Mousa Hosseinimehr, M. A. Kobaisi, C. Vuik, H. Hajibeygi
An algebraic dynamic multilevel (ADM) method for multiphase flow in heterogeneous fractured porous media using the projection-based embedded discrete fracture model (pEDFM) is presented. The fine-scale discrete system is obtained independently for matrix and each lower-dimensional fracture. On the fine-scale high resolution computational grids, an independent dynamic multilevel gird (i.e., ADM grid) is imposed. The fully implicit discrete system is mapped completely algebraically to this ADM grid resolution using sequences of restriction and prolongation operators. Multilevel multiscale basis functions are locally computed and employed to honor the heterogeneity contrasts of the fractured domain by interpolating the solution accurately. These basis functions are computed only at the beginning of the simulation to increase the computational efficiency. Once the ADM system is solved for all unknowns (i.e., pressure and saturation), the solution at ADM resolution is prolonged back to fine-scale resolution in order to obtain an approximated fine-scale solution. This dynamic multilevel system employs the fine-scale grid cells only at the sharp gradient of the solution (e.g., at the moving front). With two fractured test-cases (homogeneous and heterogeneous), the performance of ADM is assessed by comparing it to fine-scale results as reference solution. It will be shown that ADM is able to reduce the computational costs and provide efficiency while maintaining the desired accuracy.
{"title":"Dynamic Multilevel Multiscale Simulation of Naturally Fractured Reservoirs with Generic Fracture-Matrix Conductivity Contrasts","authors":"Mousa Hosseinimehr, M. A. Kobaisi, C. Vuik, H. Hajibeygi","doi":"10.2118/196626-ms","DOIUrl":"https://doi.org/10.2118/196626-ms","url":null,"abstract":"\u0000 An algebraic dynamic multilevel (ADM) method for multiphase flow in heterogeneous fractured porous media using the projection-based embedded discrete fracture model (pEDFM) is presented. The fine-scale discrete system is obtained independently for matrix and each lower-dimensional fracture. On the fine-scale high resolution computational grids, an independent dynamic multilevel gird (i.e., ADM grid) is imposed. The fully implicit discrete system is mapped completely algebraically to this ADM grid resolution using sequences of restriction and prolongation operators. Multilevel multiscale basis functions are locally computed and employed to honor the heterogeneity contrasts of the fractured domain by interpolating the solution accurately. These basis functions are computed only at the beginning of the simulation to increase the computational efficiency. Once the ADM system is solved for all unknowns (i.e., pressure and saturation), the solution at ADM resolution is prolonged back to fine-scale resolution in order to obtain an approximated fine-scale solution. This dynamic multilevel system employs the fine-scale grid cells only at the sharp gradient of the solution (e.g., at the moving front). With two fractured test-cases (homogeneous and heterogeneous), the performance of ADM is assessed by comparing it to fine-scale results as reference solution. It will be shown that ADM is able to reduce the computational costs and provide efficiency while maintaining the desired accuracy.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79605416","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}
P. Salinas, C. Jacquemyn, A. Kampitsis, L. Via-Estrem, C. Heaney, C. Pain, M. Jackson
The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier- Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.
