M. Ryan, Brian Unietis, A. Kaverzin, Travys Townson, James Steves, C. Chew, Mark Maggard, Justin Jones, Brendan R. McGehee, K. Minnaar
The Liza Phase 1 development project features the Liza Destiny Floating Production, Storage, and Offloading (FPSO) vessel, moored 190 km offshore Guyana in 1,743 m (5,719 ft) of water, and four subsea drill centers supporting 17 wells. Not only was this a Greenfield development that required an integrated team to prepare for Operations; it was also located in a New Frontier that required development of logistics and marine infrastructure to support multi drillship and FPSO operations in challenging metocean and tidal conditions. In addition, early operations and production testing was further complicated by the COVID-19 pandemic and safety protocols put in place to keep the workforce safe. Three aspects of achieving First Oil are discussed, highlighting challenges and lessons learned: Managing subsea completions, well cleanup, and flow assurance while drilling was ongoing Enabling accurate data collection from Multi-Phase Flow Meters (MPFMs) and downhole pressure gauges, which was critical to developing foundational understanding of well performance for reservoir characterization and management Establishing an integrated asset team and workflows to ensure life cycle value capture by managing complex marine operations, commissioning, and surveillance while meeting stringent COVID-19 protocols Lessons learned from Destiny Operations will be incorporated into future projects, including a robust digital strategy centered on a fiber ring to shore, which will enable high-speed communications for future FPSOs, and an onshore integrated operations control center for improvement of long-term operations. Early understanding of reservoir connectivity and performance from data collection will continue to inform the reservoir management strategy so as to maximize asset value for the country of Guyana.
{"title":"Guyana Operations and First Oil","authors":"M. Ryan, Brian Unietis, A. Kaverzin, Travys Townson, James Steves, C. Chew, Mark Maggard, Justin Jones, Brendan R. McGehee, K. Minnaar","doi":"10.4043/30979-ms","DOIUrl":"https://doi.org/10.4043/30979-ms","url":null,"abstract":"\u0000 The Liza Phase 1 development project features the Liza Destiny Floating Production, Storage, and Offloading (FPSO) vessel, moored 190 km offshore Guyana in 1,743 m (5,719 ft) of water, and four subsea drill centers supporting 17 wells. Not only was this a Greenfield development that required an integrated team to prepare for Operations; it was also located in a New Frontier that required development of logistics and marine infrastructure to support multi drillship and FPSO operations in challenging metocean and tidal conditions. In addition, early operations and production testing was further complicated by the COVID-19 pandemic and safety protocols put in place to keep the workforce safe.\u0000 Three aspects of achieving First Oil are discussed, highlighting challenges and lessons learned:\u0000 Managing subsea completions, well cleanup, and flow assurance while drilling was ongoing Enabling accurate data collection from Multi-Phase Flow Meters (MPFMs) and downhole pressure gauges, which was critical to developing foundational understanding of well performance for reservoir characterization and management Establishing an integrated asset team and workflows to ensure life cycle value capture by managing complex marine operations, commissioning, and surveillance while meeting stringent COVID-19 protocols\u0000 Lessons learned from Destiny Operations will be incorporated into future projects, including a robust digital strategy centered on a fiber ring to shore, which will enable high-speed communications for future FPSOs, and an onshore integrated operations control center for improvement of long-term operations. Early understanding of reservoir connectivity and performance from data collection will continue to inform the reservoir management strategy so as to maximize asset value for the country of Guyana.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84841530","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}
C. Geertsen, S. Langford, C. Mckinnon, Fred McKinnon, V. Niesen, Frederico Orberg, Nick Wang
The project was a 2km, electrically heat-traced, subsea pipe-in-pipe (PIP) system for transportation of a bitumen-like material across a shipping channel. Due to the viscosity of the bitumen, it must be transported at a minimum of 160°C; has a normal pipeline operating temperature of 200°C; and a design temperature is 228°C. Due to the high operating temperature, pre-stressing and backfilling the PIP was required to lock in stresses at an intermediate pre-stressing temperature. The electrical heat-trace wires (installed to heat up the inner pipe and prevent setting of the bitumen during cooldowns) were used to achieve this pre-stressing during the fabrication process. The heating schedule causes high stress levels and require advanced engineering analyses to model the behaviour of the inner and outer pipe during the fabrication, installation, pre-stressing, and operation. The complex loading history of the inner pipe and the expansion spools was included in the global 3D, finite element (FE) models that were used to validate the pipeline profile, backfilling, pre-stressing temperature, and sequence of operations. The complex buckling behaviour of the inner pipe is presented and shown to be within DNV GL OS-F- 101 code limits. The end expansion during the various stages of pre-stressing is presented and compared to observed behaviour. The loads and stresses in the bulkheads are presented and shown to be acceptable. The analysis demonstrates that the pipeline system can be safely installed and operated up to the maximum design temperature of 228°C. The project used pre-stressing by heating the inner pipe to an intermediate temperature before coupling the inner pipe to the outer pipe. The purpose of the pre-stressing was to manage the high axial stresses making it feasible to achieve the high design temperature of 228°C. Pre-expanding of the expansion spools at either end of the subsea pipelines was also used due to the space limitations. Innovative engineering analysis and construction methods were used to ensure the integrity of the inner pipe during the pre-stressing process and operation.
