Bjoern-Tore Anfinsen, I. Mosti, Waldemar Szemat-Vielma
The use of automated workflows for engineering calculations is significantly improving the efficiency of modern well planning systems. Current automated well control solutions are at large limited to single bubble considerations. Transient, multiphase technology has proven to be more accurate and reliable for well control planning, but it has been too complex to automate and integrate into automated engineering systems. The objective of this work is to improve well control planning efficiency by using an automated workflow that enables integration of transient multiphase technology into modern well-planning systems. The workflow is based around an advanced multiphase engine that covers all relevant physical processes in the wellbore including transient temperature and acceleration. The model has an accurate equations-of-state- (EOS) based pressure-volume-temperature (PVT) model with compositional tracking that, in combination with the transient temperature, can accurately predict the transition from dissolved to free gas - a key parameter in the development of a kick. The workflow is based on Driller's method and has been automated with a controller network that moves the simulation through the distinct phases of the driller's first circulation without any interaction from the user. High-performance cloud computing ensures the workflow performance. The drilling industry has focused on risk reductions after the Deepwater Horizon (BSSE 2010) accident. But the well-control risk is still high. In Norway, the reported incidents indicate a flat or increasing trend. Geological uncertainties and inaccurate mud density (static and circulating) have been identified as root causes for the majority of the reported incidents. Transient multiphase models are reducing well-control risk by accurately modeling downhole variations in fluid pressure as a function of operational mode, fluids, influx type, geometry, water depth, and pressure and temperature conditions. Such models have been regarded as expert tools because of the complexity and numerically demanding simulations. The automated workflow enables a well control engineer to run accurate multiphase simulations with the same user effort as single bubble kick tolerance tools. In special cases where more sensitivities are required, it is easy to transfer the project to the expert mode - where the automated simulation can be finetuned.
{"title":"Automated Workflow Based on Transient, Multiphase Technology Improves Well Control Planning Efficiency and Reduces Risk","authors":"Bjoern-Tore Anfinsen, I. Mosti, Waldemar Szemat-Vielma","doi":"10.2118/207726-ms","DOIUrl":"https://doi.org/10.2118/207726-ms","url":null,"abstract":"\u0000 The use of automated workflows for engineering calculations is significantly improving the efficiency of modern well planning systems. Current automated well control solutions are at large limited to single bubble considerations. Transient, multiphase technology has proven to be more accurate and reliable for well control planning, but it has been too complex to automate and integrate into automated engineering systems.\u0000 The objective of this work is to improve well control planning efficiency by using an automated workflow that enables integration of transient multiphase technology into modern well-planning systems. The workflow is based around an advanced multiphase engine that covers all relevant physical processes in the wellbore including transient temperature and acceleration. The model has an accurate equations-of-state- (EOS) based pressure-volume-temperature (PVT) model with compositional tracking that, in combination with the transient temperature, can accurately predict the transition from dissolved to free gas - a key parameter in the development of a kick.\u0000 The workflow is based on Driller's method and has been automated with a controller network that moves the simulation through the distinct phases of the driller's first circulation without any interaction from the user. High-performance cloud computing ensures the workflow performance.\u0000 The drilling industry has focused on risk reductions after the Deepwater Horizon (BSSE 2010) accident. But the well-control risk is still high. In Norway, the reported incidents indicate a flat or increasing trend. Geological uncertainties and inaccurate mud density (static and circulating) have been identified as root causes for the majority of the reported incidents.\u0000 Transient multiphase models are reducing well-control risk by accurately modeling downhole variations in fluid pressure as a function of operational mode, fluids, influx type, geometry, water depth, and pressure and temperature conditions. Such models have been regarded as expert tools because of the complexity and numerically demanding simulations.\u0000 The automated workflow enables a well control engineer to run accurate multiphase simulations with the same user effort as single bubble kick tolerance tools. In special cases where more sensitivities are required, it is easy to transfer the project to the expert mode - where the automated simulation can be finetuned.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"28 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78144799","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}
The current combination of increasingly complex wellbores and tightening budgets forces operators to do more with less and find new ways to expand the drilling envelop. Often this pushes the parameters to the limit in order to achieve faster penetration rates. Operating at the limit or beyond impacts equipment reliability and project cost. A thorough failure analysis of the root cause(s) of every incident can help identify and address areas that need improvement. Identifying a cause fosters improvement while it simultaneously pushes the boundaries so the profitability of mature assets can be maximized. Typical failure analysis attempts to determine the cause of a failure and establish corrective actions to prevent reoccurrence. In a large extended reach drilling project targeting a mature field, the approach to a single failure was expanded and projected in a proactive manner to anticipate the impact of current failure modes in future more challenging scenarios. This innovative method combines the classic failure analysis approach with a comparative approach designed to identify and classify each factor that contributed to the failure. This information is then compiled into a dynamic predictive risk matrix to improve the planning. This method, thanks to the contextualization of individual failures and the multi-facet comparative analysis, revealed a pattern between reliability trends and environmental challenges. The pattern was correlated with the increased drilling difficulty over the lifetime of the project, and suggested that the long-established practices had to be revised to overcome the new scenario. The analysis contributed to the delineation of a strong action plan that immediately revealed a consistent service quality improvement quarter on quarter and nearly a 50% decrease in failure rate. The enhanced reliability had a direct impact on the performance that registered a significant reduction of the drilling time, thus lowering the overall well construction cost. In today's economics where cost reduction, resource optimization and sustainability are at the top of the operator's priority list, failure analysis has become paramount to ensure continuous improvement. Effective analytic methods to identify and eliminate showstoppers are needed to minimize unplanned events and deliver within budget. By digging deep into the root cause of incidents, this new approach to failure analysis enabled an enhanced, broader and more effective quality improvement plan that tackled service quality from multiple angles. From refining bottomhole assembly (BHA) design and risk matrix to drafting field guidelines and roadmaps, this approach also provided extra guidance and risk awareness for future well planning improvement. This particularly applies to mature fields where wellbore complexity increases at the same time budgets decrease and it's necessary to improve operational excellence to assure profitability.