{"title":"A Parallel Load-Balancing Reservoir Simulator with Dynamic Mesh Optimisation","authors":"P. Salinas, C. Jacquemyn, A. Kampitsis, L. Via-Estrem, C. Heaney, C. Pain, M. Jackson","doi":"10.2118/196664-ms","DOIUrl":"https://doi.org/10.2118/196664-ms","url":null,"abstract":"\u0000 The use of dynamic mesh optimization (DMO) for multiphase flow in porous have been proposed recently showing a very good potential to reduce the computational cost by placing the resolution where and when necessary. Nonetheless, further work needs to be done to prove its usability in very large domains where parallel computing with distributed memory, i.e. using MPI libraries, may be necessary. Here, we describe the methodology used to parallelize a multiphase porous media flow simulator in combination with DMO as well as study of its performance. Due to the peculiarities and complexities of the typical porous media simulations due to its high aspect ratios, we have included a fail-safe for parallel simulations with DMO that enhance the robustness and stability of the methods used to parallelize DMO in other fields (Navier- Stokes flows). The results show that DMO for parallel computing in multiphase porous media flows can perform very well, showing good scaling behaviour.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85005132","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}
This challenging reservoir characterization case study is defined by the interaction between two reservoirs with different production mechanisms: a fractured basement reservoir and an overlying sandstone reservoir. The existing static geologic concept has been significantly enhanced by integrating pressure data from a unique three-year shut-in period to aid modeling of fractured reservoir connectivity. Previously, the seismic dataset was predominantly used to model the fault and fracture network and guide well planning. In the current approach, the full field data set, including all drilling parameters and new reservoir surveillance data were integrated to address uncertainty in the connected hydrocarbon volume and the relative importance of each production mechanism. The result is a reservoir management tool with which to test re-development concepts and effectively manage pressure decline and increasing gas/oil ratio (GOR) and water production. To achieve a fully integrated history matched model, the first step was to make a thorough review of the existing detailed seismic interpretation, vintage production logging tool runs (PLT's), wireline logs (including borehole image logs (BHI)) and drilling data to find a causal link between hydraulically conductive fractures and well production behavior. In parallel, a material balance exercise was run to incorporate the new pressure data acquired during the field's shut-in period. The results of the material balance analysis were combined with seismic and well data to define the distribution of connected fractures across the field. Additionally, the material balance analysis was used to determine the connected hydrocarbon volume, the distribution of initial oil in-place and the relative hydrocarbon contribution from each production mechanism. The field is covered by multi-azimuth 3D seismic and 43 vertical to highly deviated development wells, providing significant static and dynamic data for characterizing the distribution of connected fractures. Despite this high quality, diverse and field-wide dataset, prior modeling iterations struggled to sufficiently describe the production behavior seen at the well level. This has resulted in a major challenge to predicting the production behavior of new development wells and planning for reservoir management challenges. Capturing the complex interaction between production variables (including lithology, matrix versus fracture network, geomechanical stresses, reservoir damage and pressure depletion) at a field level instead of at an individual well level resulted in a unified static and dynamic model that reconciles all scales of observation. This oilfield represents a unique reservoir characterization opportunity. The result is a key example of how iterative, integrated geological and engineering driven reservoir modeling can be used to inform the development in a complex, mature field. This case study provides an excellent analogue for the reservoir chara
{"title":"Dynamically Conditioned Modeling to Address Development Challenges in a Highly Complex Fractured Basement Reservoir, Yemen","authors":"A. McGeer, Mohammad Oggi Refani","doi":"10.2118/196720-ms","DOIUrl":"https://doi.org/10.2118/196720-ms","url":null,"abstract":"\u0000 This challenging reservoir characterization case study is defined by the interaction between two reservoirs with different production mechanisms: a fractured basement reservoir and an overlying sandstone reservoir. The existing static geologic concept has been significantly enhanced by integrating pressure data from a unique three-year shut-in period to aid modeling of fractured reservoir connectivity. Previously, the seismic dataset was predominantly used to model the fault and fracture network and guide well planning. In the current approach, the full field data set, including all drilling parameters and new reservoir surveillance data were integrated to address uncertainty in the connected hydrocarbon volume and the relative importance of each production mechanism. The result is a reservoir management tool with which to test re-development concepts and effectively manage pressure decline and increasing gas/oil ratio (GOR) and water production.