This paper presents Computational Fluid Dynamics (CFD)-based simulations of the hydrodynamic behaviors of a floating barge in shallow waters on an inclined seabed near shore. The hull hydrodynamic behaviors with respect to water depth are quantified by evaluation of the hydrodynamic coefficients, i.e., added mass, viscous damping coefficients, and current drag coefficients, which are required for the prediction of hull motion responses and mooring loads of the barge. CFD simulations are performed to predict the hull hydrodynamic coefficients with consideration of the actual seabed conditions, including water depth and varying bathymetry. Added mass and viscous damping coefficients are calculated using forced harmonic oscillations, while current drag coefficient is obtained using steady current flow simulation. These hydrodynamic coefficients are calculated for three of the six degrees of freedom (DOFs), i.e., surge, sway, and yaw of the hull. By considering three different nearshore water depths with a flat seabed and two inclined seabeds, the hull added mass, viscous damping, and current drag coefficients are quantified and compared against the coefficients in deepwater conditions. The hydrodynamic coefficients are found to be significantly affected by shallow water depths. Overall trends show exponential increase of added mass and viscous damping coefficients as water depth reduces. There is a further linear increase in the coefficients when the seabed bathymetry changes from flat to inclined, particularly when the water depth to hull draft ratio is less than 4.50. Similarly, current drag coefficients increase with decreasing water depths for flat seabed conditions, while for inclined seabed conditions, they may increase or decrease depending on the directions with respect to the shore and the current heading. This paper demonstrates the efficiency of CFD simulations in predicting a floating barge’s hydrodynamic behaviors in shallow water conditions, including varying nearshore bathymetry and viscous effects. The CFD simulation methodologies presented may be extended for the hydrodynamic behavior assessments of other nearshore floating structures such as Floating Offshore Liquefied Gas Terminals (FLGTs), Floating Storage and Regasification Units (FSRUs), and floating wind turbine structures.
{"title":"CFD-Based Simulations of Hydrodynamic Behaviors of a Floating Barge Near Shore","authors":"Y. Teng, Jaime HuiChoo Tan","doi":"10.4043/31480-ms","DOIUrl":"https://doi.org/10.4043/31480-ms","url":null,"abstract":"\u0000 This paper presents Computational Fluid Dynamics (CFD)-based simulations of the hydrodynamic behaviors of a floating barge in shallow waters on an inclined seabed near shore. The hull hydrodynamic behaviors with respect to water depth are quantified by evaluation of the hydrodynamic coefficients, i.e., added mass, viscous damping coefficients, and current drag coefficients, which are required for the prediction of hull motion responses and mooring loads of the barge. CFD simulations are performed to predict the hull hydrodynamic coefficients with consideration of the actual seabed conditions, including water depth and varying bathymetry. Added mass and viscous damping coefficients are calculated using forced harmonic oscillations, while current drag coefficient is obtained using steady current flow simulation. These hydrodynamic coefficients are calculated for three of the six degrees of freedom (DOFs), i.e., surge, sway, and yaw of the hull.\u0000 By considering three different nearshore water depths with a flat seabed and two inclined seabeds, the hull added mass, viscous damping, and current drag coefficients are quantified and compared against the coefficients in deepwater conditions. The hydrodynamic coefficients are found to be significantly affected by shallow water depths. Overall trends show exponential increase of added mass and viscous damping coefficients as water depth reduces. There is a further linear increase in the coefficients when the seabed bathymetry changes from flat to inclined, particularly when the water depth to hull draft ratio is less than 4.50. Similarly, current drag coefficients increase with decreasing water depths for flat seabed conditions, while for inclined seabed conditions, they may increase or decrease depending on the directions with respect to the shore and the current heading.\u0000 This paper demonstrates the efficiency of CFD simulations in predicting a floating barge’s hydrodynamic behaviors in shallow water conditions, including varying nearshore bathymetry and viscous effects. The CFD simulation methodologies presented may be extended for the hydrodynamic behavior assessments of other nearshore floating structures such as Floating Offshore Liquefied Gas Terminals (FLGTs), Floating Storage and Regasification Units (FSRUs), and floating wind turbine structures.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76601361","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}
R. Adam, S. H. Ayub, H. N. Nguyen, R. Masoudi, T. S. Murugesu, Muhammad Hanif Haziq Mohammad, Fauzi Kadir, J. Margotta, Zuhar Zahir Tuan Harith, Alexander Kolupaev, Y. Zainudain, Dj Thomas
The objective of this paper is to demonstrate the success of an alternative numerical modeling approach to build a static model by incorporating Forward Stratigraphic Modelling (FSM) as geological input. This new methodology was performed on a field in the Malay Basin where early production wells indicated the high uncertainty in oil-originally-in-place, facies distribution and reservoir connectivity. For this reason, a new approach was developed for a static model in the area that provides new insights of subsurface reservoirs, de-risking future field assets and mitigates the subsurface uncertainty. Process-based simulations as presented with FSM present realistic scenarios of lithology distribution and vertical barriers that enable advanced subsurface characterization. FSM process built a quantitative method that simulate sediment distribution from regional to reservoir architecture for A field D and E sands. The main parameters for simulation run include regional understanding