{"title":"Contextual Failure Analysis Improves Reliability While Pushing the Envelope of Extended Reach Wells in a Giant Brown Field, UAE","authors":"E. Cantarelli, Khoa Le Pham Dang, H. Escalera","doi":"10.2118/208216-ms","DOIUrl":"https://doi.org/10.2118/208216-ms","url":null,"abstract":"\u0000 The current combination of increasingly complex wellbores and tightening budgets forces operators to do more with less and find new ways to expand the drilling envelop. Often this pushes the parameters to the limit in order to achieve faster penetration rates. Operating at the limit or beyond impacts equipment reliability and project cost. A thorough failure analysis of the root cause(s) of every incident can help identify and address areas that need improvement. Identifying a cause fosters improvement while it simultaneously pushes the boundaries so the profitability of mature assets can be maximized.\u0000 Typical failure analysis attempts to determine the cause of a failure and establish corrective actions to prevent reoccurrence. In a large extended reach drilling project targeting a mature field, the approach to a single failure was expanded and projected in a proactive manner to anticipate the impact of current failure modes in future more challenging scenarios. This innovative method combines the classic failure analysis approach with a comparative approach designed to identify and classify each factor that contributed to the failure. This information is then compiled into a dynamic predictive risk matrix to improve the planning.\u0000 This method, thanks to the contextualization of individual failures and the multi-facet comparative analysis, revealed a pattern between reliability trends and environmental challenges. The pattern was correlated with the increased drilling difficulty over the lifetime of the project, and suggested that the long-established practices had to be revised to overcome the new scenario. The analysis contributed to the delineation of a strong action plan that immediately revealed a consistent service quality improvement quarter on quarter and nearly a 50% decrease in failure rate. The enhanced reliability had a direct impact on the performance that registered a significant reduction of the drilling time, thus lowering the overall well construction cost.\u0000 In today's economics where cost reduction, resource optimization and sustainability are at the top of the operator's priority list, failure analysis has become paramount to ensure continuous improvement. Effective analytic methods to identify and eliminate showstoppers are needed to minimize unplanned events and deliver within budget.\u0000 By digging deep into the root cause of incidents, this new approach to failure analysis enabled an enhanced, broader and more effective quality improvement plan that tackled service quality from multiple angles. From refining bottomhole assembly (BHA) design and risk matrix to drafting field guidelines and roadmaps, this approach also provided extra guidance and risk awareness for future well planning improvement. This particularly applies to mature fields where wellbore complexity increases at the same time budgets decrease and it's necessary to improve operational excellence to assure profitability.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77250825","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}
Z. Alyousef, Ali Altaq, M. Almajid, Lyla Almaskeen
Foams are used in many oil and gas applications including conformance control during EOR processes, fracturing, and acidizing operations. Foams are defined as dispersions of gas bubbles into a continuous liquid phase. Typically, foams are generated when an injection gas such as nitrogen, carbon dioxide, or flue gas is mixed with an injection fluid containing a foaming agent. This method, however, requires a gas source to be present for foams to be generated. The objective of this study is to evaluate a new alternative technique for foam generation using two salt solutions. Nitrogen gas is generated as a result of the reaction of the two salt solutions at specific conditions. This generated nitrogen gas is then used for foam generation in porous media. The foam generated using the two salt solutions is tested in a microfluidic device (rock-on-a-chip) to study the gas mobility reduction in porous media. A Foam rheometer apparatus is also used to measure foam apparent viscosity when the two salt solutions are mixed with a foaming agent. The results are compared with those obtained when nitrogen gas is injected into the system independently in the absence of the two salt solutions. Results reveal that the amount of added salts significantly impact the produced nitrogen volume. Additionally, the test conditions especially the temperature, significantly impacts the reaction rate. The rate of nitrogen gas generation is directly proportional to the temperature when tested at 25-80°C. In addition, experiments demonstrate that the foams generated using the two salt solutions reaction have almost identical characteristics as those produced when nitrogen gas is injected into the foam rheometer apparatus independently. Both methods generate the same foams with comparable foam apparent viscosity. In the microfluidic system, the foam obtained using the two salt solutions in the presence of a foaming agent shows excellent resistance to gas flow and subsequently exhibit large gas mobility reduction. This experimental study, for the first time, confirms the ability of the two salt solutions reaction to generate nitrogen gas spontaneously upon contact under certain conditions. The generated gas is used to generate foams in the presence of a foaming agent. This newly proposed technique of foam generation could significantly impact many oil and gas operations including conformance control during EOR processes, fracturing, and acid stimulation operations.
