https://doi.org/10.3997/2214-4609.202183023","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87277453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183029
E. Pedersen, L. Rodríguez, G. Jones, H. Qualman
{"title":"Insights from Process-Based Models and Integration with Reservoir Characterization and Rock Typing Workflows for the Pre-Salt Lacustrine Carbonate Reservoirs","authors":"E. Pedersen, L. Rodríguez, G. Jones, H. Qualman","doi":"10.3997/2214-4609.202183029","DOIUrl":"https://doi.org/10.3997/2214-4609.202183029","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90950417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183030
T. Ramstad, A. Kristoffersen, L. Rennan, R. Wat, C.J.T. De Lima
{"title":"Micro-CT Imaging of Low Salinity Water Induced EOR Mechanisms in Pre-Salt Carbonates","authors":"T. Ramstad, A. Kristoffersen, L. Rennan, R. Wat, C.J.T. De Lima","doi":"10.3997/2214-4609.202183030","DOIUrl":"https://doi.org/10.3997/2214-4609.202183030","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"54 5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90970758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183024
C. Breithaupt, P. Moore, J. Gulley, F. Fernandez-ibanez, S. Fullmer, C. Kerans, D. Cleavland
{"title":"New Concepts for Karst Architecture in Carbonate Reservoirs: Insights from San Salvador Island Bahamas","authors":"C. Breithaupt, P. Moore, J. Gulley, F. Fernandez-ibanez, S. Fullmer, C. Kerans, D. Cleavland","doi":"10.3997/2214-4609.202183024","DOIUrl":"https://doi.org/10.3997/2214-4609.202183024","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87428969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.3997/2214-4609.202183022
P. Álvarez, A.C. Araüjo, N. Stanton, J. P. Oliveira, R. Ferro, M. Iemma, I. Nascimento, L. Borghi
{"title":"Crustal Features and Transfer Zone of Campos Basin: A Review and Evaluation","authors":"P. Álvarez, A.C. Araüjo, N. Stanton, J. P. Oliveira, R. Ferro, M. Iemma, I. Nascimento, L. Borghi","doi":"10.3997/2214-4609.202183022","DOIUrl":"https://doi.org/10.3997/2214-4609.202183022","url":null,"abstract":"","PeriodicalId":21695,"journal":{"name":"Second EAGE Conference on Pre-Salt Reservoir","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90432326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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