The main characteristic of the complicated carbonate reservoirs is notably strong heterogeneity, leading to a high uncertainty in formation parameter evaluation [1,2]. In general, logging, core analysis and pressure transient analysis (PTA) are used to evaluate the reservoir parameters of carbonate rocks. However, core and logging analysis can be used to get static parameters in the range of centimeter to meter, while PTA can obtain static and dynamic parameters in the range of hundreds of meters to several kilometers, such as skin coefficient, boundary conditions, permeability and cross flow coefficient. Therefore, the PTA results are more practical and reliable. However, the well test curve shows similar characteristics for multi-layers reservoirs, dual-medium reservoirs, and carbonate reservoirs with lithology mixed sedimentation lithology [3,4]. It is important to reduce the parameter evaluation multiplicity. However, many scholars did not consider the multiplicity of PTA interpretation in practical application, which led to large errors in the results [5,7]. Therefore, this paper comprehensively summarizes all the reasons leading to the depression of pressure derivative curve, and puts forward the corresponding identification approach, which has been applied in Abu Ghirab reservoir well test interpretation and created conditions for improving the accuracy of PTA.
{"title":"Integrated Well Test Interpretation Approach for Complicated Carbonate Reservoirs: A Field Case","authors":"Yongjie Liu, Zhaobo Sun, Renfeng Yang","doi":"10.4043/31528-ms","DOIUrl":"https://doi.org/10.4043/31528-ms","url":null,"abstract":"\u0000 The main characteristic of the complicated carbonate reservoirs is notably strong heterogeneity, leading to a high uncertainty in formation parameter evaluation [1,2]. In general, logging, core analysis and pressure transient analysis (PTA) are used to evaluate the reservoir parameters of carbonate rocks. However, core and logging analysis can be used to get static parameters in the range of centimeter to meter, while PTA can obtain static and dynamic parameters in the range of hundreds of meters to several kilometers, such as skin coefficient, boundary conditions, permeability and cross flow coefficient. Therefore, the PTA results are more practical and reliable. However, the well test curve shows similar characteristics for multi-layers reservoirs, dual-medium reservoirs, and carbonate reservoirs with lithology mixed sedimentation lithology [3,4]. It is important to reduce the parameter evaluation multiplicity.\u0000 However, many scholars did not consider the multiplicity of PTA interpretation in practical application, which led to large errors in the results [5,7]. Therefore, this paper comprehensively summarizes all the reasons leading to the depression of pressure derivative curve, and puts forward the corresponding identification approach, which has been applied in Abu Ghirab reservoir well test interpretation and created conditions for improving the accuracy of PTA.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"79 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87102555","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}
Klemens Katterbauer, Abdulaziz Al Qasim, Abdallah Al Shehri, A. Yousif
Hydrogen has become a very promising green energy source and it has the potential to be utilized in a variety of applications. Hydrogen, as a power source, has the benefits of being transportable and stored over long periods of times, and does not lead to any carbon emissions related to the utilization of the power source. Thermal EOR methods are among the most used recovery methods. They involve the introduction of thermal energy or heat into the reservoir to raise the temperature of the oil and reduce its viscosity. The heat makes the oil mobile and assists in moving it towards the producer wells. The heat can be added externally by injecting a hot fluid such as steam or hot water into the formations, or it can be generated internally through in-situ combustion by burning the oil in depleted gas or waterflooded reservoirs using air or oxygen. This method is an attractive alternative to produce cost-efficiently significant amounts of hydrogen from these depleted or waterflooded reservoirs. A major challenge is to optimize injection of air/oxygen to maximize hydrogen production via ensuring that the in-situ combustion sufficiently supports the breakdown of water into hydrogen molecules. which can then be separated from other gases via a palladium copper alloy membrane, leaving clean blue hydrogen. A crucial challenge in this process is achieving sufficient temperature in the reservoir in order to achieve this combustion process. The temperatures typically must reach around 500 degree Celsius to break the molecules apart. Hence, accurately monitoring the temperature within the reservoir plays a crucial role in order to optimize the oxygen injection and maximize recovery from the reservoir. Artificial intelligence (AI) practices have allowed to significantly improve optimization of reservoir production, based on observations in the near wellbore reservoir layers. This work utilizes a data-driven physics-inspired AI model for the optimal control of the high temperature wireless sensors for the optimal control of the oxygen injection in real-time. The framework was examined on a synthetic reservoir model with various producers and injectors. Each producer and injector contain various wireless high temperature sensors that are connected to each other. The framework then utilizes the temperature sensor data, in addition to the produced hydrogen, to optimize oxygen injection. This work represents a first and innovative approach to optimize subsurface wireless high temperature wireless sensing for maximizing hydrogen recovery from waterflooded reservoirs. The data-driven approach allows to optimize the hydrogen recovery representing a crucial element towards the drive for economical extraction of blue hydrogen.