{"title":"Evaluation of In-Situ Generation of Nitrogen Gas for Foam Applications using Two Salt Solutions","authors":"Z. Alyousef, Ali Altaq, M. Almajid, Lyla Almaskeen","doi":"10.2118/207605-ms","DOIUrl":"https://doi.org/10.2118/207605-ms","url":null,"abstract":"\u0000 Foams are used in many oil and gas applications including conformance control during EOR processes, fracturing, and acidizing operations. Foams are defined as dispersions of gas bubbles into a continuous liquid phase. Typically, foams are generated when an injection gas such as nitrogen, carbon dioxide, or flue gas is mixed with an injection fluid containing a foaming agent. This method, however, requires a gas source to be present for foams to be generated. The objective of this study is to evaluate a new alternative technique for foam generation using two salt solutions. Nitrogen gas is generated as a result of the reaction of the two salt solutions at specific conditions. This generated nitrogen gas is then used for foam generation in porous media.\u0000 The foam generated using the two salt solutions is tested in a microfluidic device (rock-on-a-chip) to study the gas mobility reduction in porous media. A Foam rheometer apparatus is also used to measure foam apparent viscosity when the two salt solutions are mixed with a foaming agent. The results are compared with those obtained when nitrogen gas is injected into the system independently in the absence of the two salt solutions.\u0000 Results reveal that the amount of added salts significantly impact the produced nitrogen volume. Additionally, the test conditions especially the temperature, significantly impacts the reaction rate. The rate of nitrogen gas generation is directly proportional to the temperature when tested at 25-80°C. In addition, experiments demonstrate that the foams generated using the two salt solutions reaction have almost identical characteristics as those produced when nitrogen gas is injected into the foam rheometer apparatus independently. Both methods generate the same foams with comparable foam apparent viscosity. In the microfluidic system, the foam obtained using the two salt solutions in the presence of a foaming agent shows excellent resistance to gas flow and subsequently exhibit large gas mobility reduction.\u0000 This experimental study, for the first time, confirms the ability of the two salt solutions reaction to generate nitrogen gas spontaneously upon contact under certain conditions. The generated gas is used to generate foams in the presence of a foaming agent. This newly proposed technique of foam generation could significantly impact many oil and gas operations including conformance control during EOR processes, fracturing, and acid stimulation operations.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73782706","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}
H. Di, C. Kloucha, Cen Li, A. Abubakar, Zhun Li, Houcine Ben Jeddou, H. Mustapha
Delineating seismic stratigraphic features and depositional facies is of importance to successful reservoir mapping and identification in the subsurface. Robust seismic stratigraphy interpretation is confronted with two major challenges. The first one is to maximally automate the process particularly with the increasing size of seismic data and complexity of target stratigraphies, while the second challenge is to efficiently incorporate available structures into stratigraphy model building. Machine learning, particularly convolutional neural network (CNN), has been introduced into assisting seismic stratigraphy interpretation through supervised learning. However, the small amount of available expert labels greatly restricts the performance of such supervised CNN. Moreover, most of the exiting CNN implementations are based on only amplitude, which fails to use necessary structural information such as faults for constraining the machine learning. To resolve both challenges, this paper presents a semi-supervised learning workflow for fault-guided seismic stratigraphy interpretation, which consists of two components. The first component is seismic feature engineering (SFE), which aims at learning the provided seismic and fault data through a unsupervised convolutional autoencoder (CAE), while the second one is stratigraphy model building (SMB), which aims at building an optimal mapping function between the features extracted from the SFE CAE and the target stratigraphic labels provided by an experienced interpreter through a supervised CNN. Both components are connected by embedding the encoder of the SFE CAE into the SMB CNN, which forces the SMB learning based on these features commonly existing in the entire study area instead of those only at the limited training data; correspondingly, the risk of overfitting is greatly eliminated. More innovatively, the fault constraint is introduced by customizing the SMB CNN of two output branches, with one to match the target stratigraphies and the other to reconstruct the input fault, so that the fault continues contributing to the process of SMB learning. The performance of such fault-guided seismic stratigraphy interpretation is validated by an application to a real seismic dataset, and the machine prediction not only matches the manual interpretation accurately but also clearly illustrates the depositional process in the study area.
