J. Ismailova, A. Abdukarimov, B. Mombekov, D. Delikesheva, L. Zerpa, Zhasulan Dairov
Wax deposition on inner surfaces of pipelines is a costly problem for the petroleum industry. This flow assurance problem is of particular interest during the production and transportation of waxy oils in cold environments. An understanding of known mechanisms and available thermodynamic models will be useful for the management and planning of mitigation strategies for wax deposition. This paper presents a critical review of wax prediction models used for estimation of wax deposition based on chemical hydrocarbon compositions and thermobaric condition. The comparative analysis is applied to highlight the effective mechanisms guiding the wax deposition, and how this knowledge can be used to model and provide solutions to reducing wax deposition issues. One group of thermodynamic models assume that the precipitated wax is a solid solution. These models are divided into two categories: ideal (Erickson and Pedersen models) and non-ideal solutions (Won and Coutinho models). In the other group of models, the wax phase consists of many solid phases (Lira-Galeana model). The authors summarized the limitations of the models, evaluated, and identified ways to represent the overview of existing thermodynamical models for predicting wax precipitation. Within the strong demand from industry, the results of this manuscript can aid to aspire engineers and researcher.
{"title":"A Comparative Evaluation of Thermodynamic Models for Prediction of Wax Deposition","authors":"J. Ismailova, A. Abdukarimov, B. Mombekov, D. Delikesheva, L. Zerpa, Zhasulan Dairov","doi":"10.2118/207984-ms","DOIUrl":"https://doi.org/10.2118/207984-ms","url":null,"abstract":"\u0000 Wax deposition on inner surfaces of pipelines is a costly problem for the petroleum industry. This flow assurance problem is of particular interest during the production and transportation of waxy oils in cold environments. An understanding of known mechanisms and available thermodynamic models will be useful for the management and planning of mitigation strategies for wax deposition. This paper presents a critical review of wax prediction models used for estimation of wax deposition based on chemical hydrocarbon compositions and thermobaric condition. The comparative analysis is applied to highlight the effective mechanisms guiding the wax deposition, and how this knowledge can be used to model and provide solutions to reducing wax deposition issues. One group of thermodynamic models assume that the precipitated wax is a solid solution. These models are divided into two categories: ideal (Erickson and Pedersen models) and non-ideal solutions (Won and Coutinho models). In the other group of models, the wax phase consists of many solid phases (Lira-Galeana model).\u0000 The authors summarized the limitations of the models, evaluated, and identified ways to represent the overview of existing thermodynamical models for predicting wax precipitation.\u0000 Within the strong demand from industry, the results of this manuscript can aid to aspire engineers and researcher.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87588297","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}
B. Al-Otaibi, Issa Abu Shiekah, M. Jha, G. de Bruijn, P. Male, Shahad Al-Omair, H. Ibrahim
After 40 years of depletion drive, a mature, giant and multi-layer carbonate reservoir is developed through waterflooding. Oil production, sustained through infill drilling and new development patterns, is often associated with increasingly higher water production compared to earlier development phases. A field re-development plan has been established to alleviate the impact of reservoir heterogeneities on oil recovery, driven by the analysis of the historical performance of production and injection of a range of well types. The field is developed through historical opportunistic development concepts utilizing evolving technology trends. Therefore, the field has initially wide spacing vertical waterflooding patterns followed by horizontal wells, subjected to seawater or produced water injection, applying a range of wells placement or completion technologies and different water injection operating strategies. Systematic categorization, grouping and analyzing of a rich data set of wells performance have been complemented and integrated with insights from coarse full field and conceptual sector dynamic modeling activities. This workflow efficiently paved the way to optimize the field development aiming for increased oil recovery and cost saving opportunities. Integrated analysis of evolving historical development decisions revealed and ranked the primary subsurface and operational drivers behind the limited sweep efficiency and increased watercut. This helped mapping the impact of fundamental subsurface attributes from well placement, completion, or water injection strategies. Excellent vertical wells performance during the primary depletion and the early stage of water flooding was slowly outperformed by a more sustainable horizontal well production and injection strategy. This is consistent with a conceptual model in which the reservoir is dominated by extensive high conductive features that contributed in the early life of the field to good oil production before becoming the primary source of premature water breakthrough after a limited fraction of pore volume water was injected. The next level of analysis provided actual field evidence to support informed decisions to optimize the front runner horizontal wells development concept to cover wells length, orientation, vertical placement in the stratigraphy, spacing, pattern strategy and completion design. The findings enabled delivering updated field development plan covering the field life cycle to sustain and increase field oil production through adding ~ 200 additional wells and introducing more structured water flooding patterns in addition to establishing improved wells reservoir management practices. This integrated study manifests the power, efficiency and value from data driven analysis to capture lessons learned from evolving wells and development concepts applied in a complex brown field over six decades. The workflow enabled the delivery of an updated field development plan and prod