\u0000 To achieve a fully integrated history matched model, the first step was to make a thorough review of the existing detailed seismic interpretation, vintage production logging tool runs (PLT's), wireline logs (including borehole image logs (BHI)) and drilling data to find a causal link between hydraulically conductive fractures and well production behavior. In parallel, a material balance exercise was run to incorporate the new pressure data acquired during the field's shut-in period. The results of the material balance analysis were combined with seismic and well data to define the distribution of connected fractures across the field. Additionally, the material balance analysis was used to determine the connected hydrocarbon volume, the distribution of initial oil in-place and the relative hydrocarbon contribution from each production mechanism.\u0000 The field is covered by multi-azimuth 3D seismic and 43 vertical to highly deviated development wells, providing significant static and dynamic data for characterizing the distribution of connected fractures. Despite this high quality, diverse and field-wide dataset, prior modeling iterations struggled to sufficiently describe the production behavior seen at the well level. This has resulted in a major challenge to predicting the production behavior of new development wells and planning for reservoir management challenges. Capturing the complex interaction between production variables (including lithology, matrix versus fracture network, geomechanical stresses, reservoir damage and pressure depletion) at a field level instead of at an individual well level resulted in a unified static and dynamic model that reconciles all scales of observation.\u0000 This oilfield represents a unique reservoir characterization opportunity. The result is a key example of how iterative, integrated geological and engineering driven reservoir modeling can be used to inform the development in a complex, mature field. This case study provides an excellent analogue for the reservoir chara","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73214034","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}
This paper discusses a method for optimizing production and operation for onshore/offshore wells. Optimizing the production of oil and gas fields necessitates the use of accurate predication techniques to minimize uncertainties associated with day-to-day operational challenges related to serious operational problems caused by asphaltene deposition. It involves the use of a dynamic flow simulator for modeling oil and gas production systems and reservoir management to determine the feasibility of its economic development. Many studies have focused on relating asphaltene precipitation flocculation and deposition in oil reservoirs and flow assurance in the wellbores. Experimental techniques and theoretical models have been developed trying to understand and predict asphaltene behavior. Nevertheless, some ambiguities still remain with regard to the characterization asphaltene in crude oil and its stability during the primary, secondary, and tertiary recovery stages within the near-wellbore regions. A synthetic onshore full-field scale that is based on a heterogeneous three-dimensional Cartesian single-well model is considered in this paper. Two wells (a producer and an injector) and one reservoirs are considered to evaluate the dynamic properties under the influence of asphaltene. The size of the reservoir is 25 ft × 25ft × 20 ft and is represented by grid numbers of 50 columns × 50 rows × 5 layers with 12 hydrocarbon components constituting the constant crude composition of this model. The model comprised a total of 12,500 grid blocks. The three-dimensional simulation employed 5-layers, incorporating all relevant production and reservoir data. Different production scenarios were investigated to define the most appropriate and efficient production strategy. This paper provides a method to assess the effect of asphaltene precipitation, flocculation, and deposition in the well productivity and the economic impacts related to it and investigating prevention techniques and other related in-situ pore level flow assurance parameters. The results will include a comparison of production rates with and without asphaltene precipitation, flocculation, and deposition. In addition, it provides a comparison of asphaltene precipitation, flocculation, and deposition at different times using varying bottomhole and production rate constraints. Several cases (i.e., WAG cycles, completion, target layers of injection, etc.) are tested to help in selection of the optimum completion and operating strategy in the presences asphaltene. The paper will provide insight into factors affecting the flow assurance of oil and gas reservoirs.