{"title":"Fault-Guided Seismic Stratigraphy Interpretation via Semi-Supervised Learning","authors":"H. Di, C. Kloucha, Cen Li, A. Abubakar, Zhun Li, Houcine Ben Jeddou, H. Mustapha","doi":"10.2118/207218-ms","DOIUrl":"https://doi.org/10.2118/207218-ms","url":null,"abstract":"\u0000 Delineating seismic stratigraphic features and depositional facies is of importance to successful reservoir mapping and identification in the subsurface. Robust seismic stratigraphy interpretation is confronted with two major challenges. The first one is to maximally automate the process particularly with the increasing size of seismic data and complexity of target stratigraphies, while the second challenge is to efficiently incorporate available structures into stratigraphy model building. Machine learning, particularly convolutional neural network (CNN), has been introduced into assisting seismic stratigraphy interpretation through supervised learning. However, the small amount of available expert labels greatly restricts the performance of such supervised CNN. Moreover, most of the exiting CNN implementations are based on only amplitude, which fails to use necessary structural information such as faults for constraining the machine learning.\u0000 To resolve both challenges, this paper presents a semi-supervised learning workflow for fault-guided seismic stratigraphy interpretation, which consists of two components. The first component is seismic feature engineering (SFE), which aims at learning the provided seismic and fault data through a unsupervised convolutional autoencoder (CAE), while the second one is stratigraphy model building (SMB), which aims at building an optimal mapping function between the features extracted from the SFE CAE and the target stratigraphic labels provided by an experienced interpreter through a supervised CNN. Both components are connected by embedding the encoder of the SFE CAE into the SMB CNN, which forces the SMB learning based on these features commonly existing in the entire study area instead of those only at the limited training data; correspondingly, the risk of overfitting is greatly eliminated. More innovatively, the fault constraint is introduced by customizing the SMB CNN of two output branches, with one to match the target stratigraphies and the other to reconstruct the input fault, so that the fault continues contributing to the process of SMB learning. The performance of such fault-guided seismic stratigraphy interpretation is validated by an application to a real seismic dataset, and the machine prediction not only matches the manual interpretation accurately but also clearly illustrates the depositional process in the study area.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81743889","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}
Latifa Obaid Alnuaimi, M. Sohrabi, S. Aghabozorgi, Ahmed Alshmakhy
Simulation of Water-Alternating-Gas (WAG) Experiments require precise estimation of hysteresis phenomenon in three-phase relative permeability. Most of the research available in the literature are focused on experiments performed on sandstone rocks and the study of carbonate rocks has attracted less attention. In this paper, a recently published hysteresis model by Heriot-Watt University (HWU) was used for simulation of WAG experiments conducted on mixed-wet homogenous carbonate rock. In this study, we simulated immiscible WAG experiments, which were performed under reservoir conditions on mixed-wet carbonate reservoir rock extracted from Abu Dhabi field by using real reservoir fluids. Experiments are performed with different injection scenarios and at high IFT conditions. Then, the results of the coreflood experiments were history matched using 3RPSim to generate two-phase and three-phase relative permeability data. Finally, the hysteresis model suggested by Heriot-Watt University was used for the estimation of hysteresis in relative permeability data. The performance of the model was compared with the experimental data from sandstones to evaluate the impact of heterogeneity on hysteresis phenomenon. It was shown that the available correlations for estimation of three-phase oil relative permeability fail to simulate the oil production during WAG experiments, while the modified Stone model suggested by HWU provided a better prediction. Overall, HWU hysteresis model improved the match for trapped gas saturation and pressure drop. The results show that the hysteresis effect is less dominant in the carbonate rock compared to the sandstone rock. The tracer test results show that the carbonate rock is more homogenous compared to sandstone rock. Therefore, the conclusion is that the hysteresis effect is negligible in homogenous systems.
{"title":"Simulation of Immiscible WAG Experiments Performed in Carbonate Rocks: The Impact of Heterogeneity on Hysteresis Phenomenon","authors":"Latifa Obaid Alnuaimi, M. Sohrabi, S. Aghabozorgi, Ahmed Alshmakhy","doi":"10.2118/207503-ms","DOIUrl":"https://doi.org/10.2118/207503-ms","url":null,"abstract":"\u0000 Simulation of Water-Alternating-Gas (WAG) Experiments require precise estimation of hysteresis phenomenon in three-phase relative permeability. Most of the research available in the literature are focused on experiments performed on sandstone rocks and the study of carbonate rocks has attracted less attention. In this paper, a recently published hysteresis model by Heriot-Watt University (HWU) was used for simulation of WAG experiments conducted on mixed-wet homogenous carbonate rock.\u0000 In this study, we simulated immiscible WAG experiments, which were performed under reservoir conditions on mixed-wet carbonate reservoir rock extracted from Abu Dhabi field by using real reservoir fluids. Experiments are performed with different injection scenarios and at high IFT conditions. Then, the results of the coreflood experiments were history matched using 3RPSim to generate two-phase and three-phase relative permeability data. Finally, the hysteresis model suggested by Heriot-Watt University was used for the estimation of hysteresis in relative permeability data. The performance of the model was compared with the experimental data from sandstones to evaluate the impact of heterogeneity on hysteresis phenomenon.\u0000 It was shown that the available correlations for estimation of three-phase oil relative permeability fail to simulate the oil production during WAG experiments, while the modified Stone model suggested by HWU provided a better prediction. Overall, HWU hysteresis model improved the match for trapped gas saturation and pressure drop. The results show that the hysteresis effect is less dominant in the carbonate rock compared to the sandstone rock. The tracer test results show that the carbonate rock is more homogenous compared to sandstone rock. Therefore, the conclusion is that the hysteresis effect is negligible in homogenous systems.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86306647","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. Kannan, Pal Priyabrata, F. Banat, Satyadileep Dara, I. Khan, Eisa AlJenaibi, Marwan AlAwlqi
Calcium alginate-based carbon composite (CAC) adsorbents have been proved to effectively remove total organic acid anions as HSS anions, metal ions, and organic degraded products from lean methyldiethanolamine (MDEA solvents) used as solvent in natural gas sweetening unit. During the material developmental phase, the CAC adsorbent was synthesized and utilized to remove various contaminants, including heat stable salts (HSS), organic degraded products, and heavy metal ions from lean MDEA using a lab-scale adsorption setup. Based on the results, a "demo-scale" fixed bed adsorption unit was designed and simulated using adsorption model to predict breakthrough behavior. In the current work, the efficiency of the CAC adsorbent in removing HSS and total organic acid anions were investigated. Analysis of treated samples demonstrated the removal efficiency of the adsorbent under plant scale conditions. Further experiments performed at lab scale indicated the effectiveness of the adsorbent in the removal of bicine from lean MDEA samples. This work provides a framework for future testing and comprehensive process performance evaluation of adsorbents for lean MDEA reclamation in actual plant conditions. A fast, simple, and reliable scale up procedure for fixed bed adsorber developed earlier was validated through this work.