{"title":"60 Years Field Performance Data-Driven Analytics to Generate Updated Waterflood Field Development Plan in a North Kuwait Giant Carbonate Reservoir","authors":"B. Al-Otaibi, Issa Abu Shiekah, M. Jha, G. de Bruijn, P. Male, Shahad Al-Omair, H. Ibrahim","doi":"10.2118/207231-ms","DOIUrl":"https://doi.org/10.2118/207231-ms","url":null,"abstract":"\u0000 After 40 years of depletion drive, a mature, giant and multi-layer carbonate reservoir is developed through waterflooding. Oil production, sustained through infill drilling and new development patterns, is often associated with increasingly higher water production compared to earlier development phases. A field re-development plan has been established to alleviate the impact of reservoir heterogeneities on oil recovery, driven by the analysis of the historical performance of production and injection of a range of well types.\u0000 The field is developed through historical opportunistic development concepts utilizing evolving technology trends. Therefore, the field has initially wide spacing vertical waterflooding patterns followed by horizontal wells, subjected to seawater or produced water injection, applying a range of wells placement or completion technologies and different water injection operating strategies. Systematic categorization, grouping and analyzing of a rich data set of wells performance have been complemented and integrated with insights from coarse full field and conceptual sector dynamic modeling activities. This workflow efficiently paved the way to optimize the field development aiming for increased oil recovery and cost saving opportunities.\u0000 Integrated analysis of evolving historical development decisions revealed and ranked the primary subsurface and operational drivers behind the limited sweep efficiency and increased watercut. This helped mapping the impact of fundamental subsurface attributes from well placement, completion, or water injection strategies. Excellent vertical wells performance during the primary depletion and the early stage of water flooding was slowly outperformed by a more sustainable horizontal well production and injection strategy. This is consistent with a conceptual model in which the reservoir is dominated by extensive high conductive features that contributed in the early life of the field to good oil production before becoming the primary source of premature water breakthrough after a limited fraction of pore volume water was injected. The next level of analysis provided actual field evidence to support informed decisions to optimize the front runner horizontal wells development concept to cover wells length, orientation, vertical placement in the stratigraphy, spacing, pattern strategy and completion design. The findings enabled delivering updated field development plan covering the field life cycle to sustain and increase field oil production through adding ~ 200 additional wells and introducing more structured water flooding patterns in addition to establishing improved wells reservoir management practices.\u0000 This integrated study manifests the power, efficiency and value from data driven analysis to capture lessons learned from evolving wells and development concepts applied in a complex brown field over six decades. The workflow enabled the delivery of an updated field development plan and prod","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84297913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is based on successful implementation of procedural automation of Ethane (C2) recovery - rejection mode change using Yokogawa's Exapilot software, wherein ADNONC Gas Processing Habshan 5 & Sulphur management approved the implementation based on similar success of the Sulphur Recover Unit start-up/shutdown procedural automation & company's drive for digitalisation. Scope was to develop modules for automating C2 Recovery /Rejection change over procedure in NGL unit using M/s Yokogawa Exapilot software. These automated procedures aimed to standardize said mode change over operations by incorporating the operating know how and the expertise of skilled-experienced operators into the Exapilot system as a set of Standard Operating Procedures (SOPs) that are executed in right operating sequence for enhanced operating efficiency. Two main procedures & associated modules were designed, engineered and built using Exapilot to enable single-click change over automation for NGL units. Those were validated with operation and deployed in the Exapilot Server and were integrated with the Operator Consoles (HIS) for access, and was supplemented with operator training. Ethane Recovery to Rejection Mode Change Ethane Rejection to Recovery Mode Change Besides standardization and reduced change over time, this improved the critical asset integrity and lifespan of NGL section equipment by advocating systematic operations. Following benefits including major take away from this project: ➢ Standardized the mode change-over procedures & minimized human error by the digitalization of paper documentation procedures into electronic workflow process. Procedural Automation like Exapilot is powerful tool for digital transformation of batch/discrete operation like unit/equipment start-up/shutdown or grade/mode change over. ➢ Reduced inherent delay due to manual change over. Hence, minimizing the loss-opportunities & operating cost. Besides this tool can be used as training tool (when used in offline mode) which help operator succession plan & effective knowledge transfer ➢ Automated critical operation such as temperature/flow ramping, improved equipment integrity and prolonged equipment life. Procedural Automation using Exapilot thus can improve operation efficiency, asset integrity, equipment or material life span This paper presents a success story of procedural automation of batch operation in continuation of similar success in SRU start-up & shutdown automation. This tool along with proper integration work with DCS, has opened door for automation/digitalization in batch operation in continuous process not only in other sites of ADNOC Gas Processing and other ADNOC Group Companies but also in other industries that helps companies to enhance efficiency and fulfil their digitalization journey. Though Exapilot software belongs to M/s Yokogawa, however other DCS systems have similar software such as Honeywell DCS EPKS has E-procedure for procedural automation.
