OTC-28901-MS proposed the novel dynamically installed "fish" anchor in 2018, adopting a geometry taken from nature, for potential economic and safer tethering of floating facilities in deep water. Every cross section of the fish anchor shaft is elliptical, leading to very low drag resistance during free fall through the water column, and also low resistance in penetrating the seabed sediments. The padeye is fitted on the widest part of the shaft to mobilise the maximum resistance area under operational loading. The fish anchor embedment depth during dynamic installation, and capacity under both monotonic and cyclic operational loading in calcareous silt were assessed through centrifuge model tests and large deformation finite element analyses. During dynamic installation, the normalised tip embedment depth of the fish anchor was typically three times that for the torpedo anchors and 50% greater than that for the OMNI-Max anchors. Under operational loading, the fish anchor dove deeper, reaching penetrations 20 to 60% greater than achieved during installation. By contrast the torpedo anchors (for all mooring mudline inclinations) and the OMNI-Max anchors (apart from a single test with mooring mudline inclination of 0°) pulled out directly without diving, reflecting insufficient free-fall penetration in calcareous soil. This paper provides a follow up reporting the performance of the fish anchor through field tests in the Swan River, Perth. A 1/15th scale model fish anchor was fabricated with dry weight being 0.304 kN. The anchor was tested at five different locations. At two shallow water locations (water depths 1.1 and 1.9 m, respectively), the tests were performed from the Burswood and Maylands jetty. At relatively deeper water depths of 2.91∼4.73 m, the tests were performed from a barge. The riverbed soils consisted of clay, silty clay, silt and sandy silt. The impact velocities were 5.9∼11.7 m/s. The normalised tip embedment depths were even greater compared to those achieved from centrifuge tests in calcareous silt. Under operational monotonic loadings, the fish anchor dove, as opposed to pull out of the riverbed, for mooring angles ≤ 37∼47°. Interestingly, in contrast to non-diving torpedo and suction caisson anchors, the diving fish anchor resulted non-elliptical failure envelopes, which have been expressed mathematically. The ultimate capacity was 3.5∼15 times the weight of the anchor submerged in water for taught and catenary moorings.
{"title":"Fish Anchor Testing in the Swan River","authors":"M. Hossain, Youngho Kim","doi":"10.4043/31423-ms","DOIUrl":"https://doi.org/10.4043/31423-ms","url":null,"abstract":"\u0000 OTC-28901-MS proposed the novel dynamically installed \"fish\" anchor in 2018, adopting a geometry taken from nature, for potential economic and safer tethering of floating facilities in deep water. Every cross section of the fish anchor shaft is elliptical, leading to very low drag resistance during free fall through the water column, and also low resistance in penetrating the seabed sediments. The padeye is fitted on the widest part of the shaft to mobilise the maximum resistance area under operational loading. The fish anchor embedment depth during dynamic installation, and capacity under both monotonic and cyclic operational loading in calcareous silt were assessed through centrifuge model tests and large deformation finite element analyses. During dynamic installation, the normalised tip embedment depth of the fish anchor was typically three times that for the torpedo anchors and 50% greater than that for the OMNI-Max anchors. Under operational loading, the fish anchor dove deeper, reaching penetrations 20 to 60% greater than achieved during installation. By contrast the torpedo anchors (for all mooring mudline inclinations) and the OMNI-Max anchors (apart from a single test with mooring mudline inclination of 0°) pulled out directly without diving, reflecting insufficient free-fall penetration in calcareous soil.\u0000 This paper provides a follow up reporting the performance of the fish anchor through field tests in the Swan River, Perth. A 1/15th scale model fish anchor was fabricated with dry weight being 0.304 kN. The anchor was tested at five different locations. At two shallow water locations (water depths 1.1 and 1.9 m, respectively), the tests were performed from the Burswood and Maylands jetty. At relatively deeper water depths of 2.91∼4.73 m, the tests were performed from a barge. The riverbed soils consisted of clay, silty clay, silt and sandy silt. The impact velocities were 5.9∼11.7 m/s. The normalised tip embedment depths were even greater compared to those achieved from centrifuge tests in calcareous silt. Under operational monotonic loadings, the fish anchor dove, as opposed to pull out of the riverbed, for mooring angles ≤ 37∼47°. Interestingly, in contrast to non-diving torpedo and suction caisson anchors, the diving fish anchor resulted non-elliptical failure envelopes, which have been expressed mathematically. The ultimate capacity was 3.5∼15 times the weight of the anchor submerged in water for taught and catenary moorings.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88818266","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}
Norlela Mustaffa, Rohaizad M Norpiah, Dyg Amalina Azzyati Awang Bakar, Qurratuaini M Nazori, Muliadi Agus
Typically, for a high volume, low condensate-gas ratio offshore gas production field having high content of carbon dioxide (CO2), hydrogen sulphide (H2S), mercury and solid particulates having to meet Liquified Natural Gas (LNG) inlet specification would require an enormous facility exceeding the largest available floatover vessel capacity. Aside from an enormous and complex processing facility, it would also require a large emergency disposal system and sour service pipeline material to cater for start-up and process excursion scenarios. In order to obtain a commercially attractive solution while meeting technical integrity and designing for operational excellence in mind, several innovative design approaches were implemented. The scope of this paper will cover major optimization implemented at gas treatment system, emergency blowdown system, export gas pipeline, and venting system at receiving platform.