of sediment sources, in-situ organic sediment production, global sea-level curve enhanced by Milankovitch cycles and main long-term processes that control the subsidence of the area. FSM prediction combined with regional seismic, cores and well log data have provided a robust scenario of reservoir characteristics for static model. The results of the study detailed high-resolution sequence stratigraphy, significant changes in the depositional system and sand accumulation through time. The results of FSM were quality-checked with the A field well dataset for consistency. After performance of sensitivity analysis, the best-matched model was chosen for subsequent static model building process. In generating static depo- and rock type models, the FSM result were compared with the Geostatistical Stochastic Inversion (GSI) for property distribution away from the well control. The result of FSM guided model building showed A field D reservoirs as relatively having better sand quality with good lateral connectivity. A field E sand however is a more complex reservoir with limited areal and vertical connectivity. Overall, the total STOIIP for D reservoirs improved significantly while E reservoirs are comparable with existing model. The dynamic modelling was calibrated to field and wells performance (production history, MDT, DST, etc.) taking into account main remaining uncertainties and risks and evaluation of multiple field development options. With thorough integrated analysis of A field and its surroundings, integrated FSM and GSI derived static model reflects accurate facies distribution of the area compared with conventional workflows. It was used as an aid for Field A development optimization and increased the probability to find good reservoir facies as proven from findings of recently drilled development wells.
{"title":"Enhancement of a Complex Field's Reservoir Model Through Novel Application of Forward Stratigraphic Modeling","authors":"R. Adam, S. H. Ayub, H. N. Nguyen, R. Masoudi, T. S. Murugesu, Muhammad Hanif Haziq Mohammad, Fauzi Kadir, J. Margotta, Zuhar Zahir Tuan Harith, Alexander Kolupaev, Y. Zainudain, Dj Thomas","doi":"10.4043/31503-ms","DOIUrl":"https://doi.org/10.4043/31503-ms","url":null,"abstract":"\u0000 The objective of this paper is to demonstrate the success of an alternative numerical modeling approach to build a static model by incorporating Forward Stratigraphic Modelling (FSM) as geological input. This new methodology was performed on a field in the Malay Basin where early production wells indicated the high uncertainty in oil-originally-in-place, facies distribution and reservoir connectivity. For this reason, a new approach was developed for a static model in the area that provides new insights of subsurface reservoirs, de-risking future field assets and mitigates the subsurface uncertainty.\u0000 Process-based simulations as presented with FSM present realistic scenarios of lithology distribution and vertical barriers that enable advanced subsurface characterization. FSM process built a quantitative method that simulate sediment distribution from regional to reservoir architecture for A field D and E sands. The main parameters for simulation run include regional understanding of sediment sources, in-situ organic sediment production, global sea-level curve enhanced by Milankovitch cycles and main long-term processes that control the subsidence of the area.\u0000 FSM prediction combined with regional seismic, cores and well log data have provided a robust scenario of reservoir characteristics for static model. The results of the study detailed high-resolution sequence stratigraphy, significant changes in the depositional system and sand accumulation through time. The results of FSM were quality-checked with the A field well dataset for consistency. After performance of sensitivity analysis, the best-matched model was chosen for subsequent static model building process. In generating static depo- and rock type models, the FSM result were compared with the Geostatistical Stochastic Inversion (GSI) for property distribution away from the well control. The result of FSM guided model building showed A field D reservoirs as relatively having better sand quality with good lateral connectivity. A field E sand however is a more complex reservoir with limited areal and vertical connectivity. Overall, the total STOIIP for D reservoirs improved significantly while E reservoirs are comparable with existing model. The dynamic modelling was calibrated to field and wells performance (production history, MDT, DST, etc.) taking into account main remaining uncertainties and risks and evaluation of multiple field development options.\u0000 With thorough integrated analysis of A field and its surroundings, integrated FSM and GSI derived static model reflects accurate facies distribution of the area compared with conventional workflows. It was used as an aid for Field A development optimization and increased the probability to find good reservoir facies as proven from findings of recently drilled development wells.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75337066","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}
During the implementation of polymer flooding, high injection pressure and water cut return occur in the later stage. The early polymer flooding in offshore oilfields is more sensitive to the change of injection and production rate, so it is necessary to explore a new early polymer injection development mode suitable for offshore oilfields. By considering the impact factors of early polymer flooding development in offshore oilfields, such as large well spacing, thick oil layer, early polymer injection timing, limited platform life and space, the "pan type" development mode of polymer flooding water cut in offshore oilfields is established based on experimental research and numerical simulation and achieved the polymer flooding overall infill, polymer/surface binary flooding, unstable polymer flooding technology which has been applied in 3 oilfields in Bohai bay, providing support for the polymer flooding technology development in offshore oil fields in China.