{"title":"Procedural Automation of Ethane Recovery to Rejection in NGL Trains","authors":"Subhendu Sengupta, Vincent Goveas","doi":"10.2118/208159-ms","DOIUrl":"https://doi.org/10.2118/208159-ms","url":null,"abstract":"\u0000 This paper is based on successful implementation of procedural automation of Ethane (C2) recovery - rejection mode change using Yokogawa's Exapilot software, wherein ADNONC Gas Processing Habshan 5 & Sulphur management approved the implementation based on similar success of the Sulphur Recover Unit start-up/shutdown procedural automation & company's drive for digitalisation.\u0000 Scope was to develop modules for automating C2 Recovery /Rejection change over procedure in NGL unit using M/s Yokogawa Exapilot software.\u0000 These automated procedures aimed to standardize said mode change over operations by incorporating the operating know how and the expertise of skilled-experienced operators into the Exapilot system as a set of Standard Operating Procedures (SOPs) that are executed in right operating sequence for enhanced operating efficiency.\u0000 Two main procedures & associated modules were designed, engineered and built using Exapilot to enable single-click change over automation for NGL units. Those were validated with operation and deployed in the Exapilot Server and were integrated with the Operator Consoles (HIS) for access, and was supplemented with operator training.\u0000 Ethane Recovery to Rejection Mode Change Ethane Rejection to Recovery Mode Change\u0000 Besides standardization and reduced change over time, this improved the critical asset integrity and lifespan of NGL section equipment by advocating systematic operations.\u0000 Following benefits including major take away from this project:\u0000 ➢ Standardized the mode change-over procedures & minimized human error by the digitalization of paper documentation procedures into electronic workflow process. Procedural Automation like Exapilot is powerful tool for digital transformation of batch/discrete operation like unit/equipment start-up/shutdown or grade/mode change over. ➢ Reduced inherent delay due to manual change over. Hence, minimizing the loss-opportunities & operating cost. Besides this tool can be used as training tool (when used in offline mode) which help operator succession plan & effective knowledge transfer ➢ Automated critical operation such as temperature/flow ramping, improved equipment integrity and prolonged equipment life. Procedural Automation using Exapilot thus can improve operation efficiency, asset integrity, equipment or material life span\u0000 This paper presents a success story of procedural automation of batch operation in continuation of similar success in SRU start-up & shutdown automation. This tool along with proper integration work with DCS, has opened door for automation/digitalization in batch operation in continuous process not only in other sites of ADNOC Gas Processing and other ADNOC Group Companies but also in other industries that helps companies to enhance efficiency and fulfil their digitalization journey. Though Exapilot software belongs to M/s Yokogawa, however other DCS systems have similar software such as Honeywell DCS EPKS has E-procedure for procedural automation.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84424802","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}
W. Liew, El Khalil Mohamed M’Bareck Heboul, Mohamad Shahril Majid Bin Allapitchai, S. Sellapan, Ahmad Luqman Bin Johan, Ahmad Hafizi Bin Ahmad Zaini, Mohd Hairi Bin Abdul Razak, Puteri Dharmilla Syafawati Binti Dharma Dian, Ahmad Zharif Bin Abdullah, William Zomerdijk
Wells plug & abandonment was carried out in a deepwater field (Field C) offshore West Africa. There were 15 deepwater subsea wells in this field. Thirteen of the wells were completed with Open Water Vertical Xmas Tree (OXT) while remaining two were completed with Enhanced Vertical Xmas Tree (EVXT). In the wells with Open Water Vertical Xmas Tree (OXT), the upper completion tubing and hanger were ran together with the Xmas Tree in a single run. This posed challenges to Operator in retrieving the Xmas Tree. This paper will discuss the novel approach used by Operator in the OXT retrieval. Due to the design of OXT which was different from most of the vertical Xmas Trees (XT) in the world, there were a few challenges in the process of XTs retrieval. If the XTs and upper completion tubing were retrieved in reversal of the way it was completed, it will exposed the well to prolonged duration of single barrier until a BOP can be latched on for subsequent activities. On top of that, the Original Equipment Manufacturer's Completion Workover Riser (CWOR) system and Support Landing Structure (SLS) was not available in full package to be utilized in this project. Furthermore, there were constraints on the rig moonpool space, handling of OXT on surface and clashes between the rig's BOP and existing subsea structures. In managing the risk of well exposure to single proven and monitored barrier during the process of OXT retrieval, Operator has evaluated a few options and came out with a novel approach in the OXT retrieval which managed to minimize exposure time and reduce risk in operations. In contrary to the original principle of well completion here, after a barrier was established in the well, the OXTs was retrieved separately from the upper completion tubing to allow rig BOP to be latched onto wellhead in shortest possible time. To achieve this objective, operations was planned to be carried out on a dual activity derrick rig. Meanwhile, a non-OEM rental CWOR system was used together with Tree Running Tool from the OEM CWOR system to access the wells for intervention work and subsequently retrieve the OXTs. By doing this, the combined CWOR stack exceeded the height limitation at the rig's moonpool. Some modifications were carried out to allow the operations to happen. A novel approach was also used to handle the OXT on surface without the OEM Support Landing Structure - which simplified the operations and reduced HSE risks. Solution was also put into place to enable latching of the rig BOP onto wellheads on Drill Centre although there were risk of clashing initially.