{"title":"Weathering Uncertainties in Oil & Gas: Challenges and Design Optimization of High Contaminant Gas Field","authors":"Norlela Mustaffa, Rohaizad M Norpiah, Dyg Amalina Azzyati Awang Bakar, Qurratuaini M Nazori, Muliadi Agus","doi":"10.4043/31379-ms","DOIUrl":"https://doi.org/10.4043/31379-ms","url":null,"abstract":"\u0000 Typically, for a high volume, low condensate-gas ratio offshore gas production field having high content of carbon dioxide (CO2), hydrogen sulphide (H2S), mercury and solid particulates having to meet Liquified Natural Gas (LNG) inlet specification would require an enormous facility exceeding the largest available floatover vessel capacity. Aside from an enormous and complex processing facility, it would also require a large emergency disposal system and sour service pipeline material to cater for start-up and process excursion scenarios. In order to obtain a commercially attractive solution while meeting technical integrity and designing for operational excellence in mind, several innovative design approaches were implemented. The scope of this paper will cover major optimization implemented at gas treatment system, emergency blowdown system, export gas pipeline, and venting system at receiving platform.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88603761","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}
Tossapol Tongkum, Khamawat Siritheerasas, Feras Abu Jafar, Chulakorn Yosakrai, A. Abbasgholipour
Mubadala Petroleum conducts a fast-paced drilling program in the Gulf of Thailand, where rapid response resolutions are often required. This paper demonstrates the Remote Operation (RO) approach, which is an integrated approach comprised of people, software, network, and technology to transform operations, and moves analytical activities to safer office-based environments (Figure 1). The approach provides a high level of performance, leveraging global domain expertise, real-time collaboration, data visualization techniques, and intelligent planning within the restrictive context of the COVID-19 pandemic. Figure 1 Remote Operation relevant function RO is the ability to operate a system at a distance. This is an adopted innovation and technology in the oil and gas industry, which is a completely new way of working. The principal concept for introducing the RO approach was to reduce the Personnel on Board (POB) and the HSE exposure, which was particularly relevant during the outbreak of the COVID-19 pandemic. The approach relied on leading-edge digital technology, as the RO was required to handle real-time directional drilling (DD), measurements, and logging while drilling (MLWD). During the implementation, the crew was trained in multi-skilling related to the DD/MLWD function, while working with the necessity of digital technology. Digital transformation is emerging as a driver of sweeping change in the world around us. Today, the Oil and Gas industry has redefined its boundaries through automation and digitalization. The potential benefits of going digital are clear, including increased productivity, safer operations, and significant cost savings. This exercise, it allowed us to reduce the POB on-site by 40% while maintaining both drilling efficiency and service quality. The drilling data can be monitored in real-time. The Remote Operation Center (ROC) has the capacity to execution and montor directional drilling, formation evaluation, programming, and dumping data from various tools. An experienced crew were assigned to the RO team ensuring competencies and familiarity with drilling operation in specific field characterization. This transformation supported our business continuity objectives by reducing the number of people traveling offshore during the COVID-19 pandemic while allowing us to achieve all our drilling performance objectives. In this new environment, following the turmoil of pandemics, this exercise indicates an opportunity to make fundamental improvements to the way business is conducted using the Remote Operations approach. RO takes a significant step towards the future for highly traditional industry. Preparing the industry toward the future may prove to be the most important outcome of the application of RO during the COVID-19 pandemic. The application of RO during the COVID pandemic has confirmed the possibility of more permanent improvements and increased resilience against future pandemics and other challenging events,
{"title":"Remote Operations and Digital Transformation: A Solution for Business Continuity During Covid-19 Pandemic","authors":"Tossapol Tongkum, Khamawat Siritheerasas, Feras Abu Jafar, Chulakorn Yosakrai, A. Abbasgholipour","doi":"10.4043/31336-ms","DOIUrl":"https://doi.org/10.4043/31336-ms","url":null,"abstract":"\u0000 Mubadala Petroleum conducts a fast-paced drilling program in the Gulf of Thailand, where rapid response resolutions are often required. This paper demonstrates the Remote Operation (RO) approach, which is an integrated approach comprised of people, software, network, and technology to transform operations, and moves analytical activities to safer office-based environments (Figure 1). The approach provides a high level of performance, leveraging global domain expertise, real-time collaboration, data visualization techniques, and intelligent planning within the restrictive context of the COVID-19 pandemic.\u0000 Figure 1 Remote Operation relevant function\u0000 RO is the ability to operate a system at a distance. This is an adopted innovation and technology in the oil and gas industry, which is a completely new way of working. The principal concept for introducing the RO approach was to reduce the Personnel on Board (POB) and the HSE exposure, which was particularly relevant during the outbreak of the COVID-19 pandemic. The approach relied on leading-edge digital technology, as the RO was required to handle real-time directional drilling (DD), measurements, and logging while drilling (MLWD). During the implementation, the crew was trained in multi-skilling related to the DD/MLWD function, while working with the necessity of digital technology.