Pub Date : 2019-08-12DOI: 10.3997/2214-4609.201901512
A. Adler, M. Araya-Polo, T. Poggio
This paper introduces novel deep recurrent neural network architectures for Velocity Model Building (VMB), which is beyond what Araya-Polo et al 2018 pioneered with the Machine Learning-based seismic tomography built with convolutional non-recurrent neural network. Our investigation includes the utilization of basic recurrent neural network (RNN) cells, as well as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) cells. Performance evaluation reveals that salt bodies are consistently predicted more accurately by GRU and LSTM-based architectures, as compared to non-recurrent architectures. The results take us a step closer to the final goal of a reliable fully Machine Learning-based tomography from pre-stack data, which when achieved will reduce the VMB turnaround from weeks to days.
{"title":"Deep Recurrent Architectures for Seismic Tomography","authors":"A. Adler, M. Araya-Polo, T. Poggio","doi":"10.3997/2214-4609.201901512","DOIUrl":"https://doi.org/10.3997/2214-4609.201901512","url":null,"abstract":"This paper introduces novel deep recurrent neural network architectures for Velocity Model Building (VMB), which is beyond what Araya-Polo et al 2018 pioneered with the Machine Learning-based seismic tomography built with convolutional non-recurrent neural network. Our investigation includes the utilization of basic recurrent neural network (RNN) cells, as well as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) cells. Performance evaluation reveals that salt bodies are consistently predicted more accurately by GRU and LSTM-based architectures, as compared to non-recurrent architectures. The results take us a step closer to the final goal of a reliable fully Machine Learning-based tomography from pre-stack data, which when achieved will reduce the VMB turnaround from weeks to days.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82180921","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 : 2019-06-19DOI: 10.3997/2214-4609.201901503
A. Kingdon, M. Bianchi, M. Fellgett, E. Hough, O. Kuras
Decarbonisation of energy supplies will require development of new technologies to store energy, heat and waste gases and to act as alternatives to batteries are required for storing renewable energy to make it available during periods of peak demand. The subsurface has the potential to deliver these new technologies through Carbon Capture and Storage (CCS), aquifer storage of heat and compressed air, and extracting geothermal energy. The heterogeneity of the subsurface and lack of detailed knowledge of its static and dynamic properties makes modelling of the efficacy of such proposed technologies difficult. Geoscientists require new experimental facilities where subsurface properties can be studied at unprecedented detail to underpin realistic simulations. The British Geological Survey, on behalf of the Natural Environment Research Council, is developing two new experimental facilities. The planned UK Geoenergy Observatory at Ince Marshes in Cheshire will allow a wide variety of datasets to be gathered on rocks, fluids and fluid transport, bespoke experiments to be undertaken and the properties of a volume of the rock to be understood. It will consist of four different arrays of newly-drilled and extensively-cored boreholes which will characterize the subsurface in greater detail than has previously been possible.