{"title":"Challenges of Engineering the Hottest Subsea Heated Pipeline for the CRISP Project","authors":"C. Geertsen, S. Langford, C. Mckinnon, Fred McKinnon, V. Niesen, Frederico Orberg, Nick Wang","doi":"10.4043/31188-ms","DOIUrl":"https://doi.org/10.4043/31188-ms","url":null,"abstract":"\u0000 \u0000 \u0000 The project was a 2km, electrically heat-traced, subsea pipe-in-pipe (PIP) system for transportation of a bitumen-like material across a shipping channel. Due to the viscosity of the bitumen, it must be transported at a minimum of 160°C; has a normal pipeline operating temperature of 200°C; and a design temperature is 228°C.\u0000 \u0000 \u0000 \u0000 Due to the high operating temperature, pre-stressing and backfilling the PIP was required to lock in stresses at an intermediate pre-stressing temperature. The electrical heat-trace wires (installed to heat up the inner pipe and prevent setting of the bitumen during cooldowns) were used to achieve this pre-stressing during the fabrication process. The heating schedule causes high stress levels and require advanced engineering analyses to model the behaviour of the inner and outer pipe during the fabrication, installation, pre-stressing, and operation. The complex loading history of the inner pipe and the expansion spools was included in the global 3D, finite element (FE) models that were used to validate the pipeline profile, backfilling, pre-stressing temperature, and sequence of operations.\u0000 \u0000 \u0000 \u0000 The complex buckling behaviour of the inner pipe is presented and shown to be within DNV GL OS-F- 101 code limits. The end expansion during the various stages of pre-stressing is presented and compared to observed behaviour. The loads and stresses in the bulkheads are presented and shown to be acceptable. The analysis demonstrates that the pipeline system can be safely installed and operated up to the maximum design temperature of 228°C.\u0000 \u0000 \u0000 \u0000 The project used pre-stressing by heating the inner pipe to an intermediate temperature before coupling the inner pipe to the outer pipe. The purpose of the pre-stressing was to manage the high axial stresses making it feasible to achieve the high design temperature of 228°C. Pre-expanding of the expansion spools at either end of the subsea pipelines was also used due to the space limitations. Innovative engineering analysis and construction methods were used to ensure the integrity of the inner pipe during the pre-stressing process and operation.\u0000","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81788304","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 natural gas hydrate, plentifully distributed in ocean floor sediments and permafrost regions, is considered a promising unconventional energy resource. The investigation of hydrate dissociation mechanisms in porous media is essential to optimize current production methods. To provide a microscopic insight in the hydrate dissociation process, we developed a Lattice Boltzmann (LB) model to investigate this multi–physicochemical process, including mass transfer, conjugate heat transfer, and gas transport. The methane hydrate dissociation is regarded as the reactive transport process coupled with heat transfer. The methane transport in porous media is modelled by the generalized LB method with the Bhatnagar-Gross-Krook (BGK) collision model. The mass transfer from hydrate to fluid phase is described by the hydrate kinetic and thermodynamic models. Finally, the conjugate heat transfer LB-model for heterogeneous media is added for solving the energy equation. In the numerical experiments, we primarily investigated the effects of different hydrate distribution morphologies such as pore–filling, grain–coating, and dispersed on the hydrate dissociation process. From simulations, we found that in general, the dissociation rate and the methane average density rapidly approached the maximum value and then decreased with fluctuation during the dissociation process. This trend is due to that the endothermic reaction heat decreased the temperature, resulting in decelerating the dissociation. The average temperature decreased to minimum value instantaneously as hydrate started to dissociate. After the minimum value, the average temperature would increase slowly, accompanied by the thermal stimulation and hydrate consumption, displaying a valley shape of the temperature curve. We also found that the whole dissociation process and permeability–saturation relations are significantly affected by the hydrate morphologies. Under the same hydrate saturation, the dispersed case dissolves the fastest, whereas the grain–coating case is the slowest. Furthermore, we proposed a general permeability–saturation relation applicable for three cases, filling the gap in the current relative permeability models. The LB model proposed in this study is capable to simulate the complex physicochemical hydrate dissociation process. Considering the impacts of thermodynamic conditions (P,T), we investigated their influences on the coupled interaction between dissociation and seepage under three different morphologies and proposed a general permeability–saturation relationship. The results can be applied as input to adjust parameters in the continuum model, and provide instructions for exploring clean energy with environmental considerations.