{"title":"Calcium Alginate-Based Carbon Composite Adsorbents for Lean Methyldiethanolamine Reclamation: Laboratory to Pilot Scale Testing and Validation","authors":"P. Kannan, Pal Priyabrata, F. Banat, Satyadileep Dara, I. Khan, Eisa AlJenaibi, Marwan AlAwlqi","doi":"10.2118/207754-ms","DOIUrl":"https://doi.org/10.2118/207754-ms","url":null,"abstract":"\u0000 Calcium alginate-based carbon composite (CAC) adsorbents have been proved to effectively remove total organic acid anions as HSS anions, metal ions, and organic degraded products from lean methyldiethanolamine (MDEA solvents) used as solvent in natural gas sweetening unit. During the material developmental phase, the CAC adsorbent was synthesized and utilized to remove various contaminants, including heat stable salts (HSS), organic degraded products, and heavy metal ions from lean MDEA using a lab-scale adsorption setup. Based on the results, a \"demo-scale\" fixed bed adsorption unit was designed and simulated using adsorption model to predict breakthrough behavior. In the current work, the efficiency of the CAC adsorbent in removing HSS and total organic acid anions were investigated. Analysis of treated samples demonstrated the removal efficiency of the adsorbent under plant scale conditions. Further experiments performed at lab scale indicated the effectiveness of the adsorbent in the removal of bicine from lean MDEA samples. This work provides a framework for future testing and comprehensive process performance evaluation of adsorbents for lean MDEA reclamation in actual plant conditions. A fast, simple, and reliable scale up procedure for fixed bed adsorber developed earlier was validated through this work.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87800993","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}
Amaar Siyal, Khurshed Rahimov, W. Alameri, E. Al-Shalabi
Different enhanced oil recovery (EOR) methods are usually applied to target remaining oil saturation in a reservoir after both conventional primary and secondary recovery stages. The remaining oil in the reservoir is classified into capillary trapped residual oil and unswept /bypassed oil. Mobilizing the residual oil in the reservoir is usually achieved through either decreasing the capillary forces and/or increasing the viscous or gravitational forces. The recovery of the microscopically trapped residual oil is mainly studied using capillary desaturation curve (CDC). Hence, a fundamental understanding of the CDC is needed for optimizing the design and application of different EOR methods in both sandstone and carbonate reservoirs. For sandstone reservoirs, especially water-water rocks, determining the residual oil saturation and generating CDC has been widely studied and documented in literature. On the other hand, very few studies have been conducted on carbonate rocks and less data is available. Therefore, this paper provides a comprehensive review of several important research studies published on CDC over the past few decades for both sandstone and carbonate reservoirs. We critically analyzed and discussed theses CDC studies based on capillary number, Bond number, and trapping number ranges. The effect of different factors on CDC were further investigated including interfacial tension, heterogeneity, permeability, and wettability. This comparative review shows that capillary desaturation curves in carbonates are shallower as opposed to these in sandstones. This is due to different factors such as the presence of high fracture density, presence of micropores, large pore size distribution, mixed-to-oil wetting nature, high permeability, and heterogeneity. In general, the critical capillary number reported in literature for sandstone rocks is in the range of 10−5 to 10−2. However, for carbonate rocks, that number ranges between 10−8 and 10−5. In addition, the wettability has been shown to have a major effect on the shape of CDC in both sandstone and carbonate rocks; different CDCs have been reported for water-wet, mixed-wet, and oil-wet rocks. The CDC shape is broader and the capillary number values are higher in oil-wet rocks compared to mixed-wet and water-wet rocks. This study provides a comprehensive and comparative analysis of CDC in both sandstone and carbonate rocks, which serves as a guide in understanding different CDCs and hence, better screening of different EOR methods for different types of reservoirs.