{"title":"A Novel Approach to First in the World Retrieval of Open Water Vertical Xmas Tree","authors":"W. Liew, El Khalil Mohamed M’Bareck Heboul, Mohamad Shahril Majid Bin Allapitchai, S. Sellapan, Ahmad Luqman Bin Johan, Ahmad Hafizi Bin Ahmad Zaini, Mohd Hairi Bin Abdul Razak, Puteri Dharmilla Syafawati Binti Dharma Dian, Ahmad Zharif Bin Abdullah, William Zomerdijk","doi":"10.2118/207376-ms","DOIUrl":"https://doi.org/10.2118/207376-ms","url":null,"abstract":"\u0000 Wells plug & abandonment was carried out in a deepwater field (Field C) offshore West Africa. There were 15 deepwater subsea wells in this field. Thirteen of the wells were completed with Open Water Vertical Xmas Tree (OXT) while remaining two were completed with Enhanced Vertical Xmas Tree (EVXT). In the wells with Open Water Vertical Xmas Tree (OXT), the upper completion tubing and hanger were ran together with the Xmas Tree in a single run. This posed challenges to Operator in retrieving the Xmas Tree. This paper will discuss the novel approach used by Operator in the OXT retrieval.\u0000 Due to the design of OXT which was different from most of the vertical Xmas Trees (XT) in the world, there were a few challenges in the process of XTs retrieval. If the XTs and upper completion tubing were retrieved in reversal of the way it was completed, it will exposed the well to prolonged duration of single barrier until a BOP can be latched on for subsequent activities. On top of that, the Original Equipment Manufacturer's Completion Workover Riser (CWOR) system and Support Landing Structure (SLS) was not available in full package to be utilized in this project. Furthermore, there were constraints on the rig moonpool space, handling of OXT on surface and clashes between the rig's BOP and existing subsea structures.\u0000 In managing the risk of well exposure to single proven and monitored barrier during the process of OXT retrieval, Operator has evaluated a few options and came out with a novel approach in the OXT retrieval which managed to minimize exposure time and reduce risk in operations. In contrary to the original principle of well completion here, after a barrier was established in the well, the OXTs was retrieved separately from the upper completion tubing to allow rig BOP to be latched onto wellhead in shortest possible time. To achieve this objective, operations was planned to be carried out on a dual activity derrick rig. Meanwhile, a non-OEM rental CWOR system was used together with Tree Running Tool from the OEM CWOR system to access the wells for intervention work and subsequently retrieve the OXTs. By doing this, the combined CWOR stack exceeded the height limitation at the rig's moonpool. Some modifications were carried out to allow the operations to happen. A novel approach was also used to handle the OXT on surface without the OEM Support Landing Structure - which simplified the operations and reduced HSE risks. Solution was also put into place to enable latching of the rig BOP onto wellheads on Drill Centre although there were risk of clashing initially.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88147506","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}
Instead of relying on analytical functions to approximate property relationships, this innovative hybrid neural network technique offers highly adaptive, full-function (!) predictions that can be applied to different subsurface data types ranging from (1.) core-to-log prediction (permeability), (2.) multivariate property maps (oil-saturated thickness maps), and, (3.) petrophysical properties from 3D seismic data (i.e., hydrocarbon pore volume, instantaneous velocity). For each scenario a separate example is shown. In case study 1, core measurements are used as the target array and well log data serve training. To analyze the uncertainty of predicted estimates, a second oilfield case study applies 100 iterations of log data from 350 wells to obtain P10-P50-P90 probabilities by randomly removing 40% (140 wells) for validation purposes. In a third case study elastic logs and a low-frequency model are used to predict seismic properties. KNN generates a high level of freedom operator with only one (or more) hidden layer(s). Iterative parameterization precludes that high correlation coefficients arise from overtraining. Because the key advantage of the Kolmogorov neural network (KNN) is to permit non-linear, full-function approximations of reservoir properties, the KNN approach provides a higher-fidelity solution in comparison to other linear or non-linear neural net regressions. KNN offers a fast-track alternative to classic reservoir property predictions from model-based seismic inversions by combining (a) Kolmogorov's Superposition Theorem and (b) principles of genetic inversion (Darwin's "Survival of the fittest") together with Tikhonov regularization and gradient theory. In practice, this