\u0000 Digital transformation is emerging as a driver of sweeping change in the world around us. Today, the Oil and Gas industry has redefined its boundaries through automation and digitalization. The potential benefits of going digital are clear, including increased productivity, safer operations, and significant cost savings. This exercise, it allowed us to reduce the POB on-site by 40% while maintaining both drilling efficiency and service quality. The drilling data can be monitored in real-time. The Remote Operation Center (ROC) has the capacity to execution and montor directional drilling, formation evaluation, programming, and dumping data from various tools.\u0000 An experienced crew were assigned to the RO team ensuring competencies and familiarity with drilling operation in specific field characterization. This transformation supported our business continuity objectives by reducing the number of people traveling offshore during the COVID-19 pandemic while allowing us to achieve all our drilling performance objectives. In this new environment, following the turmoil of pandemics, this exercise indicates an opportunity to make fundamental improvements to the way business is conducted using the Remote Operations approach.\u0000 RO takes a significant step towards the future for highly traditional industry. Preparing the industry toward the future may prove to be the most important outcome of the application of RO during the COVID-19 pandemic. The application of RO during the COVID pandemic has confirmed the possibility of more permanent improvements and increased resilience against future pandemics and other challenging events,","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88886790","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}
Antoine Fessy, Sivananthan Jothee, Sébastien Jacquemin, J. Sammon, C. Cruz, Igor Ferreira, Jill Bell, Hariz Akmal Hosen, Amirul Asraf Askat
This paper illustrates how a typical subsea development (Subsea Production Systems (SPS) and Subsea Umbilicals Risers Flowlines (SURF)) can benefit from an integrated execution model which will significantly improve CAPEX, time to first oil and reduce delivery risk. The PETRONAS Limbayong Deepwater Development offshore Sabah, Malaysia is a successful example of close collaboration between a contractor and operator to leverage integrated contracting models and extended service scope, while maximizing Malaysian participation. Digital platforms for Front End Engineering and Design (FEED) and Configure to Order (CTO) product designs were utilized in combination to assess and establish the optimal field architecture for improved cost and schedule. Adopting an integrated one-stop contract approach (SURF, SPS and Subsea Services) enabled an improved development schedule and reduction in cost and risk normally associated with split-contract interfaces. Digitalization of FEEDs and standardization of product configurations created value for the Limbayong field development, accelerating time to First Oil Date (FOD) as well as securing aggressive long-lead items delivery schedules. The combination of the methods described above provides the required enhancement to a traditional execution approach, ill-suited to current oil and gas economics. This approach is instrumental in making many subsea developments feasible and a preface for accelerated future collaborations.
{"title":"Leveraging an Integrated Execution Model, Digital FEED Platform and Product Standardisation to Improve Project CAPEX","authors":"Antoine Fessy, Sivananthan Jothee, Sébastien Jacquemin, J. Sammon, C. Cruz, Igor Ferreira, Jill Bell, Hariz Akmal Hosen, Amirul Asraf Askat","doi":"10.4043/31583-ms","DOIUrl":"https://doi.org/10.4043/31583-ms","url":null,"abstract":"\u0000 This paper illustrates how a typical subsea development (Subsea Production Systems (SPS) and Subsea Umbilicals Risers Flowlines (SURF)) can benefit from an integrated execution model which will significantly improve CAPEX, time to first oil and reduce delivery risk. The PETRONAS Limbayong Deepwater Development offshore Sabah, Malaysia is a successful example of close collaboration between a contractor and operator to leverage integrated contracting models and extended service scope, while maximizing Malaysian participation.\u0000 Digital platforms for Front End Engineering and Design (FEED) and Configure to Order (CTO) product designs were utilized in combination to assess and establish the optimal field architecture for improved cost and schedule. Adopting an integrated one-stop contract approach (SURF, SPS and Subsea Services) enabled an improved development schedule and reduction in cost and risk normally associated with split-contract interfaces. Digitalization of FEEDs and standardization of product configurations created value for the Limbayong field development, accelerating time to First Oil Date (FOD) as well as securing aggressive long-lead items delivery schedules.\u0000 The combination of the methods described above provides the required enhancement to a traditional execution approach, ill-suited to current oil and gas economics. This approach is instrumental in making many subsea developments feasible and a preface for accelerated future collaborations.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85169401","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}
L. Shi, Wanzhe Yang, Kai Chen, Guojun Yu, Canwei Jin, Lingxiao Ni, B. Jing, Zhendi Hu
Floating wind farms has been a global trend in utilizing offshore wind resources. With the development of floating offshore wind turbine (FOWT), dynamic inter-array cable would be required to connect between floating structures. W shape is a kind of dynamic cable configuration that shape the cable floating in midwater and connect between floating platforms. This paper tends to look into W shape dynamic cable configuration performance in extreme environmental conditions. The sensitivity of buoyancy and cable length is evaluated, which provides information for future development of such kind of configuration.