{"title":"Recent Advances in Capillary Desaturation Curves for Sandstone and Carbonate Reservoirs","authors":"Amaar Siyal, Khurshed Rahimov, W. Alameri, E. Al-Shalabi","doi":"10.2118/207595-ms","DOIUrl":"https://doi.org/10.2118/207595-ms","url":null,"abstract":"\u0000 Different enhanced oil recovery (EOR) methods are usually applied to target remaining oil saturation in a reservoir after both conventional primary and secondary recovery stages. The remaining oil in the reservoir is classified into capillary trapped residual oil and unswept /bypassed oil. Mobilizing the residual oil in the reservoir is usually achieved through either decreasing the capillary forces and/or increasing the viscous or gravitational forces. The recovery of the microscopically trapped residual oil is mainly studied using capillary desaturation curve (CDC). Hence, a fundamental understanding of the CDC is needed for optimizing the design and application of different EOR methods in both sandstone and carbonate reservoirs. For sandstone reservoirs, especially water-water rocks, determining the residual oil saturation and generating CDC has been widely studied and documented in literature. On the other hand, very few studies have been conducted on carbonate rocks and less data is available. Therefore, this paper provides a comprehensive review of several important research studies published on CDC over the past few decades for both sandstone and carbonate reservoirs. We critically analyzed and discussed theses CDC studies based on capillary number, Bond number, and trapping number ranges. The effect of different factors on CDC were further investigated including interfacial tension, heterogeneity, permeability, and wettability.\u0000 This comparative review shows that capillary desaturation curves in carbonates are shallower as opposed to these in sandstones. This is due to different factors such as the presence of high fracture density, presence of micropores, large pore size distribution, mixed-to-oil wetting nature, high permeability, and heterogeneity. In general, the critical capillary number reported in literature for sandstone rocks is in the range of 10−5 to 10−2. However, for carbonate rocks, that number ranges between 10−8 and 10−5. In addition, the wettability has been shown to have a major effect on the shape of CDC in both sandstone and carbonate rocks; different CDCs have been reported for water-wet, mixed-wet, and oil-wet rocks. The CDC shape is broader and the capillary number values are higher in oil-wet rocks compared to mixed-wet and water-wet rocks. This study provides a comprehensive and comparative analysis of CDC in both sandstone and carbonate rocks, which serves as a guide in understanding different CDCs and hence, better screening of different EOR methods for different types of reservoirs.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85936825","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}
When inadequate information appears via a long-winded channel, project leaders usually struggle to make timely decisions. There is frequently a lack of visibility, contractual and organizational fragmentation, and genuine facts being segregated and concealed due to an optimism bias. Despite the finest planning and estimation efforts, projects frequently exceed their budgets or experience delays of more than 30%. The paper outlines the importance of data and of data use to improve the performance in projects planning and delivery. The data value and hierarchy are reviewed in the context of the construction industry and the importance of a smooth digitalization process for ensuring acceptance and adoption is discussed. The concept of ‘digital construction blocks’TM and Lean thinking is introduced to address the problem of complexity which is commonly recognized as the main cause of cost overruns, time delays, and poor quality and safety for the construction industry. To capture the footprint of how the asset was built, the authors propose the Digital Twin of Execution adding dynamism to the commonly discussed Digital Twin of Asset, which is more static when the asset has already been constructed. The project is organized into digital blocks, allowing all project functions and disciplines to focus on a common path of construction, allowing for an earlier start of a constraint-free construction and, as a result, de-risking and compressing the total execution schedule. Data from existing systems and technologies is unlocked and placed in automated processes, allowing thousands of documents, activities, and fast-moving events to be collected in digital blocks of construction. The digital block is connected throughout project stages and taken across all aspects of the project, including plot plans, activity plans, drawings, 3D, materials, and so on, resolving the project's disarray caused by manual and analogue procedures. The entire planning, project setup, and execution process is aided by GIS, which provides visibility at various levels of magnification via an interactive geo spatial map superimposed with plot plans, timetables, and work packages. Artificial intelligence (AI) and machine learning (ML) can be used to forecast the probability of danger in various field operations. It's done by using IoT devices implanted in employees’ PPE and in the environment to process data collected on the system. Digital Control Tower can provide a smart dashboard that not only displays the KPIs but also helps the user prioritize his next steps. It may provide an overall view of the project's progress and KPIs, as well as get to the root of a problem in a specific installation area, raise red flags and alerts, and function as a user's assistant by predicting errors early on.