{"title":"Research and Application of Comprehensive Adjustment Technology for Offshore Polymer Flooding Oilfield","authors":"Xiaodong Kang, Jian Zhang, Peng Li, Yang Zeng","doi":"10.4043/31510-ms","DOIUrl":"https://doi.org/10.4043/31510-ms","url":null,"abstract":"\u0000 During the implementation of polymer flooding, high injection pressure and water cut return occur in the later stage. The early polymer flooding in offshore oilfields is more sensitive to the change of injection and production rate, so it is necessary to explore a new early polymer injection development mode suitable for offshore oilfields. By considering the impact factors of early polymer flooding development in offshore oilfields, such as large well spacing, thick oil layer, early polymer injection timing, limited platform life and space, the \"pan type\" development mode of polymer flooding water cut in offshore oilfields is established based on experimental research and numerical simulation and achieved the polymer flooding overall infill, polymer/surface binary flooding, unstable polymer flooding technology which has been applied in 3 oilfields in Bohai bay, providing support for the polymer flooding technology development in offshore oil fields in China.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79574440","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}
M. F. Mostapa, Alex Tarang Patrick, H. N. Nguyen, A. P. Tata
Deepwater fields are well known for their complex turbidite heterogeneity. J field, which has a water depth of 1600-1800 meters, is a distal deepwater turbidite fan located within a high compressional area, resulted in highly faulted structures. All wells drilled in the J field penetrated thin-bedded sand-shale reservoirs (average 30-80 cm) which are below current available tools’ resolution. This has directly impacted the accuracy of reservoirs properties interpretation and characterization. Additionally, based on the acquired pressure data from past appraisal campaigns, the field is proven to be laterally and vertically compartmentalized. However, reservoir connectivity and producibility away from those appraisal wells remains uncertain and challenging to be identified, due to the legacy 3D seismic image quality, limitation in data resolutions, and limited regional data. This paper will briefly address the challenges of deepwater distal turbidites understanding while proposing a holistic workflow with the integration of 3D seismic and well data to enhance thin-bed interpretation and complex compartmentalization prediction.
{"title":"New Understanding of Ultra-Deepwater Thin Beds Interpretation and Compartmentalization in Light of New Seismic Reprocessed Data and Well Results","authors":"M. F. Mostapa, Alex Tarang Patrick, H. N. Nguyen, A. P. Tata","doi":"10.4043/31675-ms","DOIUrl":"https://doi.org/10.4043/31675-ms","url":null,"abstract":"\u0000 Deepwater fields are well known for their complex turbidite heterogeneity. J field, which has a water depth of 1600-1800 meters, is a distal deepwater turbidite fan located within a high compressional area, resulted in highly faulted structures. All wells drilled in the J field penetrated thin-bedded sand-shale reservoirs (average 30-80 cm) which are below current available tools’ resolution. This has directly impacted the accuracy of reservoirs properties interpretation and characterization.\u0000 Additionally, based on the acquired pressure data from past appraisal campaigns, the field is proven to be laterally and vertically compartmentalized. However, reservoir connectivity and producibility away from those appraisal wells remains uncertain and challenging to be identified, due to the legacy 3D seismic image quality, limitation in data resolutions, and limited regional data.\u0000 This paper will briefly address the challenges of deepwater distal turbidites understanding while proposing a holistic workflow with the integration of 3D seismic and well data to enhance thin-bed interpretation and complex compartmentalization prediction.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75851590","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}
Syarifah Puteh Mariah Syed Abd Rahim, M. F. Azman, Zaidi Awang@Mohamed, Mior Yusni Ahmad Fuad
It is widely known that for highly corrosive environment, corrosion-resistance alloy (CRA) is recommended as the production tubing material. This is because its alternative, carbon steel (CS) is prone to corrosion that leads to integrity issues such as tubing leak and tubing parted. However, CRA usage would increase well cost resulting in unattractive commercial implication especially for a marginal field development which tends to be very sensitive economically. This paper gathers the actual performance of various tubing materials that have been installed in a high CO2 oil field in Peninsular Malaysia, in which the findings would be used to determine a proper tubing material selection strategy for future development. Actual data from 30 years of production was collected and to be analyzed statistically. Each well's water cut trend was evaluated to establish relationship between producing water to the corrosion rate and metal loss in the presence of CO2. It is noted that some wells completed with CS both in single and dual completion are still producing with no leaks after 30 years. This case applies to either single string or dual string, with both strings are completed as producer. However, majority of active CS-completed wells require tubing pack off to overcome multiple leaks, especially in dual utility wells. Notably, wells that are completed with CRA e.g., 13 Cr are active with no possible leaks at all. Some wells which are completed with glass-reinforced epoxy (GRE) and higher grade of CRA; 22 & 25 Cr, also do not show any potential leaks or tubing integrity issue. It is proven and highly recommended to complete high CO2 fields with CRA material. Nevertheless, by understanding the well and reservoir performance, particularly on the effect of water cut in relation to general corrosion due to CO2, the use of more expensive materials can be optimized. This paper is to discuss, in the context of marginal field development where production life is relatively shorter and production rate is low, the consideration of deploying a cheaper material and/or less corrosion-resistant substances as the tubing material to make the development more commercially attractive or remain status quo with CRA.