{"title":"Performance Evaluation of W Shape Dynamic Inter-Array Cable Configuration for Floating Offshore Wind Turbine","authors":"L. Shi, Wanzhe Yang, Kai Chen, Guojun Yu, Canwei Jin, Lingxiao Ni, B. Jing, Zhendi Hu","doi":"10.4043/31344-ms","DOIUrl":"https://doi.org/10.4043/31344-ms","url":null,"abstract":"\u0000 Floating wind farms has been a global trend in utilizing offshore wind resources. With the development of floating offshore wind turbine (FOWT), dynamic inter-array cable would be required to connect between floating structures. W shape is a kind of dynamic cable configuration that shape the cable floating in midwater and connect between floating platforms. This paper tends to look into W shape dynamic cable configuration performance in extreme environmental conditions. The sensitivity of buoyancy and cable length is evaluated, which provides information for future development of such kind of configuration.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85757711","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}
Silpakorn Dachanuwattana, Suwitcha Ratanatanyong, T. Wasanapradit, Pojana Vimolsubsin, Sawin Kulchanyavivat
Real-time sensors are crucial for monitoring electrical submersible pump (ESP) operation. However, manually analyzing the whole data from these sensors is virtually impossible due to its overwhelming volume. Artificial intelligence (AI) is a game-changing tool that can leverage the big data from ESP sensors more efficiently. Coupled with ESP knowledge, AI could reveal insights into ESP behaviors, well performances, and reservoirs dynamics, leading to ESP life extension and better production optimization. In this paper, we present the development and deployment of an AI workflow to enhance ESP surveillance. The workflow is developed in-house using the Python programming language and consists of the following four main modules: Data ingestion – to ingest all ESP-relevant databases Data preprocess – to transform the databases in the format ready for AI modelling AI modelling – to experiment several AI models, e.g., to detect ESP critical events, and predict ESP run life. Deployment – To automatically notify ESP critical events and visualize insight from the AI models The application of a hierarchical clustering algorithm reveals that the ESP run life in our fields are most influenced by gas production. Then, after more than 1000 runs of experiments, we achieve a deep learning model to predict whether an ESP will fail within the next 90 days. We also develop a module to automate nodal analysis as part of the AI workflow. Combining this physics-based model with a data-driven approach, the resulting AI models can accurately detect ESP critical events, such as ESP degradation, imminent gas lock, and sand production. To deploy the AI workflow, we build a dashboard to effectively visualize actionable insights from the AI models on our local server. The workflow sends notifications of ESP critical events to users for prompt troubleshooting actions and collects user feedbacks for improvement of the AI models in the next model development cycle. This paper demonstrates a holistic approach to develop a closed-loop ESP surveillance workflow that integrates the powers of AI, automation, and ESP knowledge including nodal analysis. The AI workflow potentially creates value of several million dollars or higher per year by extending ESP run lives and optimizing production. The lessons learnt from this AI workflow development are shared to assist the development and deploying of similar AI methods throughout the oil and gas industry.