is accomplished by minimizing an objective function on multiple and simultaneous outputs from full-function (via look-up table) Kolmogorov neural network runs. All case studies produce high correlations between actual and predicted properties when compared to other stochastic or deterministic inversions. For instance, in the log to seismic prediction better (simulated) resolution of neural network results can be discerned compared to traditional inversion results. Moreover, all blind tests match the overall shape of prominent log curve deflections with a higher degree of fidelity than from inversion. An important fringe benefit of KNN application is the observed increase in seismic resolution that by comparison falls between the seismic resolution of a model-based inversion and the simulated resolution from seismic stochastic inversion.
{"title":"New-Age Kolmogorov Full-Function Neural Network KNN Offers High-Fidelity Reservoir Predictions via Estimation of Core, Well Log, Map and Seismic Properties","authors":"I. Priezzhev, D. Danko, U. Strecker","doi":"10.2118/207575-ms","DOIUrl":"https://doi.org/10.2118/207575-ms","url":null,"abstract":"\u0000 Instead of relying on analytical functions to approximate property relationships, this innovative hybrid neural network technique offers highly adaptive, full-function (!) predictions that can be applied to different subsurface data types ranging from (1.) core-to-log prediction (permeability), (2.) multivariate property maps (oil-saturated thickness maps), and, (3.) petrophysical properties from 3D seismic data (i.e., hydrocarbon pore volume, instantaneous velocity). For each scenario a separate example is shown. In case study 1, core measurements are used as the target array and well log data serve training. To analyze the uncertainty of predicted estimates, a second oilfield case study applies 100 iterations of log data from 350 wells to obtain P10-P50-P90 probabilities by randomly removing 40% (140 wells) for validation purposes. In a third case study elastic logs and a low-frequency model are used to predict seismic properties. KNN generates a high level of freedom operator with only one (or more) hidden layer(s). Iterative parameterization precludes that high correlation coefficients arise from overtraining. Because the key advantage of the Kolmogorov neural network (KNN) is to permit non-linear, full-function approximations of reservoir properties, the KNN approach provides a higher-fidelity solution in comparison to other linear or non-linear neural net regressions. KNN offers a fast-track alternative to classic reservoir property predictions from model-based seismic inversions by combining (a) Kolmogorov's Superposition Theorem and (b) principles of genetic inversion (Darwin's \"Survival of the fittest\") together with Tikhonov regularization and gradient theory. In practice, this is accomplished by minimizing an objective function on multiple and simultaneous outputs from full-function (via look-up table) Kolmogorov neural network runs. All case studies produce high correlations between actual and predicted properties when compared to other stochastic or deterministic inversions. For instance, in the log to seismic prediction better (simulated) resolution of neural network results can be discerned compared to traditional inversion results. Moreover, all blind tests match the overall shape of prominent log curve deflections with a higher degree of fidelity than from inversion. An important fringe benefit of KNN application is the observed increase in seismic resolution that by comparison falls between the seismic resolution of a model-based inversion and the simulated resolution from seismic stochastic inversion.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85750922","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 COVID-19 quickly spread across the globe to reach pandemic levels, companies across every industry had to quickly adapt their business practices to allow employees to connect virtually and work remotely. This addressed new complications in several areas, including contact tracing. This paper reviews an approach that Siemens Energy took to remove the errors and inefficiencies in manually conducting contact tracing by automating the process using an end-to-end case manager app. The app, which provides full transparency, analytics, and support, fully digitizes contact tracing from each employee's mobile device or computer. We discuss the features of the app, how it has been used in the UAE region, and the benefits that the company has realized in automating contact tracing—including faster tracing time, improved accuracy, and greater compliance with UAE COVID requirements. In just a few months’ time, the app went from an idea to a fully-developed and widely used application—which is now approved for use in company facilities and business units around the world.