{"title":"Impact of Various Tubing Material Performance Under High CO2 Environment on Future Marginal Field Development Strategy","authors":"Syarifah Puteh Mariah Syed Abd Rahim, M. F. Azman, Zaidi Awang@Mohamed, Mior Yusni Ahmad Fuad","doi":"10.4043/31564-ms","DOIUrl":"https://doi.org/10.4043/31564-ms","url":null,"abstract":"\u0000 It is widely known that for highly corrosive environment, corrosion-resistance alloy (CRA) is recommended as the production tubing material. This is because its alternative, carbon steel (CS) is prone to corrosion that leads to integrity issues such as tubing leak and tubing parted. However, CRA usage would increase well cost resulting in unattractive commercial implication especially for a marginal field development which tends to be very sensitive economically. This paper gathers the actual performance of various tubing materials that have been installed in a high CO2 oil field in Peninsular Malaysia, in which the findings would be used to determine a proper tubing material selection strategy for future development.\u0000 Actual data from 30 years of production was collected and to be analyzed statistically. Each well's water cut trend was evaluated to establish relationship between producing water to the corrosion rate and metal loss in the presence of CO2.\u0000 It is noted that some wells completed with CS both in single and dual completion are still producing with no leaks after 30 years. This case applies to either single string or dual string, with both strings are completed as producer. However, majority of active CS-completed wells require tubing pack off to overcome multiple leaks, especially in dual utility wells. Notably, wells that are completed with CRA e.g., 13 Cr are active with no possible leaks at all. Some wells which are completed with glass-reinforced epoxy (GRE) and higher grade of CRA; 22 & 25 Cr, also do not show any potential leaks or tubing integrity issue.\u0000 It is proven and highly recommended to complete high CO2 fields with CRA material. Nevertheless, by understanding the well and reservoir performance, particularly on the effect of water cut in relation to general corrosion due to CO2, the use of more expensive materials can be optimized. This paper is to discuss, in the context of marginal field development where production life is relatively shorter and production rate is low, the consideration of deploying a cheaper material and/or less corrosion-resistant substances as the tubing material to make the development more commercially attractive or remain status quo with CRA.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"46 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89570655","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}
With the increasing focus on data mining and machine learning (ML) applications in the oil and gas industry, the substantial number of well integrity logs and variety of data types represent a suitable candidate for the implementation of automated corrosion log processing. Convolutional neural networks (CNNs) are used in many fields, especially for image processing and features recognition. On the other hand, genetic algorithms (GA) add a valuable benefit to data processing in terms of global search and optimization. This paper demonstrates the integration of ML techniques with legacy well integrity log data, improving the results and leading to a tangible time and cost savings. A downhole well integrity evaluation triangle comprises three important services for comprehensive diagnosis: 1) cement evaluation, 2) corrosion inspection, and 3) leak detection. These services produce multiple datasets from a variety of logging tools. The types and sources of these datasets include synthetic data from simulation and modeling, tool calibration and lab testing, as well as raw, processed, and interpreted data. This paper describes the use of advanced ML techniques to scrutinize and improve well integrity evaluation. The new process resolves the recurrent challenges of well integrity evaluation in complex completion and downhole environments. It also maximizes value from existing well and field data. Image features recognition enables major improvements in the data analysis, such as the identification of concentric casings and tubing as well as their respective collar depths and types. In addition, input parameters and well schematics promote quality control of recorded data versus the model data. The new process helps to identify casing and completion accessories and provides a reliable benchmark. Another major element is the qualitative and quantitative evaluation of corrosion using deep learning algorithms combined with the GA. This evaluation is achieved using feature extraction from the forward model (FM) data in an analogous way to collar identification in an electromagnetic decay image. The integration of big data and advanced ML enables an improved data analysis with automated data quality control (QC) and interpretation. A more pro-active well integrity management system will result. Testing and validation using field examples demonstrate the benefits of this new methodology. The outcome is a better-quality answer product that helps depict various aspects of the acquired and interpreted data. Savings in time and cost are complemented with an improved and automated quality control.