{"title":"A Novel Artificial Intelligence Framework for the Optimal Control of Wireless Temperature Sensors for Optimizing Oxygen Injection in Subsurface Reservoirs","authors":"Klemens Katterbauer, Abdulaziz Al Qasim, Abdallah Al Shehri, A. Yousif","doi":"10.4043/31558-ms","DOIUrl":"https://doi.org/10.4043/31558-ms","url":null,"abstract":"\u0000 Hydrogen has become a very promising green energy source and it has the potential to be utilized in a variety of applications. Hydrogen, as a power source, has the benefits of being transportable and stored over long periods of times, and does not lead to any carbon emissions related to the utilization of the power source. Thermal EOR methods are among the most used recovery methods. They involve the introduction of thermal energy or heat into the reservoir to raise the temperature of the oil and reduce its viscosity. The heat makes the oil mobile and assists in moving it towards the producer wells. The heat can be added externally by injecting a hot fluid such as steam or hot water into the formations, or it can be generated internally through in-situ combustion by burning the oil in depleted gas or waterflooded reservoirs using air or oxygen. This method is an attractive alternative to produce cost-efficiently significant amounts of hydrogen from these depleted or waterflooded reservoirs. A major challenge is to optimize injection of air/oxygen to maximize hydrogen production via ensuring that the in-situ combustion sufficiently supports the breakdown of water into hydrogen molecules.\u0000 which can then be separated from other gases via a palladium copper alloy membrane, leaving clean blue hydrogen. A crucial challenge in this process is achieving sufficient temperature in the reservoir in order to achieve this combustion process. The temperatures typically must reach around 500 degree Celsius to break the molecules apart. Hence, accurately monitoring the temperature within the reservoir plays a crucial role in order to optimize the oxygen injection and maximize recovery from the reservoir.\u0000 Artificial intelligence (AI) practices have allowed to significantly improve optimization of reservoir production, based on observations in the near wellbore reservoir layers. This work utilizes a data-driven physics-inspired AI model for the optimal control of the high temperature wireless sensors for the optimal control of the oxygen injection in real-time.\u0000 The framework was examined on a synthetic reservoir model with various producers and injectors. Each producer and injector contain various wireless high temperature sensors that are connected to each other. The framework then utilizes the temperature sensor data, in addition to the produced hydrogen, to optimize oxygen injection.\u0000 This work represents a first and innovative approach to optimize subsurface wireless high temperature wireless sensing for maximizing hydrogen recovery from waterflooded reservoirs. The data-driven approach allows to optimize the hydrogen recovery representing a crucial element towards the drive for economical extraction of blue hydrogen.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81043351","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}
S. Ashraf, Rahmad Haidzar Muhamad Husin, Awang Rizalman, M. Bogaerts
Cement sheath integrity to prevent interzonal communication is closely related to the static gel strength. The API Standard 65-2 puts importance on the critical gel strength period (CGSP) measurement, which begins when the critical static gel strength (CSGS) is developed and ends when 500 lbf/100 ft2 is attained. The recommended duration for this period should be 45 min or less to be effective in isolating flow potentials. The API 10B-6 covers the three methods to measure the static gel strength development accepted in the industry, which are continuous and intermittent rotation followed by ultrasonic. A laboratory-based study is presented in this paper that compares these measurement methods. The slurry frameworks chosen for the comparison ranged between 11.5 to 18 lbm/gal and the temperature extended from 27 to 121°C. The formulation of the fluid system consisted of Class G cement, silica flour, weighting agent, or light weight extender for the blended phase. Liquid phase additives such as antifoam, fluid loss, dispersant, and retarder were used. The formulations were adjusted to simulate two placement times, i.e., one between 3 to 4 hr. and the second between 7 to 8 hr. The testing performed on the selected cement systems provided significant knowledge of the four different types of static gel strength development equipment used during the testing. There are two equipment's from different manufacturers operating using the continuous rotation method followed by one each for the intermittent rotation and the acoustic type. The overall average transit time for each slurry and the respective standard deviation were arranged for ease of comparison. It was found that there are less deviations in certain fluid systems compared with some other systems. As indicated by the API 10B-6, each equipment may well result in generating different static gel profiles due to cement sample size, apparatus configuration, and formulation. Slurry formulations can be modified to improve their transition time depending on conditions as needed.