{"title":"The Deployment of Deep Learning Models for Performance Optimization and Failure Prevention of Electric Submersible Pumps","authors":"Silpakorn Dachanuwattana, Suwitcha Ratanatanyong, T. Wasanapradit, Pojana Vimolsubsin, Sawin Kulchanyavivat","doi":"10.4043/31612-ms","DOIUrl":"https://doi.org/10.4043/31612-ms","url":null,"abstract":"\u0000 Real-time sensors are crucial for monitoring electrical submersible pump (ESP) operation. However, manually analyzing the whole data from these sensors is virtually impossible due to its overwhelming volume. Artificial intelligence (AI) is a game-changing tool that can leverage the big data from ESP sensors more efficiently. Coupled with ESP knowledge, AI could reveal insights into ESP behaviors, well performances, and reservoirs dynamics, leading to ESP life extension and better production optimization.\u0000 In this paper, we present the development and deployment of an AI workflow to enhance ESP surveillance. The workflow is developed in-house using the Python programming language and consists of the following four main modules:\u0000 Data ingestion – to ingest all ESP-relevant databases Data preprocess – to transform the databases in the format ready for AI modelling AI modelling – to experiment several AI models, e.g., to detect ESP critical events, and predict ESP run life. Deployment – To automatically notify ESP critical events and visualize insight from the AI models\u0000 The application of a hierarchical clustering algorithm reveals that the ESP run life in our fields are most influenced by gas production. Then, after more than 1000 runs of experiments, we achieve a deep learning model to predict whether an ESP will fail within the next 90 days. We also develop a module to automate nodal analysis as part of the AI workflow. Combining this physics-based model with a data-driven approach, the resulting AI models can accurately detect ESP critical events, such as ESP degradation, imminent gas lock, and sand production.\u0000 To deploy the AI workflow, we build a dashboard to effectively visualize actionable insights from the AI models on our local server. The workflow sends notifications of ESP critical events to users for prompt troubleshooting actions and collects user feedbacks for improvement of the AI models in the next model development cycle.\u0000 This paper demonstrates a holistic approach to develop a closed-loop ESP surveillance workflow that integrates the powers of AI, automation, and ESP knowledge including nodal analysis. The AI workflow potentially creates value of several million dollars or higher per year by extending ESP run lives and optimizing production. The lessons learnt from this AI workflow development are shared to assist the development and deploying of similar AI methods throughout the oil and gas industry.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81173676","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 ocean surface offers enormous potential for generating renewable energy, but cost-effective, reliable, and robust systems are needed. Developing floating solar farms (FSF) can contribute to the process of reducing carbon emissions. However, the rational methodology for hydrodynamic analysis of floating solar farms is still not well established. This paper aims to identify a suitable methodology for the analysis of floating solar farms for mild and moderate environments in nearshore, and eventually deeper offshore deployments. This paper reviews the various type of FSFs developed in recent years and the methodologies applied to evaluate their hydrodynamic performance. Following that, the paper focuses on assessing three potential methodologies for the evaluation of the hydrodynamic performance of articulated FSFs in a nearshore region. The three methods are the two-step approach with multi-body radiation and diffraction analysis, hydroelastic/generalized mode method, and empirical approach utilizing Morison's equation. To evaluate these methods, a simplified small-scale FSF which is comprised of 16 articulated box-type modules, is established. A soft mooring system is introduced to constraint the horizontal motion of the farm. The small-scale farm is representative of a typical large FSF in the nearshore region of Singapore. Numerical models of the farm based on the three methods are established separately, and the dynamic responses of the farm are simulated and analyzed. The motion response operators of the modules of the FSF covering the typical wave periods in nearshore conditions are obtained, and the results from the three methods are evaluated in terms of their efficiency and accuracy. It is found that the three methods show consistent results of the dynamic responses of the solar farm in long waves. However, some discrepancies are present in short waves, mainly due to the increasing importance of hydrodynamic interactions which are neglected in one of these methods. The results could be a useful reference for the design and hydrodynamic analysis of similar FSFs.
{"title":"Review and Comparative Study of Methodologies for Hydrodynamic Analysis of Nearshore Floating Solar Farms","authors":"Chi Zhang, H. Santo, A. Magee","doi":"10.4043/31673-ms","DOIUrl":"https://doi.org/10.4043/31673-ms","url":null,"abstract":"\u0000 The ocean surface offers enormous potential for generating renewable energy, but cost-effective, reliable, and robust systems are needed. Developing floating solar farms (FSF) can contribute to the process of reducing carbon emissions. However, the rational methodology for hydrodynamic analysis of floating solar farms is still not well established. This paper aims to identify a suitable methodology for the analysis of floating solar farms for mild and moderate environments in nearshore, and eventually deeper offshore deployments.\u0000 This paper reviews the various type of FSFs developed in recent years and the methodologies applied to evaluate their hydrodynamic performance. Following that, the paper focuses on assessing three potential methodologies for the evaluation of the hydrodynamic performance of articulated FSFs in a nearshore region. The three methods are the two-step approach with multi-body radiation and diffraction analysis, hydroelastic/generalized mode method, and empirical approach utilizing Morison's equation. To evaluate these methods, a simplified small-scale FSF which is comprised of 16 articulated box-type modules, is established. A soft mooring system is introduced to constraint the horizontal motion of the farm. The small-scale farm is representative of a typical large FSF in the nearshore region of Singapore. Numerical models of the farm based on the three methods are established separately, and the dynamic responses of the farm are simulated and analyzed. The motion response operators of the modules of the FSF covering the typical wave periods in nearshore conditions are obtained, and the results from the three methods are evaluated in terms of their efficiency and accuracy.