{"title":"COVID-19 Case Manager App for Oil & Gas Companies","authors":"Shamrose Yaqoob, Salman Ali Khan","doi":"10.2118/207329-ms","DOIUrl":"https://doi.org/10.2118/207329-ms","url":null,"abstract":"\u0000 As COVID-19 quickly spread across the globe to reach pandemic levels, companies across every industry had to quickly adapt their business practices to allow employees to connect virtually and work remotely. This addressed new complications in several areas, including contact tracing. This paper reviews an approach that Siemens Energy took to remove the errors and inefficiencies in manually conducting contact tracing by automating the process using an end-to-end case manager app.\u0000 The app, which provides full transparency, analytics, and support, fully digitizes contact tracing from each employee's mobile device or computer. We discuss the features of the app, how it has been used in the UAE region, and the benefits that the company has realized in automating contact tracing—including faster tracing time, improved accuracy, and greater compliance with UAE COVID requirements.\u0000 In just a few months’ time, the app went from an idea to a fully-developed and widely used application—which is now approved for use in company facilities and business units around the world.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79742370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the latest developments in Transport and Installation methods for Topsides up to 38,500mt. For such heavy-weight structures Boskalis introduces a solution by combining the beneficial features of a Heavy Transport Vessel dry-transportation with the advantages of a DP2 Barge float-over installation. This unique Transport and Installation approach, a so called "Piggyback T&I", may be characterized as follows:
{"title":"Upscaling Float-over Installation","authors":"Rory van Doorn, Sebastiaan Polkamp","doi":"10.2118/207741-ms","DOIUrl":"https://doi.org/10.2118/207741-ms","url":null,"abstract":"\u0000 This paper presents the latest developments in Transport and Installation methods for Topsides up to 38,500mt.\u0000 For such heavy-weight structures Boskalis introduces a solution by combining the beneficial features of a Heavy Transport Vessel dry-transportation with the advantages of a DP2 Barge float-over installation.\u0000 This unique Transport and Installation approach, a so called \"Piggyback T&I\", may be characterized as follows:","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80239963","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}
Giulia Ness, K. Sorbie, Ali Hassan Al Mesmari, S. Masalmeh
Wells producing from an oilfield in Abu Dhabi were investigated to understand the CaCO3 scaling risk at current production conditions, and to predict how the downhole and topside scaling potential will change during a planned CO2 WAG project. The results of this study will be used to design the correct scale inhibitor treatment for each production phase. A rigorous scale prediction procedure for pH dependent scales previously published by the authors was applied using a commercial integrated PVT and aqueous modelling software package to produce scale prediction profiles through the system. This procedure was applied to run many sensitivity studies and determine the impact of field data variables on the final scale predictions. These results were used to examine the scaling potential of current and future fluids by creating a diagnostic "what if" chart. Some of the main variables investigated include changes in operating pressure, CO2 and H2S concentrations and variable water cut. Scale prediction profiles through the entire system from reservoir to stock tank conditions were obtained using the above modelling procedure. The main findings in this study are: (i) That CaCO3 scale is not predicted to form at separator conditions under any of the current or future scenarios investigated for these wells. This is due to the high separator pressure which holds enough CO2 in solution to keep the pH low and prevent scale precipitation. (ii) The water at stock tank conditions was found to be the critical point in the system where the CaCO3 scaling risk is severe, and where preventative action must be taken. (iii) Implementing CO2 WAG does not affect CaCO3 scaling risk at separator conditions where fluids remain undersaturated. However, the additional CO2 dissolves more CaCO3 rock in the reservoir producing higher alkalinity fluids which result in more CaCO3 scale precipitation at stock tank conditions. (iv) Fluids entering the wellbore are likely to precipitate some CaCO3 (albeit at a fairly low saturation ratio, SR) due to a significant pressure drop and the relatively high temperature, and this is not associated with the-bubble point in this case. This downhole scaling potential becomes slightly worse by an increase in CO2 concentration during CO2 WAG operations.(v) Scale inhibitor may or may not be required to treat downhole fluids depending on the wellbore pressure drop, but it is always necessary to treat fluids downstream of the separator due to the very high scaling potential at stock tank conditions. By applying a rigorous scale prediction procedure, it was possible to study the impact of CO2 WAG on the risk of CaCO3 scale precipitation downhole and topside for this field. These results highlight the current threat downhole and at stock tank conditions in particular and show how this will worsen with the implementation of CO2 WAG and this will require a chemical treatment review.