{"title":"Automated Corrosion Log Quality Control and Interpretation Using Machine-Learning","authors":"Mohamed Larbi Zeghlache, M. Rourke, Xiaotian Liu","doi":"10.4043/31631-ms","DOIUrl":"https://doi.org/10.4043/31631-ms","url":null,"abstract":"\u0000 With the increasing focus on data mining and machine learning (ML) applications in the oil and gas industry, the substantial number of well integrity logs and variety of data types represent a suitable candidate for the implementation of automated corrosion log processing. Convolutional neural networks (CNNs) are used in many fields, especially for image processing and features recognition. On the other hand, genetic algorithms (GA) add a valuable benefit to data processing in terms of global search and optimization. This paper demonstrates the integration of ML techniques with legacy well integrity log data, improving the results and leading to a tangible time and cost savings.\u0000 A downhole well integrity evaluation triangle comprises three important services for comprehensive diagnosis: 1) cement evaluation, 2) corrosion inspection, and 3) leak detection. These services produce multiple datasets from a variety of logging tools. The types and sources of these datasets include synthetic data from simulation and modeling, tool calibration and lab testing, as well as raw, processed, and interpreted data. This paper describes the use of advanced ML techniques to scrutinize and improve well integrity evaluation. The new process resolves the recurrent challenges of well integrity evaluation in complex completion and downhole environments. It also maximizes value from existing well and field data.\u0000 Image features recognition enables major improvements in the data analysis, such as the identification of concentric casings and tubing as well as their respective collar depths and types. In addition, input parameters and well schematics promote quality control of recorded data versus the model data. The new process helps to identify casing and completion accessories and provides a reliable benchmark. Another major element is the qualitative and quantitative evaluation of corrosion using deep learning algorithms combined with the GA. This evaluation is achieved using feature extraction from the forward model (FM) data in an analogous way to collar identification in an electromagnetic decay image. The integration of big data and advanced ML enables an improved data analysis with automated data quality control (QC) and interpretation. A more pro-active well integrity management system will result.\u0000 Testing and validation using field examples demonstrate the benefits of this new methodology. The outcome is a better-quality answer product that helps depict various aspects of the acquired and interpreted data. Savings in time and cost are complemented with an improved and automated quality control.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89982373","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}
For offshore unmanned platforms, reliable and continuous power is critical in the remote wellhead platform operation of the oil and gas company. Thermoelectric generators (TEG) and solar panels are being examined as sources of power to meet the energy needs. Because of high expenses of TEG installation and upkeep, a study was initiated to explore the renewable energy source with better reliability while minimizing costs. A combination of solar and wind turbine system was fully met these requirements. TEG was replaced by a wind turbine during the experimental phase. The wind turbine can be easily connected to an existing system, making it incredibly versatile and cost-effective for upgrading to a hybrid wind and solar system. The wind speed profile was used to figure out how big a wind turbine and battery should be. The study suggested that by combining solar and wind power, the cost of consistent power generation can be reduced. There is a huge potential for capital cost savings when compared to TEG. As a result, a Hybrid Wind and Solar Energy Supply System could be a viable option for remote power supply for offshore platforms, lowering capital, operating, and maintenance costs while also environmental friendly.