\u0000 It is found that the three methods show consistent results of the dynamic responses of the solar farm in long waves. However, some discrepancies are present in short waves, mainly due to the increasing importance of hydrodynamic interactions which are neglected in one of these methods. The results could be a useful reference for the design and hydrodynamic analysis of similar FSFs.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74003201","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}
Field-X was first discovered in 1979, comprising of saturated oil reservoirs with several shallower non-associated gas reservoirs. Field-X is currently producing from several oil producers. X8 well was recently drilled, completed, and produce from A and B reservoirs. However, 5 months later, the oil rate has been reduced by half with gas oil ratio (GOR) increased up to 5 times. Consequently, the well had to be shut-in due to reservoir management plan (RMP) violation. X9 well was drilled and completed, but 5 years later the well started experiencing the sustained production casing pressure (PCP) and was forced to shut-in in the following year with the locked-in potential of both A and B reservoirs. To diagnose the root cause of high GOR (HGOR) in X8 well and sustained PCP in X9 well, the Spectral Noise Log (SNL) was deployed. The main advantage of utilizing SNL is its capability of detecting fluid movement behind tubing and casing. High differential pressure creates lots of fluid movement, which generates higher noise amplitude. Meanwhile, smaller pores or leaks generate higher frequency noise that can be easily picked up by SNL. SNL tool was run in flowing condition for X8 well and the results indicated the HGOR zones were mainly contributed by the shallower B05 sand which was flowing through the leaked 4-1/2″ liner packer. Temperature deflections also indicated that the liner packer seal was leaking and B05 reservoir was contributing to the production. The liner packer leak and B05 reservoir flow would not have been detected by conventional production logging tools as the flow was happening beyond the tubing and casing. For X9 well, SNL was run in the wellbore whilst pumping water via annulus, through the leaks and flowing back up the tubing. Three tubing leaks were successfully detected from the SNL run, whereas previous conventional noise log only managed to detect 2 leaks. It is possible that the third small leak was very small, hence the conventional tool was unable to detect it. X8 well successfully back online with 8.4% rate increase than last production with GOR reduced back to initial GOR and X9 well successfully back online as per last production rate. The liner packers which are not permanent barriers for reservoir isolation and allocation can be validated, moreover, verifying that tubing leakage is mainly contributed by tubing joints, which can be used as the main input in tubing materials selection in the future. Well integrity issues can cause significant loss of production, oil spill or worst case, even loss of lives. Proper selection in data acquisition tools helps to accurately diagnose well integrity issues that can be swiftly addressed. In the low oil price environment, skimming down on data acquisition costs may not uncover the true underlying well issues or reservoir issues, but might jeopardize future projects to be undertaken in years to come.
{"title":"Noise Logging Application for Well Integrity Evaluation: A Case Study in Peninsular Malaysia","authors":"L. J. Saw, Hanalim Linda, Tolioe Amelio William","doi":"10.4043/31401-ms","DOIUrl":"https://doi.org/10.4043/31401-ms","url":null,"abstract":"\u0000 \u0000 \u0000 Field-X was first discovered in 1979, comprising of saturated oil reservoirs with several shallower non-associated gas reservoirs. Field-X is currently producing from several oil producers. X8 well was recently drilled, completed, and produce from A and B reservoirs. However, 5 months later, the oil rate has been reduced by half with gas oil ratio (GOR) increased up to 5 times. Consequently, the well had to be shut-in due to reservoir management plan (RMP) violation. X9 well was drilled and completed, but 5 years later the well started experiencing the sustained production casing pressure (PCP) and was forced to shut-in in the following year with the locked-in potential of both A and B reservoirs.\u0000 To diagnose the root cause of high GOR (HGOR) in X8 well and sustained PCP in X9 well, the Spectral Noise Log (SNL) was deployed. The main advantage of utilizing SNL is its capability of detecting fluid movement behind tubing and casing. High differential pressure creates lots of fluid movement, which generates higher noise amplitude. Meanwhile, smaller pores or leaks generate higher frequency noise that can be easily picked up by SNL.\u0000 SNL tool was run in flowing condition for X8 well and the results indicated the HGOR zones were mainly contributed by the shallower B05 sand which was flowing through the leaked 4-1/2″ liner packer. Temperature deflections also indicated that the liner packer seal was leaking and B05 reservoir was contributing to the production. The liner packer leak and B05 reservoir flow would not have been detected by conventional production logging tools as the flow was happening beyond the tubing and casing. For X9 well, SNL was run in the wellbore whilst pumping water via annulus, through the leaks and flowing back up the tubing. Three tubing leaks were successfully detected from the SNL run, whereas previous conventional noise log only managed to detect 2 leaks. It is possible that the third small leak was very small, hence the conventional tool was unable to detect it.\u0000 X8 well successfully back online with 8.4% rate increase than last production with GOR reduced back to initial GOR and X9 well successfully back online as per last production rate. The liner packers which are not permanent barriers for reservoir isolation and allocation can be validated, moreover, verifying that tubing leakage is mainly contributed by tubing joints, which can be used as the main input in tubing materials selection in the future.\u0000 Well integrity issues can cause significant loss of production, oil spill or worst case, even loss of lives. Proper selection in data acquisition tools helps to accurately diagnose well integrity issues that can be swiftly addressed. In the low oil price environment, skimming down on data acquisition costs may not uncover the true underlying well issues or reservoir issues, but might jeopardize future projects to be undertaken in years to come.\u0000","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"248 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73536042","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}