{"title":"The Evolution of CaCO3 Scaling Potential in ADNOC Reservoirs Under Water Flooding and CO2 WAG Scenarios","authors":"Giulia Ness, K. Sorbie, Ali Hassan Al Mesmari, S. Masalmeh","doi":"10.2118/208193-ms","DOIUrl":"https://doi.org/10.2118/208193-ms","url":null,"abstract":"\u0000 Wells producing from an oilfield in Abu Dhabi were investigated to understand the CaCO3 scaling risk at current production conditions, and to predict how the downhole and topside scaling potential will change during a planned CO2 WAG project. The results of this study will be used to design the correct scale inhibitor treatment for each production phase.\u0000 A rigorous scale prediction procedure for pH dependent scales previously published by the authors was applied using a commercial integrated PVT and aqueous modelling software package to produce scale prediction profiles through the system. This procedure was applied to run many sensitivity studies and determine the impact of field data variables on the final scale predictions. These results were used to examine the scaling potential of current and future fluids by creating a diagnostic \"what if\" chart. Some of the main variables investigated include changes in operating pressure, CO2 and H2S concentrations and variable water cut.\u0000 Scale prediction profiles through the entire system from reservoir to stock tank conditions were obtained using the above modelling procedure. The main findings in this study are: (i) That CaCO3 scale is not predicted to form at separator conditions under any of the current or future scenarios investigated for these wells. This is due to the high separator pressure which holds enough CO2 in solution to keep the pH low and prevent scale precipitation. (ii) The water at stock tank conditions was found to be the critical point in the system where the CaCO3 scaling risk is severe, and where preventative action must be taken. (iii) Implementing CO2 WAG does not affect CaCO3 scaling risk at separator conditions where fluids remain undersaturated. However, the additional CO2 dissolves more CaCO3 rock in the reservoir producing higher alkalinity fluids which result in more CaCO3 scale precipitation at stock tank conditions. (iv) Fluids entering the wellbore are likely to precipitate some CaCO3 (albeit at a fairly low saturation ratio, SR) due to a significant pressure drop and the relatively high temperature, and this is not associated with the-bubble point in this case. This downhole scaling potential becomes slightly worse by an increase in CO2 concentration during CO2 WAG operations.(v) Scale inhibitor may or may not be required to treat downhole fluids depending on the wellbore pressure drop, but it is always necessary to treat fluids downstream of the separator due to the very high scaling potential at stock tank conditions.\u0000 By applying a rigorous scale prediction procedure, it was possible to study the impact of CO2 WAG on the risk of CaCO3 scale precipitation downhole and topside for this field. These results highlight the current threat downhole and at stock tank conditions in particular and show how this will worsen with the implementation of CO2 WAG and this will require a chemical treatment review.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90176573","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}
AbdulMuqtadir Khan, Abdullah Binziad, Abdullah Subaii, D. Bannikov, Maksim Ponomarev, Sergey Parkhonyuk
Vertical wells require diagnostic techniques after minifrac pumping to interpret fracture height growth. This interpretation provides vital input to hydraulic fracturing redesign workflows. The temperature log is the most widely used technique to determine fracture height through cooldown analysis. A data science approach is proposed to leverage available measurements, automate the interpretation process, and enhance operational efficiency while keeping confidence in the fracturing design. Data from 55 wells were ingested to establish proof of concept.The selected geomechanical rock texture parameters were based on the fracturing theory of net-pressure-controlled height growth. Interpreted fracture height from input temperature cooldown analysis was merged with the structured dataset. The dataset was constructed at a high vertical depth of resolution of 0.5 to 1 ft. Openhole log data such as gamma-ray and bulk density helped to characterize the rock type, and calculated mechanical properties from acoustic logs such as in-situ stress and Young's modulus characterize the fracture geometry development. Moreover, injection rate, volume, and net pressure during the calibration treatment affect the fracture height growth. A machine learning (ML) workflow was applied to multiple openhole log parameters, which were integrated with minifrac calibration parameters along with the varying depth of the reservoir. The 55 wells datasets with a cumulative 120,000 rows were divided into training and testing with a ratio of 80:20. A comparative algorithm study was conducted on the test set with nine algorithms, and CatBoost showed the best results with an RMSE of 4.13 followed by Random Forest with 4.25. CatBoost models utilize both categorical and numerical data. Stress, gamma-ray, and bulk density parameters affected the fracture height analyzed from the post-fracturing temperature logs. Following successful implementation in the pilot phase, the model can be extended to horizontal wells to validate predictions from commercial simulators where stress calculations were unreliable or where stress did not entirely reflect changes in rock type. By coupling the geometry measurement technology with data analysis, a useful automated model was successfully developed to enhance operational efficiency without compromising any part of the workflow. The advanced algorithm can be used in any field where precise fracture placement of a hydraulic fracture contributes directly to production potential. Also, the model can play a critical role in cube development to optimize lateral landing and lateral density for exploration fields.