{"title":"A Hybrid Wind and Solar Energy Supply System for Offshore Platform in Gulf of Thailand","authors":"S. Tangpuk, Warawath Thubthimsang","doi":"10.4043/31539-ms","DOIUrl":"https://doi.org/10.4043/31539-ms","url":null,"abstract":"For offshore unmanned platforms, reliable and continuous power is critical in the remote wellhead platform operation of the oil and gas company. Thermoelectric generators (TEG) and solar panels are being examined as sources of power to meet the energy needs. Because of high expenses of TEG installation and upkeep, a study was initiated to explore the renewable energy source with better reliability while minimizing costs. A combination of solar and wind turbine system was fully met these requirements.\u0000 TEG was replaced by a wind turbine during the experimental phase. The wind turbine can be easily connected to an existing system, making it incredibly versatile and cost-effective for upgrading to a hybrid wind and solar system.\u0000 The wind speed profile was used to figure out how big a wind turbine and battery should be. The study suggested that by combining solar and wind power, the cost of consistent power generation can be reduced. There is a huge potential for capital cost savings when compared to TEG.\u0000 As a result, a Hybrid Wind and Solar Energy Supply System could be a viable option for remote power supply for offshore platforms, lowering capital, operating, and maintenance costs while also environmental friendly.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86499368","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}
Yifan He, Ying-xian Liu, H. Cai, Xiaoming Chen, Jing Chen
For water-flooding oilfields, both indoor experiments and mine field practices have confirmed that long-term water flooding can change physical properties, wettability, and fluid parameters. The comprehensive performance of these changes is that the relative permeability curve of oil and water changes dynamically. Usually, numerical simulation does not consider the change of reservoir properties, which will cause the mismatch of history matching. This error is especially obvious in the high water-cut period. It further affected the understanding of remaining oil and the prediction of subsequent production. Therefore, time-varying numerical simulation is required for fine numerical simulation in high water cut period to improve the accuracy and reliability of model prediction. In order to solve the above problems, a set of fine reservoir numerical simulation process integrating core experiment, logging, dynamic and geological knowledge was established. The specific workflow is as follows: The data of core particle size analysis, X-ray diffraction and cast thin section were used to study the change law of reservoir physical properties and wettability after water flooding, which confirmed that the reservoir was re-stimulated under long-term water flooding. The relative permeability curves before and after water flooding were compared using natural cores. After water flooding, the relative permeability curves shifted to the right and the residual oil saturation decreased. It is confirmed that the relative permeability curves will change with water flooding. Carried out 500∼2000PV water flooding laboratory experiment, determined the oil displacement efficiency under high multiple flooding, calculated the residual oil saturation changes with the displacement multiple and physical properties. Using pore cross-sectional area flux to continuously characterize the temporal changes of properties during the simulation process. In this way, the accurate conversion of the attribute change law from the laboratory core to the actual model is realized, and the deviation caused by the change of the mesh size is avoided. In the simulation process, the changing laws of the attributes are defined separately according to the partitions, and the iterative modification of the attributes is realized in each time step. When time-varying numerical simulation is applied to the QHD oilfield, the matching degree of history matching has been improved. Time-varying simulation is an important means to improve the history matching effect of high water-cut water drive oilfields, and can help oilfields understand the true remaining oil distribution. This method has been extended to Bohai SZ, BZ and other oil fields.
{"title":"Fine Characterisation of Remaining Oil Using Time-Varying Numerical Simulation: Experimental Study, Characterisation in Model, and Application in QHD Oilfield","authors":"Yifan He, Ying-xian Liu, H. Cai, Xiaoming Chen, Jing Chen","doi":"10.4043/31410-ms","DOIUrl":"https://doi.org/10.4043/31410-ms","url":null,"abstract":"\u0000 For water-flooding oilfields, both indoor experiments and mine field practices have confirmed that long-term water flooding can change physical properties, wettability, and fluid parameters. The comprehensive performance of these changes is that the relative permeability curve of oil and water changes dynamically. Usually, numerical simulation does not consider the change of reservoir properties, which will cause the mismatch of history matching. This error is especially obvious in the high water-cut period. It further affected the understanding of remaining oil and the prediction of subsequent production. Therefore, time-varying numerical simulation is required for fine numerical simulation in high water cut period to improve the accuracy and reliability of model prediction.