{"title":"Oilfield Performance in the Presence of Asphaltene Using a Dynamic Flow Simulation","authors":"Abdulaziz Alqasim, Amer Al-Anazi, R. Miftakhov","doi":"10.2118/196681-ms","DOIUrl":"https://doi.org/10.2118/196681-ms","url":null,"abstract":"\u0000 This paper discusses a method for optimizing production and operation for onshore/offshore wells. Optimizing the production of oil and gas fields necessitates the use of accurate predication techniques to minimize uncertainties associated with day-to-day operational challenges related to serious operational problems caused by asphaltene deposition. It involves the use of a dynamic flow simulator for modeling oil and gas production systems and reservoir management to determine the feasibility of its economic development. Many studies have focused on relating asphaltene precipitation flocculation and deposition in oil reservoirs and flow assurance in the wellbores. Experimental techniques and theoretical models have been developed trying to understand and predict asphaltene behavior. Nevertheless, some ambiguities still remain with regard to the characterization asphaltene in crude oil and its stability during the primary, secondary, and tertiary recovery stages within the near-wellbore regions.\u0000 A synthetic onshore full-field scale that is based on a heterogeneous three-dimensional Cartesian single-well model is considered in this paper. Two wells (a producer and an injector) and one reservoirs are considered to evaluate the dynamic properties under the influence of asphaltene. The size of the reservoir is 25 ft × 25ft × 20 ft and is represented by grid numbers of 50 columns × 50 rows × 5 layers with 12 hydrocarbon components constituting the constant crude composition of this model. The model comprised a total of 12,500 grid blocks. The three-dimensional simulation employed 5-layers, incorporating all relevant production and reservoir data. Different production scenarios were investigated to define the most appropriate and efficient production strategy. This paper provides a method to assess the effect of asphaltene precipitation, flocculation, and deposition in the well productivity and the economic impacts related to it and investigating prevention techniques and other related in-situ pore level flow assurance parameters.\u0000 The results will include a comparison of production rates with and without asphaltene precipitation, flocculation, and deposition. In addition, it provides a comparison of asphaltene precipitation, flocculation, and deposition at different times using varying bottomhole and production rate constraints. Several cases (i.e., WAG cycles, completion, target layers of injection, etc.) are tested to help in selection of the optimum completion and operating strategy in the presences asphaltene. The paper will provide insight into factors affecting the flow assurance of oil and gas reservoirs.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90538333","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}
This paper discusses the use of a novel data-driven method for automated facies classification and characterization of carbonate reservoirs. The approach makes an extensive use of wireline and while drilling electrical borehole image logs and provides a direct and fast recognition of the main geological features at multi-scale level, together with secondary porosity estimation. This embodies an unbiased and valuable key-driver for rock typing, dynamic behavior understanding and reservoir modeling purposes in these puzzling scenarios. The implemented methodology takes advantage of a non-conventional approach to the analysis and interpretation of image logs, based upon image processing and automatic classification techniques applied in a structural and petrophysical framework. In particular, the Multi-Resolution Graph-based Clustering (MRGC) algorithm that is able to automatically shed light on the significant patterns hidden in a given image log dataset. This allows the system to perform an objective multi-well analysis within a time-efficient template. A further characterization of the facies can be established by means of the Watershed Transform (WT) approach, based on digital image segmentation processes and which is mainly aimed at quantitative porosity partition (primary and secondary). The added value from this data-driven image log analysis is demonstrated through selected case studies coming from vertical and sub-horizontal wells in carbonate reservoirs characterized by high heterogeneity. First, the MRGC has been carried out in order to obtain an alternative log-facies classification with an inherent textural meaning. Next, the WT-based algorithm provided a robust quantification of the secondary porosity contribution to total porosity, in terms of connected vugs, isolated vugs, fractures and matrix contribution rates. Finally, image log-facies classification and quantitative porosity partition have been integrated with production logs and pressure transient analyses to reconcile the obtained carbonate rock types with the effective fluid flows and the associated dynamic behavior at well scale. The presented novel methodology is deemed able to perform an automatic, objective and advanced interpretation of field-scale image log datasets, avoiding time-consuming conventional processes and inefficient standard analyses when the number of wells to be handled is large and/or in harsh circumstances. Moreover, secondary porosity can be proficiently identified, evaluated and also characterized from the dynamic standpoint, hence representing a valuable information for any 3D reservoir models.