{"title":"Pore–Scale Study of Effects of Hydrate Morphologies on Dissociation Evolutions Using Lattice–Boltzmann Method","authors":"Zhuoran Li, G. Qin","doi":"10.4043/31067-ms","DOIUrl":"https://doi.org/10.4043/31067-ms","url":null,"abstract":"\u0000 The natural gas hydrate, plentifully distributed in ocean floor sediments and permafrost regions, is considered a promising unconventional energy resource. The investigation of hydrate dissociation mechanisms in porous media is essential to optimize current production methods. To provide a microscopic insight in the hydrate dissociation process, we developed a Lattice Boltzmann (LB) model to investigate this multi–physicochemical process, including mass transfer, conjugate heat transfer, and gas transport. The methane hydrate dissociation is regarded as the reactive transport process coupled with heat transfer. The methane transport in porous media is modelled by the generalized LB method with the Bhatnagar-Gross-Krook (BGK) collision model. The mass transfer from hydrate to fluid phase is described by the hydrate kinetic and thermodynamic models. Finally, the conjugate heat transfer LB-model for heterogeneous media is added for solving the energy equation.\u0000 In the numerical experiments, we primarily investigated the effects of different hydrate distribution morphologies such as pore–filling, grain–coating, and dispersed on the hydrate dissociation process. From simulations, we found that in general, the dissociation rate and the methane average density rapidly approached the maximum value and then decreased with fluctuation during the dissociation process. This trend is due to that the endothermic reaction heat decreased the temperature, resulting in decelerating the dissociation. The average temperature decreased to minimum value instantaneously as hydrate started to dissociate. After the minimum value, the average temperature would increase slowly, accompanied by the thermal stimulation and hydrate consumption, displaying a valley shape of the temperature curve. We also found that the whole dissociation process and permeability–saturation relations are significantly affected by the hydrate morphologies. Under the same hydrate saturation, the dispersed case dissolves the fastest, whereas the grain–coating case is the slowest. Furthermore, we proposed a general permeability–saturation relation applicable for three cases, filling the gap in the current relative permeability models. The LB model proposed in this study is capable to simulate the complex physicochemical hydrate dissociation process. Considering the impacts of thermodynamic conditions (P,T), we investigated their influences on the coupled interaction between dissociation and seepage under three different morphologies and proposed a general permeability–saturation relationship. The results can be applied as input to adjust parameters in the continuum model, and provide instructions for exploring clean energy with environmental considerations.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76870920","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}
Kinetic Pressure Control has developed the 18 ¾" 15000 psi blowout stopper (KBOS) system for applications on all subsea well activities. The 18 ¾" 15000 psi systems builds upon the successful development of the 5-1/8" 15000 psi KBOS system for surface BOP applications[5]. The system can be configured within the existing subsea BOP, by replacing a casing shear ram or blind shear ram, or can be configured as a shut-in device below the BOP. The KBOS system provides a significant improvement over existing shear ram technology, providing the ability to shear/seal any items in the wellbore, which reduces the likelihood of a blowout, resulting in an improved risk profile. The KBOS is a proprietary design which uses a pyro-technical, electrically initiated process the actuate the shearing process. The system has been designed and tested to actuate and shear/seal in milliseconds, under full wellbore flowing conditions and meets NACE/ISO sour service requirements without exemptions. The control system includes real-time monitoring and function testing capabilities, and requires minimal in-service maintenance, as the working components are isolated from the wellbore fluids. A computational predictive model has been developed, with a test regime conducted to validate the model results. A full qualification program, with 3rd party certification, has been