当不充分的信息通过冗长的渠道出现时，项目负责人通常很难及时做出决定。往往缺乏可见性，合同和组织分裂，由于乐观主义偏见，真实的事实被隔离和隐瞒。尽管做了最好的计划和评估工作，项目还是经常超出预算或经历超过30%的延迟。本文概述了数据的重要性，以及数据的使用对提高项目规划和交付绩效的重要性。在建筑行业的背景下回顾了数据价值和层次结构，并讨论了顺利的数字化过程对确保接受和采用的重要性。引入“数字建筑模块”tm和精益思维的概念来解决复杂性问题，复杂性通常被认为是建筑行业成本超支、时间延误、质量和安全差的主要原因。为了捕捉资产如何构建的足迹，作者提出了执行的数字孪生，为通常讨论的资产的数字孪生增加了动态性，当资产已经构建时，数字孪生更加静态。该项目被组织成数字块，允许所有项目功能和学科集中在一个共同的建设路径上，允许更早地开始一个无约束的建设，因此，降低风险并压缩总执行时间表。来自现有系统和技术的数据被解锁并放置在自动化流程中，允许在数字构建块中收集数千个文档、活动和快速移动的事件。数字块连接整个项目阶段，并涵盖项目的各个方面，包括地块计划，活动计划，图纸，3D，材料等，解决了手工和模拟程序造成的项目混乱。整个规划、项目设置和执行过程都得到GIS的帮助，它通过与地块计划、时间表和工作包叠加在一起的交互式地理空间地图，提供了各种放大级别的可见性。人工智能(AI)和机器学习(ML)可用于预测各种现场操作中的危险概率。这是通过使用植入员工个人防护装备和环境中的物联网设备来处理系统上收集的数据来实现的。Digital Control Tower可以提供一个智能仪表板，不仅可以显示kpi，还可以帮助用户确定下一步的优先级。它可以提供项目进度和kpi的总体视图，还可以找到特定安装区域中问题的根源，发出危险信号和警报，并通过早期预测错误来充当用户的助手。
{"title":"Digitally Enabled Organizations- Leveraging New Age Technologies","authors":"Yogesh Chandra Srivastava, Abhishek Srivastava, Consuelo Granata","doi":"10.2118/207380-ms","DOIUrl":"https://doi.org/10.2118/207380-ms","url":null,"abstract":"\u0000 When inadequate information appears via a long-winded channel, project leaders usually struggle to make timely decisions. There is frequently a lack of visibility, contractual and organizational fragmentation, and genuine facts being segregated and concealed due to an optimism bias. Despite the finest planning and estimation efforts, projects frequently exceed their budgets or experience delays of more than 30%. The paper outlines the importance of data and of data use to improve the performance in projects planning and delivery. The data value and hierarchy are reviewed in the context of the construction industry and the importance of a smooth digitalization process for ensuring acceptance and adoption is discussed. The concept of ‘digital construction blocks’TM and Lean thinking is introduced to address the problem of complexity which is commonly recognized as the main cause of cost overruns, time delays, and poor quality and safety for the construction industry.\u0000 To capture the footprint of how the asset was built, the authors propose the Digital Twin of Execution adding dynamism to the commonly discussed Digital Twin of Asset, which is more static when the asset has already been constructed. The project is organized into digital blocks, allowing all project functions and disciplines to focus on a common path of construction, allowing for an earlier start of a constraint-free construction and, as a result, de-risking and compressing the total execution schedule. Data from existing systems and technologies is unlocked and placed in automated processes, allowing thousands of documents, activities, and fast-moving events to be collected in digital blocks of construction. The digital block is connected throughout project stages and taken across all aspects of the project, including plot plans, activity plans, drawings, 3D, materials, and so on, resolving the project's disarray caused by manual and analogue procedures. The entire planning, project setup, and execution process is aided by GIS, which provides visibility at various levels of magnification via an interactive geo spatial map superimposed with plot plans, timetables, and work packages. Artificial intelligence (AI) and machine learning (ML) can be used to forecast the probability of danger in various field operations. It's done by using IoT devices implanted in employees’ PPE and in the environment to process data collected on the system. Digital Control Tower can provide a smart dashboard that not only displays the KPIs but also helps the user prioritize his next steps. It may provide an overall view of the project's progress and KPIs, as well as get to the root of a problem in a specific installation area, raise red flags and alerts, and function as a user's assistant by predicting errors early on.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91124678","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}
Q. Dashti, Saad Matar, Hanan Abdulrazzaq, Nouf Al-Shammari, F. Franco, E. Haryanto, Michael Q Zhang, R. Prakash, Nelson Bolanos, Muhammad Ibrahim, Mostafa Afifi
A network modeling campaign for 15 surface gathering centers involving more than 1800 completion strings has helped to lay out different risks on the existing surface pipeline network facility and improved the screening of different business and action plans for the South East Kuwait (SEK) asset of Kuwait Oil Company. Well and network hydraulic models were created and calibrated to support engineers from field development, planning, and operations teams in evaluating the hydraulics of the production system for the identification of flow assurance problems and system optimization opportunities. Steady-state hydraulic models allowed the analysis of the integrated wells and surface network under multiple operational scenarios, providing an important input to improve the planning and decision-making process. The focus of this study was not only in obtaining an accurate representation of the physical dimension of well and surface network elements, but also in creating a tool that includes standard analytical workflows able to evaluate wells and surface network behavior, thus useful to provide insightful predictive capability and answering the business needs on maintaining oil production and controlling unwanted fluids such as water and gas. For this reason, the model needs to be flexible enough in covering different network operating conditions. With the hydraulic models, the evaluation and diagnosis of the asset for operational problems at well and network level will be faster and more effective, providing reliable solutions in the short- and long-terms. The hydraulic models enable engineers to investigate multiple scenarios to identify constraints and improve the operations performance and the planning process in SEK, with a focus on optimal operational parameters to establish effective wells drawdown, evaluation of artificial lifting requirements, optimal well segregation on gathering centers headers, identification of flow assurance problems and supporting production forecasts to ensure effective production management.