Mutia Kharunisa Mardhatillah, M. A. Md Yusof, A. Sa'id, Iqmal Irsyad Mohammad Fuad, Yen Adams Sokama- Neuyam, Nur Asyraf Md Akhir
Southeast Asia is increasingly gaining attention as a promising geological site for permanent CO2 sequestration in deep saline aquifers. During CO2 injection into saline reservoirs, the reaction between injected CO2, the resident formation brine, and the reservoir rock could cause injectivity change due to salt precipitation, mineral dissolution, and fine particles migration. The underlying mechanisms have been extensively studied, both experimentally and numerically and the governing parameters have been identified and studied. However, the current models that have been widely adopted to investigate reactive transport and its impact on CO2 injectivity have fundamental limitations when applied to solve small, high dimensional, and non-linear data. The objective of this study is to develop efficient and robust predictive models using support vector regression (SVR) integrated with hyperparameter tuning optimization algorithms, including genetic algorithm (GA). To develop the model, 44 datasets are used to predict the CO2 injectivity change with its influencing variables such as brine salinity, injection flow rate, particle size, and particle concentration. The performance for each model is analyzed and compared with previous models by determination of coefficient (R2), adjusted determination of coefficient (R¯2), average absolute percentage error (AAPE), root mean square error (RMSE) and mean absolute error (MAE). The model with the highest R2 is selected as the predictive model for CO2 injectivity impairment during CO2 sequestration in a saline aquifer. The results revealed that both SVR and GA-SVR are able to capture the precise correlation between measured and predicted data. However, the GA-SVR model slightly outperformed the SVR model by a higher R2 value of 0.9923 compared to SVR with R2 value of 0.9918. Based on SHAP value analysis, brine salinity had the highest impact on CO2 injectivity change, followed by injection flow rate, particle concentration, and jamming ratio. It was also found that hybridization of genetic algorithm with support vector regression does improve the model performance contrary to single algorithm and contributes to the determination of the most impactful factors that induce CO2 injectivity change. The proposed model can be upscaled and integrated into field-scale models to improve the optimization of CO2 injectivity in deep saline reservoirs.
{"title":"Predictive Modelling of Carbon Dioxide Injectivity Using SVR-Hybrid","authors":"Mutia Kharunisa Mardhatillah, M. A. Md Yusof, A. Sa'id, Iqmal Irsyad Mohammad Fuad, Yen Adams Sokama- Neuyam, Nur Asyraf Md Akhir","doi":"10.4043/31472-ms","DOIUrl":"https://doi.org/10.4043/31472-ms","url":null,"abstract":"Southeast Asia is increasingly gaining attention as a promising geological site for permanent CO2 sequestration in deep saline aquifers. During CO2 injection into saline reservoirs, the reaction between injected CO2, the resident formation brine, and the reservoir rock could cause injectivity change due to salt precipitation, mineral dissolution, and fine particles migration. The underlying mechanisms have been extensively studied, both experimentally and numerically and the governing parameters have been identified and studied. However, the current models that have been widely adopted to investigate reactive transport and its impact on CO2 injectivity have fundamental limitations when applied to solve small, high dimensional, and non-linear data. The objective of this study is to develop efficient and robust predictive models using support vector regression (SVR) integrated with hyperparameter tuning optimization algorithms, including genetic algorithm (GA). To develop the model, 44 datasets are used to predict the CO2 injectivity change with its influencing variables such as brine salinity, injection flow rate, particle size, and particle concentration. The performance for each model is analyzed and compared with previous models by determination of coefficient (R2), adjusted determination of coefficient (R¯2), average absolute percentage error (AAPE), root mean square error (RMSE) and mean absolute error (MAE). The model with the highest R2 is selected as the predictive model for CO2 injectivity impairment during CO2 sequestration in a saline aquifer. The results revealed that both SVR and GA-SVR are able to capture the precise correlation between measured and predicted data. However, the GA-SVR model slightly outperformed the SVR model by a higher R2 value of 0.9923 compared to SVR with R2 value of 0.9918. Based on SHAP value analysis, brine salinity had the highest impact on CO2 injectivity change, followed by injection flow rate, particle concentration, and jamming ratio. It was also found that hybridization of genetic algorithm with support vector regression does improve the model performance contrary to single algorithm and contributes to the determination of the most impactful factors that induce CO2 injectivity change. The proposed model can be upscaled and integrated into field-scale models to improve the optimization of CO2 injectivity in deep saline reservoirs.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"3 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83479651","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}
Chang Siong Ting, N. Minggu, Dahlila Kamat, Kit Teng Chaw, Chee Seong Tan, Sanggeetha Kalidas, Gladson Joe Barretto