\u0000 In order to solve the above problems, a set of fine reservoir numerical simulation process integrating core experiment, logging, dynamic and geological knowledge was established. The specific workflow is as follows:\u0000 The data of core particle size analysis, X-ray diffraction and cast thin section were used to study the change law of reservoir physical properties and wettability after water flooding, which confirmed that the reservoir was re-stimulated under long-term water flooding. The relative permeability curves before and after water flooding were compared using natural cores. After water flooding, the relative permeability curves shifted to the right and the residual oil saturation decreased. It is confirmed that the relative permeability curves will change with water flooding. Carried out 500∼2000PV water flooding laboratory experiment, determined the oil displacement efficiency under high multiple flooding, calculated the residual oil saturation changes with the displacement multiple and physical properties. Using pore cross-sectional area flux to continuously characterize the temporal changes of properties during the simulation process. In this way, the accurate conversion of the attribute change law from the laboratory core to the actual model is realized, and the deviation caused by the change of the mesh size is avoided. In the simulation process, the changing laws of the attributes are defined separately according to the partitions, and the iterative modification of the attributes is realized in each time step.\u0000 When time-varying numerical simulation is applied to the QHD oilfield, the matching degree of history matching has been improved.\u0000 Time-varying simulation is an important means to improve the history matching effect of high water-cut water drive oilfields, and can help oilfields understand the true remaining oil distribution. This method has been extended to Bohai SZ, BZ and other oil fields.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86605380","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}
As offshore wind farm developments move into water depth above 60m, one of the greatest challenges is in designing cost-effective mooring systems capable of overcoming the added risks of more severe environments, complicated floating structure response, and turbine forces. The failure of a primary mooring component could lead to unacceptable consequences, including destruction or complete loss of assets, loss of continuous electricity generation, possible retrieval of destructed structure, and possible injury or loss of human life during maintenance. It is essential to ensure that mooring systems operate without failure. Operators have recognized the importance of installing instrumentation such as GPS to monitor floating wind structure location. However, motion monitoring instruments have seldom been deployed on mooring lines of floating wind farm structures to capture dynamic response, which will govern the integrity of the mooring system and subsequently the whole floating wind structure. Measured data from these instruments on mooring lines allow an operator to determine when the limits of acceptable response, predicted by design analysis or scale model tests, could be exceeded in terms of strength and fatigue. This paper describes the role of mooring line monitoring in an effective asset integrity management of floating wind farm and provide a typical procedure for the development of a fit-for-purpose mooring line monitoring program. Furthermore, this paper presents an advanced monitoring method to capture the dynamic response of the mooring line by a cost-effective and maintainable solution.
{"title":"The Role of Mooring Line Monitoring in an Effective Asset Integrity Management of Floating Wind Farm","authors":"Y. Sha, Wei Feng, Hui Zhang, F. Lim, S. Natarajan","doi":"10.4043/31473-ms","DOIUrl":"https://doi.org/10.4043/31473-ms","url":null,"abstract":"\u0000 As offshore wind farm developments move into water depth above 60m, one of the greatest challenges is in designing cost-effective mooring systems capable of overcoming the added risks of more severe environments, complicated floating structure response, and turbine forces. The failure of a primary mooring component could lead to unacceptable consequences, including destruction or complete loss of assets, loss of continuous electricity generation, possible retrieval of destructed structure, and possible injury or loss of human life during maintenance. It is essential to ensure that mooring systems operate without failure.\u0000 Operators have recognized the importance of installing instrumentation such as GPS to monitor floating wind structure location. However, motion monitoring instruments have seldom been deployed on mooring lines of floating wind farm structures to capture dynamic response, which will govern the integrity of the mooring system and subsequently the whole floating wind structure. Measured data from these instruments on mooring lines allow an operator to determine when the limits of acceptable response, predicted by design analysis or scale model tests, could be exceeded in terms of strength and fatigue.\u0000 This paper describes the role of mooring line monitoring in an effective asset integrity management of floating wind farm and provide a typical procedure for the development of a fit-for-purpose mooring line monitoring program. Furthermore, this paper presents an advanced monitoring method to capture the dynamic response of the mooring line by a cost-effective and maintainable solution.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88487598","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}
Lipeng He, Yongming Gao, B. Chang, Chao Wang, Yongjiang Zhang, Zhongtiang Hu, Fei Wang, Y. Shim