completed to industry standards. Shearing tests have been conducted for a large range of tubulars which have been challenging to shear with existing technology. These include: 9 ½" drill collars, combinations of large OD casing and inner strings, high strength drill pipe and tool joints, wireline, and production tubing. A subsea test of the system was successfully performed in 2019 to shear large OD casing and inner string. The KBOS system utilizes technology from other industries (ballistics, military, automotive) to provide improved shearing and sealing capabilities for all well activities (drilling, completion, intervention). The improved shearing/sealing capacity and reduced time enable a reduced likelihood of a blowout and improved risk profile
{"title":"18 3/4\" 15000 Psi Shear Anything KBOS for Subsea Well Applications","authors":"B. J. Gallagher, K. Dupal, R. Jones","doi":"10.4043/31048-ms","DOIUrl":"https://doi.org/10.4043/31048-ms","url":null,"abstract":"\u0000 Kinetic Pressure Control has developed the 18 ¾\" 15000 psi blowout stopper (KBOS) system for applications on all subsea well activities. The 18 ¾\" 15000 psi systems builds upon the successful development of the 5-1/8\" 15000 psi KBOS system for surface BOP applications[5]. The system can be configured within the existing subsea BOP, by replacing a casing shear ram or blind shear ram, or can be configured as a shut-in device below the BOP. The KBOS system provides a significant improvement over existing shear ram technology, providing the ability to shear/seal any items in the wellbore, which reduces the likelihood of a blowout, resulting in an improved risk profile.\u0000 The KBOS is a proprietary design which uses a pyro-technical, electrically initiated process the actuate the shearing process. The system has been designed and tested to actuate and shear/seal in milliseconds, under full wellbore flowing conditions and meets NACE/ISO sour service requirements without exemptions. The control system includes real-time monitoring and function testing capabilities, and requires minimal in-service maintenance, as the working components are isolated from the wellbore fluids. A computational predictive model has been developed, with a test regime conducted to validate the model results. A full qualification program, with 3rd party certification, has been completed to industry standards.\u0000 Shearing tests have been conducted for a large range of tubulars which have been challenging to shear with existing technology. These include: 9 ½\" drill collars, combinations of large OD casing and inner strings, high strength drill pipe and tool joints, wireline, and production tubing. A subsea test of the system was successfully performed in 2019 to shear large OD casing and inner string.\u0000 The KBOS system utilizes technology from other industries (ballistics, military, automotive) to provide improved shearing and sealing capabilities for all well activities (drilling, completion, intervention). The improved shearing/sealing capacity and reduced time enable a reduced likelihood of a blowout and improved risk profile","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"106 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81140707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the oil and gas exploration process, understanding the hydrocarbon distribution of a reservoir is important. Well-log and core sample data such as porosity and water saturation are widely used for this purpose. With porosity and water saturation, we can calculate hydrocarbon volume more accurately than using well-log solely. However, as obtaining core sample data is expensive and time-consuming, predicting it with well-log can be a valuable solution for early-stage exploration since acquiring well-log is relatively economic and swift. Recently, numerous studies applied machine learning algorithms to predict core data from well-log. To the best of our knowledge, most works provide point estimation without probabilistic distribution modeling. In this paper, we developed a probabilistic deep neural network to provide uncertainty via confidence interval. Besides, we employed normalizing flows and multi-task learning to improve prediction accuracy. With this approach, we present the model's uncertainty that can be reliable information for decision making. Furthermore, we demonstrate our model outperforms other supervised machine learning algorithms regards to prediction accuracy.