In this paper, we evaluate the effectiveness of production enhancement activities for well B Long-string (i.e. well BL) using distributed temperature sensing (DTS) technology. Installation of permanent fiber-optic cable across the reservoir sections has enabled gas lift monitoring, identification of well integrity issues and zonal inflow profiling from perforation contribution. Recent DTS interpretation indicated leak point at 4,025ft with sub-optimal gas lifting which has resulted in loss of 300 BOPD. Hence, well intervention such as tubing patch and gas lift valve change-out (GLVC) were conducted consecutively to restore its initial production. The effectiveness of executed remedial jobs will be discussed along the findings and interpretations of the temperature survey result from DTS. Well BL is a long-string gas lifted producer that flows from two zones. Prior to the tubing patch, the multi-finger caliper tool was logged in well BL to further validate the leak point indicated by DTS. The caliper logging survey identified that maximum penetration (100%) occurs at 4,025 ft, which classified it as a leak hole. Time-lapsed DTS measurement, specifically; pre-, during-, and post-tubing patch and GLVC were acquired. It is analyzed along with Permanent Downhole Gauge (PDG) data and surface parameters [e.g., tubing head pressure (THP), casing head pressure (CHP), Gas lift injection rate, etc]. The multi-measurement interpretation is further complemented by nodal analysis for a more conclusive finding. A baseline temperature was acquired during the shut-in period as a geothermal gradient reference to determine any anomalies against the temperature acquired during each event. Operation quick-look indicated both GLVC and tubing patch are deemed to be successfully carried out as per the program with minimal workover challenges. However, the executed remedial jobs that are expected to resume the production from Well BL to its initial production shows it is still underperforming. Production rate keeps declining during the post-job execution. Qualitative interpretation from DTS temperature profiles, reveals another significant tubing leak detected at 4,007ft after the tubing patch. By accidental find, the DTS data also showed that the production from top zone (short string) was produced through the leak hole at the long string to surface. Further investigation applying nodal analysis and PDG data indicated that crossflow was observed from the top zone production through and into bottom leak hole at the long string. This has led to serious production loss in well BL. Furthermore, temperature profile that's demonstrated the injected gas was unable to reach the orifice (operating node) due to multi-pointing, thus resulted in the well's underperforming production post-remedial job execution. In this root-cause finding showcase, DTS data have been providing valuable findings on the effectiveness of executed remedial jobs in well BL. DTS measurement and monito
{"title":"Production Enhancement Evaluation via Permanent Fiber Optics Distributed Temperature Sensing Interpretation for a Gas-Lifted Producer in Field B, Offshore Malaysia","authors":"Chang Siong Ting, N. Minggu, Dahlila Kamat, Kit Teng Chaw, Chee Seong Tan, Sanggeetha Kalidas, Gladson Joe Barretto","doi":"10.4043/31654-ms","DOIUrl":"https://doi.org/10.4043/31654-ms","url":null,"abstract":"\u0000 In this paper, we evaluate the effectiveness of production enhancement activities for well B Long-string (i.e. well BL) using distributed temperature sensing (DTS) technology. Installation of permanent fiber-optic cable across the reservoir sections has enabled gas lift monitoring, identification of well integrity issues and zonal inflow profiling from perforation contribution. Recent DTS interpretation indicated leak point at 4,025ft with sub-optimal gas lifting which has resulted in loss of 300 BOPD. Hence, well intervention such as tubing patch and gas lift valve change-out (GLVC) were conducted consecutively to restore its initial production. The effectiveness of executed remedial jobs will be discussed along the findings and interpretations of the temperature survey result from DTS.\u0000 Well BL is a long-string gas lifted producer that flows from two zones. Prior to the tubing patch, the multi-finger caliper tool was logged in well BL to further validate the leak point indicated by DTS. The caliper logging survey identified that maximum penetration (100%) occurs at 4,025 ft, which classified it as a leak hole. Time-lapsed DTS measurement, specifically; pre-, during-, and post-tubing patch and GLVC were acquired. It is analyzed along with Permanent Downhole Gauge (PDG) data and surface parameters [e.g., tubing head pressure (THP), casing head pressure (CHP), Gas lift injection rate, etc]. The multi-measurement interpretation is further complemented by nodal analysis for a more conclusive finding. A baseline temperature was acquired during the shut-in period as a geothermal gradient reference to determine any anomalies against the temperature acquired during each event.\u0000 Operation quick-look indicated both GLVC and tubing patch are deemed to be successfully carried out as per the program with minimal workover challenges. However, the executed remedial jobs that are expected to resume the production from Well BL to its initial production shows it is still underperforming. Production rate keeps declining during the post-job execution. Qualitative interpretation from DTS temperature profiles, reveals another significant tubing leak detected at 4,007ft after the tubing patch. By accidental find, the DTS data also showed that the production from top zone (short string) was produced through the leak hole at the long string to surface. Further investigation applying nodal analysis and PDG data indicated that crossflow was observed from the top zone production through and into bottom leak hole at the long string. This has led to serious production loss in well BL. Furthermore, temperature profile that's demonstrated the injected gas was unable to reach the orifice (operating node) due to multi-pointing, thus resulted in the well's underperforming production post-remedial job execution. In this root-cause finding showcase, DTS data have been providing valuable findings on the effectiveness of executed remedial jobs in well BL. DTS measurement and monito","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89965500","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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