After more than 10-years of abandonment, deepwater oilfield M was redeveloped by using four horizontal wells with 800 to 1700 m long sections. The target was the thick, porous sandstone reservoir N with the strong bottomwater drive, which had been intensively produced for 12 years with the horizontal wells placed at the middle part of the original oil column (15 to 42 m height). The local interbeds with poor properties within the reservoir were proved insufficient to block the water breakthrough. Consequently, the new horizontal sections were planned at the upper section of the clean reservoir with more than 10-m standoff to the uncertain oil/water contact (OWC) and enough distance to offset drilled boreholes. However, uncertainties from the reservoir properties, fluid characterization, and structural dip greatly complicated the effective oil trap profile and the further important well placement strategy. Global successful cases and modeling results pushed the decision team to use an ultradeep reservoir mapping service (UDRMS) to cost-effectively optimize this redevelopment efficiency. With the depth-of-investigation (DOI) up to 30 m from the borehole, UDRMS could use the resistivity inversion to remotely and certainly detect multiple boundaries and map the properties details of this specific thick reservoir, including the reservoir top, local interbeds’ boundaries, OWC, and the intricate layering of contrasting resistivity within the reservoir. These certain and quantitative details could combine the conventional petrophysical logging data to effectively manage related uncertainties and then strategically instruct the productive drilling in the horizontal section for the expected well performance. The successful redevelopment results validated the effective contributions from the UDRMS certain products. Along the long sections up to 1685 m, all uncertain elements were accurately ascertained. Within a corridor of approximately 100 m centered on the wellbore, up to five boundaries were mapped vertically to reveal the certain details of properties, reservoir top, and OWC. The dynamic OWC was identified as still tilted even after a long-term production shutdown and the remaining oil columns were higher than 12 m. Within the actual downdip structural framework, the smooth horizontal trajectories were placed in the upper reservoir with the quantitative distance to reservoir top and tilted OWC, while avoiding the local zones with poor properties. Even at the structural low, the special strategy was executed to guarantee the minimum 10 m standoff above OWC. The well placement efficiency satisfied the redevelopment requirements to positively affect the well performance. As a game-changing enabler, UDRMS-derived certain products displayed their advantages for cost-effectively managing the uncertainties affecting the development of the thick reservoirs with the diverse complexities.
{"title":"Certainty Based on Ultradeep Reservoir Mapping Service to Cost-Effectively Manage the Uncertainties Affecting the Redevelopment of the Deepwater Oil Reservoir","authors":"Lipeng He, Yongming Gao, B. Chang, Chao Wang, Yongjiang Zhang, Zhongtiang Hu, Fei Wang, Y. Shim","doi":"10.4043/31676-ms","DOIUrl":"https://doi.org/10.4043/31676-ms","url":null,"abstract":"\u0000 After more than 10-years of abandonment, deepwater oilfield M was redeveloped by using four horizontal wells with 800 to 1700 m long sections. The target was the thick, porous sandstone reservoir N with the strong bottomwater drive, which had been intensively produced for 12 years with the horizontal wells placed at the middle part of the original oil column (15 to 42 m height). The local interbeds with poor properties within the reservoir were proved insufficient to block the water breakthrough. Consequently, the new horizontal sections were planned at the upper section of the clean reservoir with more than 10-m standoff to the uncertain oil/water contact (OWC) and enough distance to offset drilled boreholes. However, uncertainties from the reservoir properties, fluid characterization, and structural dip greatly complicated the effective oil trap profile and the further important well placement strategy.\u0000 Global successful cases and modeling results pushed the decision team to use an ultradeep reservoir mapping service (UDRMS) to cost-effectively optimize this redevelopment efficiency. With the depth-of-investigation (DOI) up to 30 m from the borehole, UDRMS could use the resistivity inversion to remotely and certainly detect multiple boundaries and map the properties details of this specific thick reservoir, including the reservoir top, local interbeds’ boundaries, OWC, and the intricate layering of contrasting resistivity within the reservoir. These certain and quantitative details could combine the conventional petrophysical logging data to effectively manage related uncertainties and then strategically instruct the productive drilling in the horizontal section for the expected well performance.\u0000 The successful redevelopment results validated the effective contributions from the UDRMS certain products. Along the long sections up to 1685 m, all uncertain elements were accurately ascertained. Within a corridor of approximately 100 m centered on the wellbore, up to five boundaries were mapped vertically to reveal the certain details of properties, reservoir top, and OWC. The dynamic OWC was identified as still tilted even after a long-term production shutdown and the remaining oil columns were higher than 12 m. Within the actual downdip structural framework, the smooth horizontal trajectories were placed in the upper reservoir with the quantitative distance to reservoir top and tilted OWC, while avoiding the local zones with poor properties. Even at the structural low, the special strategy was executed to guarantee the minimum 10 m standoff above OWC. The well placement efficiency satisfied the redevelopment requirements to positively affect the well performance.\u0000 As a game-changing enabler, UDRMS-derived certain products displayed their advantages for cost-effectively managing the uncertainties affecting the development of the thick reservoirs with the diverse complexities.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"2020 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77143592","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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