{"title":"Predicting Porosity and Water Saturation from Well-Log Data Using Probabilistic Multi-Task Neural Network with Normalizing Flows","authors":"Jinwoo Lee, M. Kwon, Youngjun Hong","doi":"10.4043/31085-ms","DOIUrl":"https://doi.org/10.4043/31085-ms","url":null,"abstract":"\u0000 In the oil and gas exploration process, understanding the hydrocarbon distribution of a reservoir is important. Well-log and core sample data such as porosity and water saturation are widely used for this purpose. With porosity and water saturation, we can calculate hydrocarbon volume more accurately than using well-log solely.\u0000 However, as obtaining core sample data is expensive and time-consuming, predicting it with well-log can be a valuable solution for early-stage exploration since acquiring well-log is relatively economic and swift. Recently, numerous studies applied machine learning algorithms to predict core data from well-log. To the best of our knowledge, most works provide point estimation without probabilistic distribution modeling.\u0000 In this paper, we developed a probabilistic deep neural network to provide uncertainty via confidence interval. Besides, we employed normalizing flows and multi-task learning to improve prediction accuracy. With this approach, we present the model's uncertainty that can be reliable information for decision making. Furthermore, we demonstrate our model outperforms other supervised machine learning algorithms regards to prediction accuracy.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"275 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80111263","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}
Syafiq Effendi Jalis, Intiran Raman, Al Ashraf Zharif Al Bakri, Anwaruddin Saidu Mohamed, Kumanan Sanmugam, M. F. Samsudin
In a deep water well completed with coil tubing gas lift (CTGL), significant threat on flow assurance issues has been identified due to the Joule-Thompson effect generated from the high differential pressure of the supplied gas at 3400psi with the required pressure in the well which is below 1500psi. Several wells which have low liquid rate flowing colder with the CTGL due to the Joule Thompson-effect elevated the risk of hydrate formation. Monitoring of Wellhead Temperature (WHT) alone can be a challenge since WHT is below ambient and indication of WHT increase can be interpreted as either as an increase in liquid rate or well quit flowing. The paper describes operator experience in developing an effective flow assurance scheme for prevention and treatment should the well experience hydrate related plugging and devises a strategy for contingencies and remedial actions to reactivate wells effectively without significant production deferment. A holistic approach to manage flow assurance issues in below ambient WHT deep-water dry tree wells completed with CTGL was designed, undertaken, and proven effective. Thorough investigation to analyze the root cause of the blockages along the production tubing was conducted. Several intervention options were considered with very limited clearance for the type of intervention can be conducted in the wells of concern. Decision was made to proceed with the bull-heading method via the CTGL as it was found to be the most cost efficient and quick solution. Preventive measures were then taken to avoid similar future events from happening. Three deep-water dry tree wells which was completed with CTGL were experiencing blockages in the production tubing during an unplanned shutdown. The total potential of these wells amounts to 2600bopd and warranted the team to investigate a quick solution before attempting a workover which is costly and requires longer duration for planning before execution. Two out of the three wells treated with exothermic chemical injection were successful and restored 2000bopd production. Pre-qualification testing demonstrated similar trends of pressure communication between CTGL and tubing head pressure (THP) on the successful well treatment. Chemical solution which produced heat by exothermic reaction was bullheaded into the well with immediate communication established after injection. A standard operating procedure was then developed to manage the wells under this category and prevent future blockage. Culmination of the unique approach for wells with slim tubing (CTGL) to resolve a problem should be looked at from various angles. Investigation must be conducted until the flow restriction root-cause has been identified. Preventive measures then can be taken to avoid similar occurrence which will minimize value leakages and economic impact to the field. De-risking via conducting pre-qualification and Design of Experiment based on scenarios prior to arriving at solution helps to increase c
{"title":"Managing Flow Assurance Challenges in Below Ambient Well Head Temperature WHT Deep-Water Dry Tree Wells","authors":"Syafiq Effendi Jalis, Intiran Raman, Al Ashraf Zharif Al Bakri, Anwaruddin Saidu Mohamed, Kumanan Sanmugam, M. F. Samsudin","doi":"10.4043/31147-ms","DOIUrl":"https://doi.org/10.4043/31147-ms","url":null,"abstract":"\u0000 In a deep water well completed with coil tubing gas lift (CTGL), significant threat on flow assurance issues has been identified due to the Joule-Thompson effect generated from the high differential pressure of the supplied gas at 3400psi with the required pressure in the well which is below 1500psi. Several wells which have low liquid rate flowing colder with the CTGL due to the Joule Thompson-effect elevated the risk of hydrate formation. Monitoring of Wellhead Temperature (WHT) alone can be a challenge since WHT is below ambient and indication of WHT increase can be interpreted as either as an increase in liquid rate or well quit flowing. The paper describes operator experience in developing an effective flow assurance scheme for prevention and treatment should the well experience hydrate related plugging and devises a strategy for contingencies and remedial actions to reactivate wells effectively without significant production deferment.