{"title":"UK Geoenergy Observatories: New Facilities to Understand the Future Energy Challenges","authors":"A. Kingdon, M. Bianchi, M. Fellgett, E. Hough, O. Kuras","doi":"10.3997/2214-4609.201901503","DOIUrl":"https://doi.org/10.3997/2214-4609.201901503","url":null,"abstract":"Decarbonisation of energy supplies will require development of new technologies to store energy, heat and waste gases and to act as alternatives to batteries are required for storing renewable energy to make it available during periods of peak demand. The subsurface has the potential to deliver these new technologies through Carbon Capture and Storage (CCS), aquifer storage of heat and compressed air, and extracting geothermal energy. \u0000 \u0000The heterogeneity of the subsurface and lack of detailed knowledge of its static and dynamic properties makes modelling of the efficacy of such proposed technologies difficult. Geoscientists require new experimental facilities where subsurface properties can be studied at unprecedented detail to underpin realistic simulations. \u0000The British Geological Survey, on behalf of the Natural \u0000Environment Research Council, is developing two new experimental facilities. The planned UK Geoenergy Observatory at Ince Marshes in Cheshire will allow a wide variety of datasets to be gathered on rocks, fluids and fluid transport, bespoke experiments to be undertaken and the properties of a volume of the rock to be understood. It will consist of four different arrays of newly-drilled and extensively-cored boreholes which will characterize the subsurface in greater detail than has previously been possible.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84942661","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 : 2019-06-06DOI: 10.3997/2214-4609.201900745
R. Yusefzadeh, M. Sharifi, Y. Rafiei, S. Shariatipour
{"title":"A New Approach for Determining Optimum Location of Injection Wells Using an Efficient Dynamic Based Method","authors":"R. Yusefzadeh, M. Sharifi, Y. Rafiei, S. Shariatipour","doi":"10.3997/2214-4609.201900745","DOIUrl":"https://doi.org/10.3997/2214-4609.201900745","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81793073","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 : 2019-06-05DOI: 10.3997/2214-4609.201901238
A. Butcher, J. Kendall, R. Luckett
{"title":"Microseismic Magnitudes: Challenges in Determining the Correct Moment and Operating Regulatory Frameworks","authors":"A. Butcher, J. Kendall, R. Luckett","doi":"10.3997/2214-4609.201901238","DOIUrl":"https://doi.org/10.3997/2214-4609.201901238","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79360497","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 : 2019-06-03DOI: 10.3997/2214-4609.201901216
P. Mitchell, R. Chassagne
Summary 4D Assisted Seismic History Matching (4D ASHM) has been implemented and successfully applied to the Harding South field in the North Sea. A Success-History Based Parameter Adaption Differential Evolutionary (SHADE) algorithm was used to minimise an objective function derived from the observed and simulated 4D seismic data. Quantitative misfit values for the objective function were computed by binarisation of 4D attribute maps extracted from the observed and simulated 4D difference volumes. Multipliers of several reservoir model parameters including net-to-gross ratio, porosity, permeability and fault transmissibility were automatically updated through fifteen genetic evolutions with ten individuals in each generation. Reservoir simulations were run for each individual's model parameters and the property grids used to compute saturations, impedances and synthetic 4D seismic volumes through production time. The 4D ASHM process converged to stable solutions after 15 genetic evolutions. The objective function reached a minimum value with low variance and the the seven reservoir parameters reached stable values. The net-to-gross ratio and porosity were increased to provide a larger oil volume. The match between the observed and modelled 4D seismic data improved and the history-match to the producing wells was significantly better.
{"title":"4D Assisted Seismic History Matching Using a Differential Evolution Algorithm at the Harding South Field","authors":"P. Mitchell, R. Chassagne","doi":"10.3997/2214-4609.201901216","DOIUrl":"https://doi.org/10.3997/2214-4609.201901216","url":null,"abstract":"Summary 4D Assisted Seismic History Matching (4D ASHM) has been implemented and successfully applied to the Harding South field in the North Sea. A Success-History Based Parameter Adaption Differential Evolutionary (SHADE) algorithm was used to minimise an objective function derived from the observed and simulated 4D seismic data. Quantitative misfit values for the objective function were computed by binarisation of 4D attribute maps extracted from the observed and simulated 4D difference volumes. Multipliers of several reservoir model parameters including net-to-gross ratio, porosity, permeability and fault transmissibility were automatically updated through fifteen genetic evolutions with ten individuals in each generation. Reservoir simulations were run for each individual's model parameters and the property grids used to compute saturations, impedances and synthetic 4D seismic volumes through production time. The 4D ASHM process converged to stable solutions after 15 genetic evolutions. The objective function reached a minimum value with low variance and the the seven reservoir parameters reached stable values. The net-to-gross ratio and porosity were increased to provide a larger oil volume. The match between the observed and modelled 4D seismic data improved and the history-match to the producing wells was significantly better.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"25 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73491668","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 : 2019-06-03DOI: 10.3997/2214-4609.201901331