{"title":"Smart Processing and Analysis of Image Log Data: A Digital Approach for a Robust Facies Modelling in Heterogeneous Carbonate Reservoirs","authors":"M. Galli, R. Berto, G. Buongiovanni, M. Pirrone","doi":"10.2118/196651-ms","DOIUrl":"https://doi.org/10.2118/196651-ms","url":null,"abstract":"\u0000 This paper discusses the use of a novel data-driven method for automated facies classification and characterization of carbonate reservoirs. The approach makes an extensive use of wireline and while drilling electrical borehole image logs and provides a direct and fast recognition of the main geological features at multi-scale level, together with secondary porosity estimation. This embodies an unbiased and valuable key-driver for rock typing, dynamic behavior understanding and reservoir modeling purposes in these puzzling scenarios.\u0000 The implemented methodology takes advantage of a non-conventional approach to the analysis and interpretation of image logs, based upon image processing and automatic classification techniques applied in a structural and petrophysical framework. In particular, the Multi-Resolution Graph-based Clustering (MRGC) algorithm that is able to automatically shed light on the significant patterns hidden in a given image log dataset. This allows the system to perform an objective multi-well analysis within a time-efficient template. A further characterization of the facies can be established by means of the Watershed Transform (WT) approach, based on digital image segmentation processes and which is mainly aimed at quantitative porosity partition (primary and secondary).\u0000 The added value from this data-driven image log analysis is demonstrated through selected case studies coming from vertical and sub-horizontal wells in carbonate reservoirs characterized by high heterogeneity. First, the MRGC has been carried out in order to obtain an alternative log-facies classification with an inherent textural meaning. Next, the WT-based algorithm provided a robust quantification of the secondary porosity contribution to total porosity, in terms of connected vugs, isolated vugs, fractures and matrix contribution rates. Finally, image log-facies classification and quantitative porosity partition have been integrated with production logs and pressure transient analyses to reconcile the obtained carbonate rock types with the effective fluid flows and the associated dynamic behavior at well scale.\u0000 The presented novel methodology is deemed able to perform an automatic, objective and advanced interpretation of field-scale image log datasets, avoiding time-consuming conventional processes and inefficient standard analyses when the number of wells to be handled is large and/or in harsh circumstances. Moreover, secondary porosity can be proficiently identified, evaluated and also characterized from the dynamic standpoint, hence representing a valuable information for any 3D reservoir models.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87243958","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}
Prem Dayal Saini, E. Steen, S. D. Jong, Francien Van Den Berg
Hydrocarbon in place volumes are often inaccurate as a result of poor representation of the reservoir structure (by means of a 3D grid), that in combination with the use of traditional saturation calculation methods, lead to erroneous hydrocarbon volumes and poor investment decisions. Traditionally a reservoir model is represented with a 3D grid, in a complex setting such as fault intersections and stacked reservoirs. A corner point grid is often used, which has limitations to represent this complexity. Further, the hydrocarbon saturations are then derived on a cell by cell basis on that 3D grid using simple averaging techniques of saturation height functions. The poor structure representation on the pillar grid in addition to the simplistic averaging methods lead to inaccuracies of the in place volumes especially where a prominent transition zone is present. This paper presents new advanced saturation averaging methods (volume and height weighted) using saturation height functions on 3D grids. The new advanced saturation averaging methods are used on different reservoir models to compare the saturation distribution and volumetric differences against the traditional saturation calculation methods. A 4-way dip closure reservoir model with a tilted free water level (typical example of a carbonate reservoir in the Middle East), and a faulted S-grid model of the F3-FA field (North Sea) are used. For the 4-way dip closure reservoir model, when comparing the advanced ‘volume weighted’ and traditional ‘by center of the part of the cell’ saturation averaging methods, a significant difference in the water saturations is observed which leads to about 5% difference in the calculation of in place hydrocarbon volumes. Further, it is observed that changing the thickness and orientation of the 3D grid cells can result in even larger differences of 5-10%. The faulted F3 model shows that the difference between the hydrocarbon saturation values is largest where it matters most, that is, around the fluid contacts and in the transition zone. The new advanced saturation averaging methods give accurate hydrocarbon saturations irrespective of the size or complexity of the 3D grid and without any discretization effects.