\u0000 A holistic approach to manage flow assurance issues in below ambient WHT deep-water dry tree wells completed with CTGL was designed, undertaken, and proven effective. Thorough investigation to analyze the root cause of the blockages along the production tubing was conducted. Several intervention options were considered with very limited clearance for the type of intervention can be conducted in the wells of concern. Decision was made to proceed with the bull-heading method via the CTGL as it was found to be the most cost efficient and quick solution. Preventive measures were then taken to avoid similar future events from happening.\u0000 Three deep-water dry tree wells which was completed with CTGL were experiencing blockages in the production tubing during an unplanned shutdown. The total potential of these wells amounts to 2600bopd and warranted the team to investigate a quick solution before attempting a workover which is costly and requires longer duration for planning before execution. Two out of the three wells treated with exothermic chemical injection were successful and restored 2000bopd production. Pre-qualification testing demonstrated similar trends of pressure communication between CTGL and tubing head pressure (THP) on the successful well treatment. Chemical solution which produced heat by exothermic reaction was bullheaded into the well with immediate communication established after injection. A standard operating procedure was then developed to manage the wells under this category and prevent future blockage.\u0000 Culmination of the unique approach for wells with slim tubing (CTGL) to resolve a problem should be looked at from various angles. Investigation must be conducted until the flow restriction root-cause has been identified. Preventive measures then can be taken to avoid similar occurrence which will minimize value leakages and economic impact to the field. De-risking via conducting pre-qualification and Design of Experiment based on scenarios prior to arriving at solution helps to increase c","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80284317","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 construction of the A-2 well is considered challenging because it is a horizontal offshore HPHT well in shallow water. In fact, the well had a programmed target to reach the carbonatic rocks of the Upper Jurassic Kimmerdgian age, a light oil producing reservoir of complex type and low porosity, consequently, to select the best intervals with oil presence and define the location of water–oil contact was vital to avoid unnecessary deepening saving additional costs. Being the data interpretation of the geochemical profile in the JSK zone of main importance for reservoir characterization, allowing to determine prospective intervals in a timely manner as a key task. The information from the lithological description was integrated into the geochemical profiles, where intervals of interest are related to hydrocarbon impregnations, fluorescence and visual porosity of each one of the samples.
a -2井的施工被认为是具有挑战性的，因为它是一口浅水的水平海上高温高压井。事实上，该井的规划目标是到达上侏罗统Kimmerdgian时代的碳酸盐岩，这是一种复杂类型和低孔隙度的轻质油油藏，因此，选择存在油的最佳层段并确定水-油接触层的位置至关重要，以避免不必要的加深，节省额外的成本。JSK地区地球化学剖面的数据解释对储层描述具有重要意义，可以及时确定远景层段，这是一项关键任务。来自岩性描述的信息被整合到地球化学剖面中，其中感兴趣的间隔与每个样品的碳氢化合物浸渍、荧光和视觉孔隙度有关。
{"title":"Characterization of Productive Zones with Data from Advanced Mass Spectrometry of HPHT Well","authors":"Veronica Barrera, Jeimy Mathison, F. Flores","doi":"10.4043/31138-ms","DOIUrl":"https://doi.org/10.4043/31138-ms","url":null,"abstract":"\u0000 The construction of the A-2 well is considered challenging because it is a horizontal offshore HPHT well in shallow water. In fact, the well had a programmed target to reach the carbonatic rocks of the Upper Jurassic Kimmerdgian age, a light oil producing reservoir of complex type and low porosity, consequently, to select the best intervals with oil presence and define the location of water–oil contact was vital to avoid unnecessary deepening saving additional costs.\u0000 Being the data interpretation of the geochemical profile in the JSK zone of main importance for reservoir characterization, allowing to determine prospective intervals in a timely manner as a key task. The information from the lithological description was integrated into the geochemical profiles, where intervals of interest are related to hydrocarbon impregnations, fluorescence and visual porosity of each one of the samples.