Y. Liu, X. Xie, L. Kang, N. Guo, W. Wang
{"title":"A Quantitative Evaluation Method for Fault Lateral Sealing Based on Three-Dimensional Lithofacies Modelling","authors":"Y. Liu, X. Xie, L. Kang, N. Guo, W. Wang","doi":"10.3997/2214-4609.201901331","DOIUrl":"https://doi.org/10.3997/2214-4609.201901331","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73875762","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 : 2019-06-03DOI: 10.3997/2214-4609.201901553
Z. Shi, L. Xue, B. Chen
{"title":"Forming Conditions and Characteristics of Far-source Lithologic Reservoirs of Paleocene Yabus Formation, Melut Basin","authors":"Z. Shi, L. Xue, B. Chen","doi":"10.3997/2214-4609.201901553","DOIUrl":"https://doi.org/10.3997/2214-4609.201901553","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"147 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75181262","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 : 2019-06-03DOI: 10.3997/2214-4609.201900985
Y. Zhao, G. Tian, Z. Xiao, D. Wang, Y. Liu
{"title":"Estimation of Reservoir Porosity and Water Saturation through Phase Dispersion Rate of Complex Resistivity Logging","authors":"Y. Zhao, G. Tian, Z. Xiao, D. Wang, Y. Liu","doi":"10.3997/2214-4609.201900985","DOIUrl":"https://doi.org/10.3997/2214-4609.201900985","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73010180","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 : 2019-06-03DOI: 10.3997/2214-4609.201901328
T. Manzocchi, A. Heath, C. Childs, I. Telles, M. Carneiro
{"title":"Modelling Fault Zone Displacement Partitioning for Risking Across-Fault Juxtaposition","authors":"T. Manzocchi, A. Heath, C. Childs, I. Telles, M. Carneiro","doi":"10.3997/2214-4609.201901328","DOIUrl":"https://doi.org/10.3997/2214-4609.201901328","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73213766","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 : 2019-06-03DOI: 10.3997/2214-4609.201900752
K. Epov
An approach to quantitative incorporation of geological knowledge into the seismic inversion process is presented. Information about depositional environments and geological evolution of the sedimentary basin along with well logs interpretation and petro-elastic modeling data are used not only for background model building and inversion regularization, but also for inversion results interpretation and reservoir properties prediction. The method is based on the parameterization of the geological model using so-called “generalized geological variables” or G-Factors. These variables provide a quantitative description of the range of observed or expected facies. Topological and metric properties of the model are defined by a set of reference sedimentary environments and estimates of facies transitions probabilities. The method aims at solving a well-known problem of a-priori facies probabilities estimation required within the Bayesian framework. It can be applied in workflows involving either deterministic or stochastic inversion algorithms.
{"title":"Reconciling Geology with Geophysics: Estimating A-Priori Facies Probabilities for Seismic Amplitudes Inversion. Part 1, Theory","authors":"K. Epov","doi":"10.3997/2214-4609.201900752","DOIUrl":"https://doi.org/10.3997/2214-4609.201900752","url":null,"abstract":"An approach to quantitative incorporation of geological knowledge into the seismic inversion process is presented. Information about depositional environments and geological evolution of the sedimentary basin along with well logs interpretation and petro-elastic modeling data are used not only for background model building and inversion regularization, but also for inversion results interpretation and reservoir properties prediction. The method is based on the parameterization of the geological model using so-called “generalized geological variables” or G-Factors. These variables provide a quantitative description of the range of observed or expected facies. Topological and metric properties of the model are defined by a set of reference sedimentary environments and estimates of facies transitions probabilities. The method aims at solving a well-known problem of a-priori facies probabilities estimation required within the Bayesian framework. It can be applied in workflows involving either deterministic or stochastic inversion algorithms.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75318256","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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