{"title":"Data Analytics into Hydraulic Modelling for Better Understanding of Well/Surface Network Limits, Proactively Identify Challenges and, Provide Solutions for Improved System Performance in the Greater Burgan Field","authors":"Q. Dashti, Saad Matar, Hanan Abdulrazzaq, Nouf Al-Shammari, F. Franco, E. Haryanto, Michael Q Zhang, R. Prakash, Nelson Bolanos, Muhammad Ibrahim, Mostafa Afifi","doi":"10.2118/207512-ms","DOIUrl":"https://doi.org/10.2118/207512-ms","url":null,"abstract":"\u0000 A network modeling campaign for 15 surface gathering centers involving more than 1800 completion strings has helped to lay out different risks on the existing surface pipeline network facility and improved the screening of different business and action plans for the South East Kuwait (SEK) asset of Kuwait Oil Company.\u0000 Well and network hydraulic models were created and calibrated to support engineers from field development, planning, and operations teams in evaluating the hydraulics of the production system for the identification of flow assurance problems and system optimization opportunities. Steady-state hydraulic models allowed the analysis of the integrated wells and surface network under multiple operational scenarios, providing an important input to improve the planning and decision-making process.\u0000 The focus of this study was not only in obtaining an accurate representation of the physical dimension of well and surface network elements, but also in creating a tool that includes standard analytical workflows able to evaluate wells and surface network behavior, thus useful to provide insightful predictive capability and answering the business needs on maintaining oil production and controlling unwanted fluids such as water and gas. For this reason, the model needs to be flexible enough in covering different network operating conditions.\u0000 With the hydraulic models, the evaluation and diagnosis of the asset for operational problems at well and network level will be faster and more effective, providing reliable solutions in the short- and long-terms. The hydraulic models enable engineers to investigate multiple scenarios to identify constraints and improve the operations performance and the planning process in SEK, with a focus on optimal operational parameters to establish effective wells drawdown, evaluation of artificial lifting requirements, optimal well segregation on gathering centers headers, identification of flow assurance problems and supporting production forecasts to ensure effective production management.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"342 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75719676","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}
Min Jia, Jianjun Zhang, X. Han, Junfeng Shi, D. Guo, Guangqiang Cao, Jun Li, Nan Li, Haoyu Wang, Yi Zhang, Yan Liu
Deliquification is the primary technique for stabilizing gas production and improving gas recovery in gas fields producing water, and foam deliquification is the key subject of research for the purpose of enhancing gas production and cutting down cost. However, there is no systematic method to evaluate and compare the effects of foam deliquification in gas wells in various conditions. Aiming at the above problem, a new fuzzy quantitative evaluation method for foam deliquification is proposed. The method focus on four indicators, namely, rate of change in daily gas production, rate of change in daily water production, rate of change in the difference between tubing and casing pressures, and rate of change in daily injection cost. The evaluation results are calculated by the linear analysis, hierarchy analysis and fuzzy relation synthesis operator. The method has been applied to 30 foam deliquification wells in Sulige gas field and Chongqing gas field, and the comprehensive index of foam deliquification effect is calculated. The advantage of this method is that the technical and economic factors affecting foam deliquifiction, the membership relationships of various indicators, as well as the weight coefficients of the indicators are integratedly considered. It can be used for comprehensive evaluation and quantitative comparison of foam deliquification effects in gas wells in various conditions, assisting in determining candidate wells for foam deliquification, and guiding the selection of foaming agents.
{"title":"A Fuzzy Method to Quantitatively Evaluate the Effect of Foam Deliquification in Gas Wells","authors":"Min Jia, Jianjun Zhang, X. Han, Junfeng Shi, D. Guo, Guangqiang Cao, Jun Li, Nan Li, Haoyu Wang, Yi Zhang, Yan Liu","doi":"10.2118/207249-ms","DOIUrl":"https://doi.org/10.2118/207249-ms","url":null,"abstract":"\u0000 Deliquification is the primary technique for stabilizing gas production and improving gas recovery in gas fields producing water, and foam deliquification is the key subject of research for the purpose of enhancing gas production and cutting down cost. However, there is no systematic method to evaluate and compare the effects of foam deliquification in gas wells in various conditions. Aiming at the above problem, a new fuzzy quantitative evaluation method for foam deliquification is proposed. The method focus on four indicators, namely, rate of change in daily gas production, rate of change in daily water production, rate of change in the difference between tubing and casing pressures, and rate of change in daily injection cost. The evaluation results are calculated by the linear analysis, hierarchy analysis and fuzzy relation synthesis operator. The method has been applied to 30 foam deliquification wells in Sulige gas field and Chongqing gas field, and the comprehensive index of foam deliquification effect is calculated. The advantage of this method is that the technical and economic factors affecting foam deliquifiction, the membership relationships of various indicators, as well as the weight coefficients of the indicators are integratedly considered. It can be used for comprehensive evaluation and quantitative comparison of foam deliquification effects in gas wells in various conditions, assisting in determining candidate wells for foam deliquification, and guiding the selection of foaming agents.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73559812","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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