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81607420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In May 2015, Liza-1 encountered more than 90 m (295 ft) of high-quality oil-bearing Upper Cretaceous deepwater sandstones. Immediately, the >1 billion barrel Liza field began on its path from discovery to development. Following the Liza-1 discovery, ExxonMobil and the Stabroek Block co-venturers, Hess Guyana Exploration Limited and CNOOC Petroleum Guyana Limited, undertook a blockwide 3D seismic survey, the largest performed by ExxonMobil at that time, to better delineate the resource potential. Subsequent appraisal drilling built confidence in the performance and connectivity of the reservoir while providing calibration data to inform the development. The initial appraisal well was the "inverted-Y" Liza-2 drilled in early 2016, which comprised an original hole and a sidetrack. A comprehensive evaluation program was implemented with conventional coring of both the original hole and the sidetrack to provide reservoir calibration critical to field development. Furthermore, a production well test was performed on the Liza-2 sidetrack to build confidence in dynamic performance and connectivity assumptions. The Liza-3 appraisal was then drilled down dip of the Liza-1 and −2 to confirm static connectivity across the field. A scenario modeling and simulation approach was implemented at Liza to capture the full range of plausible realizations that could represent the field. The scenarios were measured against the incoming data (Liza-2 and Liza-3) when acquired, and scenarios with greater alignment to the data continued to be pursued while others were moved to a much lower probability of occurrence. This multi-scenario approach was utilized to develop an integrated reservoir model that allowed for depletion plan optimization across a range of subsurface scenarios within flow assurance constraints, ultimately supporting the final investment decision (FID) for the Liza Phase 1 project in 2017, just 25 months after the Liza-1 discovery. Following FID, advanced, proprietary Full Wavefield Inversion seismic reprocessing and high resolution 4D baseline seismic acquisition and processing have been utilized to enable continued optimization. The path from discovery to development culminated in December 2019 with the commencement of production from Liza Phase 1 less than 5 years after the first deepwater oil discovery in Guyana.
{"title":"The Liza Field: From Discovery to Development","authors":"N. Austin, Mita Das, A. Oyerinde, E. Elkington","doi":"10.4043/31084-ms","DOIUrl":"https://doi.org/10.4043/31084-ms","url":null,"abstract":"\u0000 In May 2015, Liza-1 encountered more than 90 m (295 ft) of high-quality oil-bearing Upper Cretaceous deepwater sandstones. Immediately, the >1 billion barrel Liza field began on its path from discovery to development.\u0000 Following the Liza-1 discovery, ExxonMobil and the Stabroek Block co-venturers, Hess Guyana Exploration Limited and CNOOC Petroleum Guyana Limited, undertook a blockwide 3D seismic survey, the largest performed by ExxonMobil at that time, to better delineate the resource potential. Subsequent appraisal drilling built confidence in the performance and connectivity of the reservoir while providing calibration data to inform the development. The initial appraisal well was the \"inverted-Y\" Liza-2 drilled in early 2016, which comprised an original hole and a sidetrack. A comprehensive evaluation program was implemented with conventional coring of both the original hole and the sidetrack to provide reservoir calibration critical to field development. Furthermore, a production well test was performed on the Liza-2 sidetrack to build confidence in dynamic performance and connectivity assumptions. The Liza-3 appraisal was then drilled down dip of the Liza-1 and −2 to confirm static connectivity across the field.\u0000 A scenario modeling and simulation approach was implemented at Liza to capture the full range of plausible realizations that could represent the field. The scenarios were measured against the incoming data (Liza-2 and Liza-3) when acquired, and scenarios with greater alignment to the data continued to be pursued while others were moved to a much lower probability of occurrence. This multi-scenario approach was utilized to develop an integrated reservoir model that allowed for depletion plan optimization across a range of subsurface scenarios within flow assurance constraints, ultimately supporting the final investment decision (FID) for the Liza Phase 1 project in 2017, just 25 months after the Liza-1 discovery.\u0000 Following FID, advanced, proprietary Full Wavefield Inversion seismic reprocessing and high resolution 4D baseline seismic acquisition and processing have been utilized to enable continued optimization. The path from discovery to development culminated in December 2019 with the commencement of production from Liza Phase 1 less than 5 years after the first deepwater oil discovery in Guyana.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82891625","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}
Wei Chen, Alexandre Cachinhasky, Chad Yates, M. Anisimov, John Speights, James L. Overstreet, A. Avagliano
Tungsten carbide hardfacing offers superior wear resistance in a wide range of oil and gas applications. However, for designs of complex geometries, trade-offs often need to be made between manufacturing robustness and service lifecycle based on limited choices of conventional deposition processes. An additive manufacturing (AM) functionally graded tungsten carbide using laser directed energy deposition (L-DED) is developed in an integrated numerically controlled multi-axis machining center with multi-material feeding capability. Essential process parameters are optimized using design of experiment (DOE). Graded structure is shown to reduce crack density. Erosion performance of the L-DED tungsten carbide is on par with commercial high velocity air fueled (HVAF) tungsten carbide coating. The study demonstrates that L-DED-based graded material strategy can significantly improve the robustness of the fabrication process and the expected service reliability. It opens up opportunities involving other hard materials, transition materials, grading strategy by thickness and/or by location.