{"title":"A New Method to Accurately Model Hydrocarbon Saturation in a Reservoir","authors":"Prem Dayal Saini, E. Steen, S. D. Jong, Francien Van Den Berg","doi":"10.2118/196705-ms","DOIUrl":"https://doi.org/10.2118/196705-ms","url":null,"abstract":"\u0000 Hydrocarbon in place volumes are often inaccurate as a result of poor representation of the reservoir structure (by means of a 3D grid), that in combination with the use of traditional saturation calculation methods, lead to erroneous hydrocarbon volumes and poor investment decisions.\u0000 Traditionally a reservoir model is represented with a 3D grid, in a complex setting such as fault intersections and stacked reservoirs. A corner point grid is often used, which has limitations to represent this complexity. Further, the hydrocarbon saturations are then derived on a cell by cell basis on that 3D grid using simple averaging techniques of saturation height functions. The poor structure representation on the pillar grid in addition to the simplistic averaging methods lead to inaccuracies of the in place volumes especially where a prominent transition zone is present.\u0000 This paper presents new advanced saturation averaging methods (volume and height weighted) using saturation height functions on 3D grids. The new advanced saturation averaging methods are used on different reservoir models to compare the saturation distribution and volumetric differences against the traditional saturation calculation methods. A 4-way dip closure reservoir model with a tilted free water level (typical example of a carbonate reservoir in the Middle East), and a faulted S-grid model of the F3-FA field (North Sea) are used.\u0000 For the 4-way dip closure reservoir model, when comparing the advanced ‘volume weighted’ and traditional ‘by center of the part of the cell’ saturation averaging methods, a significant difference in the water saturations is observed which leads to about 5% difference in the calculation of in place hydrocarbon volumes. Further, it is observed that changing the thickness and orientation of the 3D grid cells can result in even larger differences of 5-10%.\u0000 The faulted F3 model shows that the difference between the hydrocarbon saturation values is largest where it matters most, that is, around the fluid contacts and in the transition zone. The new advanced saturation averaging methods give accurate hydrocarbon saturations irrespective of the size or complexity of the 3D grid and without any discretization effects.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83358727","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}
A fully-implict mimetic finite difference method (MFD) for fractured carbonatereservoir simulation is presented. MFD, as a novel discritization, has been applied to many fields due to its local conservativeness and applicability of any shape of polygon. Here we extend it to fractured reservoirs. Our scheme is based on MFD method and discrete fracture model (DFM). This scheme supports general polyhedral meshes, which gives an advantage for reservoir simulation application. The principle of the MFD method and the corresponding numerical formula for discrete fracture model are described in details. In order to assure flux conservation, fully implicit method is employed. We test our method through some examples to show the accuracy and robustness.
{"title":"Fully Implicit Reservoir Simulation Using Mimetic Finite Difference Method in Fractured Carbonate Reservoirs","authors":"N. Zhang, A. Abushaikha","doi":"10.2118/196711-ms","DOIUrl":"https://doi.org/10.2118/196711-ms","url":null,"abstract":"\u0000 A fully-implict mimetic finite difference method (MFD) for fractured carbonatereservoir simulation is presented. MFD, as a novel discritization, has been applied to many fields due to its local conservativeness and applicability of any shape of polygon. Here we extend it to fractured reservoirs. Our scheme is based on MFD method and discrete fracture model (DFM). This scheme supports general polyhedral meshes, which gives an advantage for reservoir simulation application. The principle of the MFD method and the corresponding numerical formula for discrete fracture model are described in details. In order to assure flux conservation, fully implicit method is employed. We test our method through some examples to show the accuracy and robustness.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80653217","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}
Reservoir A is being developed in early and interim phases in order to gather static & dynamic data to minimize the risk associated to subsurface uncertainties. In early and interim phases, only production is taking places. During full field, water injection scheme will be implemented using mainly 5-spot pattern. It is very crucial to measure the subsurface uncertainties and their impact on the reservoir development. For this purpose, the uncertainty parameters are identified and their ranges are selected based on the current well performances during probabilistic History matching (PHM) phase. In full field runs, the uncertain subsurface parameters are quantified to prioritize the future reservoir monitoring and data gathering plans. Note that wells are equipped with the permanent downhole pressure gauges. Reservoir A is one of the major reservoirs of a green-field located offshore Abu Dhabi and is being developed with a 5-spot water injection pattern. The producers and water injectors are horizontal wells which are drilled across different flow unit within the reservoir. The reservoir properties are variable across all the flow units, which may results in a non-uniform water front. Being a green field, there are more uncertainties as compared to the brown field. More than three years production & pressure data is available which is used in this uncertainty study. This production data is mainly used to achieve the probabilistic History match on well-wise basis. In this uncertainty study, previous HM parameters are removed. However, based on previous history matching learnings, the subsurface uncertain parameters ranges are selected for this probabilistic History match phase. The criteria for filtering the valid runs during this phase are set to be ±150 Psi compared to the actual downhole pressure readings. In case of decreasing this filtering range to 75 Psi, results in reduction in the reserve range in P90 to P10. Based on ±150 Psi principle, the subsurface parameter ranges are furthered reformed for full field uncertainty study/run. The industry standard workflow is followed to quantify the subsurface parameters during this phase. In this study, we used the Permeability modifiers based on RRT, Faults transmisibilities, Relative Perm curves (based on SCAL data), Kv/Kh ratio (from PTA), etc. as uncertain parameters. The impact of each parameter is measured and quantified with respect to plateau and total reserves.