{"title":"Fracture Height Prediction Model Utilizing Openhole Logs, Mechanical Models, and Temperature Cooldown Analysis with Machine Learning Algorithms","authors":"AbdulMuqtadir Khan, Abdullah Binziad, Abdullah Subaii, D. Bannikov, Maksim Ponomarev, Sergey Parkhonyuk","doi":"10.2118/207975-ms","DOIUrl":"https://doi.org/10.2118/207975-ms","url":null,"abstract":"\u0000 Vertical wells require diagnostic techniques after minifrac pumping to interpret fracture height growth. This interpretation provides vital input to hydraulic fracturing redesign workflows. The temperature log is the most widely used technique to determine fracture height through cooldown analysis. A data science approach is proposed to leverage available measurements, automate the interpretation process, and enhance operational efficiency while keeping confidence in the fracturing design.\u0000 Data from 55 wells were ingested to establish proof of concept.The selected geomechanical rock texture parameters were based on the fracturing theory of net-pressure-controlled height growth. Interpreted fracture height from input temperature cooldown analysis was merged with the structured dataset. The dataset was constructed at a high vertical depth of resolution of 0.5 to 1 ft. Openhole log data such as gamma-ray and bulk density helped to characterize the rock type, and calculated mechanical properties from acoustic logs such as in-situ stress and Young's modulus characterize the fracture geometry development. Moreover, injection rate, volume, and net pressure during the calibration treatment affect the fracture height growth.\u0000 A machine learning (ML) workflow was applied to multiple openhole log parameters, which were integrated with minifrac calibration parameters along with the varying depth of the reservoir. The 55 wells datasets with a cumulative 120,000 rows were divided into training and testing with a ratio of 80:20. A comparative algorithm study was conducted on the test set with nine algorithms, and CatBoost showed the best results with an RMSE of 4.13 followed by Random Forest with 4.25. CatBoost models utilize both categorical and numerical data. Stress, gamma-ray, and bulk density parameters affected the fracture height analyzed from the post-fracturing temperature logs. Following successful implementation in the pilot phase, the model can be extended to horizontal wells to validate predictions from commercial simulators where stress calculations were unreliable or where stress did not entirely reflect changes in rock type.\u0000 By coupling the geometry measurement technology with data analysis, a useful automated model was successfully developed to enhance operational efficiency without compromising any part of the workflow. The advanced algorithm can be used in any field where precise fracture placement of a hydraulic fracture contributes directly to production potential. Also, the model can play a critical role in cube development to optimize lateral landing and lateral density for exploration fields.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90302097","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}
Rylan Paul Dsouza, R. Cornwall, Alan David Brodie, Pedro Patela, H. Daghmouni, Mohammad Hariz Arakkalakkam, Venkata Praveen Kumar Boni, Asif Khan Haq Dad Khan
This paper describes an innovative solution for the safe and effective management of wells with unplanned sustained annulus pressure (SAP). The solution restores double barrier integrity in the well and provides reliable real time annulus pressure and temperature data. It also has the functionality to autonomously bleed-off the annulus pressure at a pre-determined set point. As a result, the nature and severity of the SAP can be better understood, and in many cases wells that would otherwise have been closed in awaiting workover can remain in production.
{"title":"Case Study of a Novel Autonomous Real-Time Monitoring, Control and Analysis System, to Maximize Production Uptime on Sustained Annulus Pressure Wells, While Improving HSE and Compliance with Double Barrier Well Integrity Policies","authors":"Rylan Paul Dsouza, R. Cornwall, Alan David Brodie, Pedro Patela, H. Daghmouni, Mohammad Hariz Arakkalakkam, Venkata Praveen Kumar Boni, Asif Khan Haq Dad Khan","doi":"10.2118/208114-ms","DOIUrl":"https://doi.org/10.2118/208114-ms","url":null,"abstract":"\u0000 This paper describes an innovative solution for the safe and effective management of wells with unplanned sustained annulus pressure (SAP). The solution restores double barrier integrity in the well and provides reliable real time annulus pressure and temperature data. It also has the functionality to autonomously bleed-off the annulus pressure at a pre-determined set point. As a result, the nature and severity of the SAP can be better understood, and in many cases wells that would otherwise have been closed in awaiting workover can remain in production.","PeriodicalId":10959,"journal":{"name":"Day 3 Wed, November 17, 2021","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80682962","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}