{"title":"A Case Study for Graded Material Development","authors":"Wei Chen, Alexandre Cachinhasky, Chad Yates, M. Anisimov, John Speights, James L. Overstreet, A. Avagliano","doi":"10.4043/31065-ms","DOIUrl":"https://doi.org/10.4043/31065-ms","url":null,"abstract":"\u0000 Tungsten carbide hardfacing offers superior wear resistance in a wide range of oil and gas applications. However, for designs of complex geometries, trade-offs often need to be made between manufacturing robustness and service lifecycle based on limited choices of conventional deposition processes. An additive manufacturing (AM) functionally graded tungsten carbide using laser directed energy deposition (L-DED) is developed in an integrated numerically controlled multi-axis machining center with multi-material feeding capability. Essential process parameters are optimized using design of experiment (DOE). Graded structure is shown to reduce crack density. Erosion performance of the L-DED tungsten carbide is on par with commercial high velocity air fueled (HVAF) tungsten carbide coating. The study demonstrates that L-DED-based graded material strategy can significantly improve the robustness of the fabrication process and the expected service reliability. It opens up opportunities involving other hard materials, transition materials, grading strategy by thickness and/or by location.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83105562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reservoir characterization is an ambitious challenge that aims to predict variations within the subsurface using fit-for-purpose information that follows physical and geological sense. To properly achieve subsurface characterization, artificial intelligence (AI) algorithms may be used. Machine learning, a subset of AI, is a data-driven approach that has exploded in popularity during the past decades in industries such as healthcare, banking and finance, cryptocurrency, data security, and e-commerce. An advantage of machine learning methods is that they can be implemented to produce results without the need to have first established a complete theoretical scientific model for a problem – with a set of complex model equations to be solved analytically or numerically. The principal challenge of machine learning lies in attaining enough training information, which is essential in obtaining an adequate model that allows for a prediction with a high level of accuracy. Ensemble machine learning in reservoir characterization studies is a candidate to reduce subsurface uncertainty by integrating seismic and well data. In this article, a bootstrap aggregating algorithm is evaluated to determine its potential as a subsurface discriminator. The algorithm fits decision trees on various sub-samples of a dataset and uses averaging to improve the accuracy of the prediction without over-fitting. The gamma ray results from our test dataset show a high correlation with the measured logs, giving confidence in our workflow applied to subsurface characterization.
{"title":"Subsurface Characterization Using Ensemble Machine Learning","authors":"G. G. Leiceaga, R. Balch, G. El-kaseeh","doi":"10.4043/31061-ms","DOIUrl":"https://doi.org/10.4043/31061-ms","url":null,"abstract":"\u0000 Reservoir characterization is an ambitious challenge that aims to predict variations within the subsurface using fit-for-purpose information that follows physical and geological sense. To properly achieve subsurface characterization, artificial intelligence (AI) algorithms may be used. Machine learning, a subset of AI, is a data-driven approach that has exploded in popularity during the past decades in industries such as healthcare, banking and finance, cryptocurrency, data security, and e-commerce. An advantage of machine learning methods is that they can be implemented to produce results without the need to have first established a complete theoretical scientific model for a problem – with a set of complex model equations to be solved analytically or numerically. The principal challenge of machine learning lies in attaining enough training information, which is essential in obtaining an adequate model that allows for a prediction with a high level of accuracy. Ensemble machine learning in reservoir characterization studies is a candidate to reduce subsurface uncertainty by integrating seismic and well data. In this article, a bootstrap aggregating algorithm is evaluated to determine its potential as a subsurface discriminator. The algorithm fits decision trees on various sub-samples of a dataset and uses averaging to improve the accuracy of the prediction without over-fitting. The gamma ray results from our test dataset show a high correlation with the measured logs, giving confidence in our workflow applied to subsurface characterization.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85854487","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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