{"title":"Evaluation of Reservoir Dynamic Uncertainties in Digital Concept Based Green Field Before Implementation of Full Field Development Scheme","authors":"B. Altaf, A. Allouti","doi":"10.2118/196625-ms","DOIUrl":"https://doi.org/10.2118/196625-ms","url":null,"abstract":"\u0000 Reservoir A is being developed in early and interim phases in order to gather static & dynamic data to minimize the risk associated to subsurface uncertainties. In early and interim phases, only production is taking places. During full field, water injection scheme will be implemented using mainly 5-spot pattern. It is very crucial to measure the subsurface uncertainties and their impact on the reservoir development. For this purpose, the uncertainty parameters are identified and their ranges are selected based on the current well performances during probabilistic History matching (PHM) phase. In full field runs, the uncertain subsurface parameters are quantified to prioritize the future reservoir monitoring and data gathering plans. Note that wells are equipped with the permanent downhole pressure gauges.\u0000 Reservoir A is one of the major reservoirs of a green-field located offshore Abu Dhabi and is being developed with a 5-spot water injection pattern. The producers and water injectors are horizontal wells which are drilled across different flow unit within the reservoir. The reservoir properties are variable across all the flow units, which may results in a non-uniform water front. Being a green field, there are more uncertainties as compared to the brown field. More than three years production & pressure data is available which is used in this uncertainty study. This production data is mainly used to achieve the probabilistic History match on well-wise basis. In this uncertainty study, previous HM parameters are removed. However, based on previous history matching learnings, the subsurface uncertain parameters ranges are selected for this probabilistic History match phase. The criteria for filtering the valid runs during this phase are set to be ±150 Psi compared to the actual downhole pressure readings. In case of decreasing this filtering range to 75 Psi, results in reduction in the reserve range in P90 to P10. Based on ±150 Psi principle, the subsurface parameter ranges are furthered reformed for full field uncertainty study/run. The industry standard workflow is followed to quantify the subsurface parameters during this phase. In this study, we used the Permeability modifiers based on RRT, Faults transmisibilities, Relative Perm curves (based on SCAL data), Kv/Kh ratio (from PTA), etc. as uncertain parameters. The impact of each parameter is measured and quantified with respect to plateau and total reserves.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"1999 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88246317","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}
J. Ortiz, D. Klemin, O. Savelyev, J. Gossuin, S. Melnikov, A. Serebryanskaya, Yunlong Liu, O. Gurpinar, M. Salazar, Thaer Gheneim Herrera
Use of numerical models to characterize and evaluate reservoir potential is an industry wide practice, with increasingly more development decisions being substantiated by finite difference models. Advances on hardware and software, along with the ability to effectively incorporate accurate process physics, makes simulation a robust tool for field development decisions, particularly on complex operations such as enhanced oil recovery and/or reservoirs with challenging heterogeneity and pore structures. Use of these models does not come without its challenges where data requirements (and use of special characterization both at lab and field level) increase as does the reservoir characterization granularity and thus model sizes. Unsurprisingly the increase of model precision and data requirements amplifies non-uniqueness of the numerical solutions obtained during any field evaluation including field development planning (FDP). Incomplete/inconsistent datasets pose a further challenge to the accuracy (and arguably risk) of the forecasts by introducing further uncertainty on the process characterization. Use of complementary technology such as digital rock, that would enable mitigate impact of such uncertainties in a timely manner -either at field or laboratory level, is thus highly desirable particularly when dealing with enhanced oil recovery. Compounding the non-linearity effect of the EOR agent characterization is the effect of the augmented numerical artifacts (dispersion, dilution, etc) of which complex chemical implementations are prone to, making the upscaling process from laboratory dimensions to field more complex. This paper complements our previous investigation on the use of digital rock solutions and multi-scale upscaling and is addressing two complementing topics: Use of multiscale digital rock technology for field development – using a case study to illustrate the use of DR on field appraisal complementing otherwise unsampled facies, using a multi-nested approach to reconcile DR observations at different plug scalesEvaluate the impact of finite-difference numerical simulation grid on the surfactant injection performance- highlighting limitations and challenges of existing models as well as proposing potential upscaling alternatives. It is our intention to further reconcile digital rock upscaling with other EOR methods such as polymer/CO2 injection and of course surfactant. While we were able to highlight the caveats of upscaling on complex chemical floods we continue to investigate and design a solution that would encompass combination of chemicals (surfactant, alkaline and polymer) as well as handle of concentration/salinity changes.
{"title":"Advanced Eor Process Upscaling Using Multi-Scale Digital Verification Technology and FDP Application","authors":"J. Ortiz, D. Klemin, O. Savelyev, J. Gossuin, S. Melnikov, A. Serebryanskaya, Yunlong Liu, O. Gurpinar, M. Salazar, Thaer Gheneim Herrera","doi":"10.2118/196695-ms","DOIUrl":"https://doi.org/10.2118/196695-ms","url":null,"abstract":"\u0000 Use of numerical models to characterize and evaluate reservoir potential is an industry wide practice, with increasingly more development decisions being substantiated by finite difference models. Advances on hardware and software, along with the ability to effectively incorporate accurate process physics, makes simulation a robust tool for field development decisions, particularly on complex operations such as enhanced oil recovery and/or reservoirs with challenging heterogeneity and pore structures. Use of these models does not come without its challenges where data requirements (and use of special characterization both at lab and field level) increase as does the reservoir characterization granularity and thus model sizes.\u0000 Unsurprisingly the increase of model precision and data requirements amplifies non-uniqueness of the numerical solutions obtained during any field evaluation including field development planning (FDP). Incomplete/inconsistent datasets pose a further challenge to the accuracy (and arguably risk) of the forecasts by introducing further uncertainty on the process characterization. Use of complementary technology such as digital rock, that would enable mitigate impact of such uncertainties in a timely manner -either at field or laboratory level, is thus highly desirable particularly when dealing with enhanced oil recovery. Compounding the non-linearity effect of the EOR agent characterization is the effect of the augmented numerical artifacts (dispersion, dilution, etc) of which complex chemical implementations are prone to, making the upscaling process from laboratory dimensions to field more complex.\u0000 This paper complements our previous investigation on the use of digital rock solutions and multi-scale upscaling and is addressing two complementing topics: Use of multiscale digital rock technology for field development – using a case study to illustrate the use of DR on field appraisal complementing otherwise unsampled facies, using a multi-nested approach to reconcile DR observations at different plug scalesEvaluate the impact of finite-difference numerical simulation grid on the surfactant injection performance- highlighting limitations and challenges of existing models as well as proposing potential upscaling alternatives.\u0000 It is our intention to further reconcile digital rock upscaling with other EOR methods such as polymer/CO2 injection and of course surfactant. While we were able to highlight the caveats of upscaling on complex chemical floods we continue to investigate and design a solution that would encompass combination of chemicals (surfactant, alkaline and polymer) as well as handle of concentration/salinity changes.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76809250","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}
In this paper, the approach to multivariate static and dynamic modeling is considered on the example of an offshore field discovered in 2017. Based on the limited volume of information, the quantitative and qualitative description of uncertainties included further in the 3D modeling is made. This model is proposed to be used as a tool for prompt decision making when implementing a fast-track project with limited time between exploration and pre-FEED stages.
{"title":"Multivariate 3D Static and Dynamic Modeling Approach for an Oil Field at Early Stages of Exploration for a Fast-Track Project","authors":"V. Litvin, A. Potapov, M. Snachev","doi":"10.2118/196642-ms","DOIUrl":"https://doi.org/10.2118/196642-ms","url":null,"abstract":"\u0000 In this paper, the approach to multivariate static and dynamic modeling is considered on the example of an offshore field discovered in 2017. Based on the limited volume of information, the quantitative and qualitative description of uncertainties included further in the 3D modeling is made. This model is proposed to be used as a tool for prompt decision making when implementing a fast-track project with limited time between exploration and pre-FEED stages.","PeriodicalId":11098,"journal":{"name":"Day 2 Wed, September 18, 2019","volume":"49 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91494575","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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