{"title":"Comparing Oilwell Cement Static Gel Strength Development by Ultrasonic, Intermittent and Continuous Rotation Measurement Methods","authors":"S. Ashraf, Rahmad Haidzar Muhamad Husin, Awang Rizalman, M. Bogaerts","doi":"10.4043/31348-ms","DOIUrl":"https://doi.org/10.4043/31348-ms","url":null,"abstract":"\u0000 Cement sheath integrity to prevent interzonal communication is closely related to the static gel strength. The API Standard 65-2 puts importance on the critical gel strength period (CGSP) measurement, which begins when the critical static gel strength (CSGS) is developed and ends when 500 lbf/100 ft2 is attained. The recommended duration for this period should be 45 min or less to be effective in isolating flow potentials. The API 10B-6 covers the three methods to measure the static gel strength development accepted in the industry, which are continuous and intermittent rotation followed by ultrasonic. A laboratory-based study is presented in this paper that compares these measurement methods.\u0000 The slurry frameworks chosen for the comparison ranged between 11.5 to 18 lbm/gal and the temperature extended from 27 to 121°C. The formulation of the fluid system consisted of Class G cement, silica flour, weighting agent, or light weight extender for the blended phase. Liquid phase additives such as antifoam, fluid loss, dispersant, and retarder were used. The formulations were adjusted to simulate two placement times, i.e., one between 3 to 4 hr. and the second between 7 to 8 hr.\u0000 The testing performed on the selected cement systems provided significant knowledge of the four different types of static gel strength development equipment used during the testing. There are two equipment's from different manufacturers operating using the continuous rotation method followed by one each for the intermittent rotation and the acoustic type.\u0000 The overall average transit time for each slurry and the respective standard deviation were arranged for ease of comparison. It was found that there are less deviations in certain fluid systems compared with some other systems. As indicated by the API 10B-6, each equipment may well result in generating different static gel profiles due to cement sample size, apparatus configuration, and formulation. Slurry formulations can be modified to improve their transition time depending on conditions as needed.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86959773","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}
Interest in Floating Offshore Wind Farm (FOWF) is regaining momentum as countries and energy producers vie for economic and innovative solutions to decarbonize products and operations with net zero targets in perspective. Typically tapping offshore wind is costlier in comparison to land based solutions, despite the flexibility it offers due to remote operations away from populated areas. Floating wind farms offer an attractive mix of flexibility and cost effectiveness by eliminating the need for large supporting structures and enabling further deep-sea installations and access to stronger winds. While floating wind turbine technology is promising, it needs further maturation along with favorable policy implementation on the part of regulators to make floating wind farms attractive to operators/investors. This paper investigates Technology, Project Management challenges and opportunities from a large, Joint Venture capital project context with net zero target perspectives. Conceptually, floating wind energy is generated by a cluster of floating wind turbines, as against conventional fixed-bottom turbines which account for the majority of wind installations today. Several recent technological advancements have led to innovative floating wind solutions and also driven the costs downward. However, technological challenges like mooring and anchoring systems suited for harsh environments and policy challenges still present barriers to increased investment decisions. In both cases, synergies could potentially be harnessed from existing Oil & Gas deep sea technology. This paper will attempt to address such technology and policy challenges, as well as project management perspectives in maturing floating wind technology. Further, the project development lifecycle will be analyzed from stakeholder and risk management, technology maturation, decision making, and complexity management perspectives. While alleviating cost and flexibility challenges related to stick-built fixed-base solutions, floating technologies may have strategic potential to unlock the full potential of offshore wind and to serve as a vehicle to achieve green transition goals. This paper summarizes the potential risks and opportunities from political, economic, socio-cultural, technological, legal and environmental (PESTLE) points of view. Potential stakeholder influences and a decision quality matrix will be identified and documented. FOWF, PESTLE, Project Management, Complexity Management
{"title":"Floating Offshore Wind Energy – Brief Review of Prospects, Project Development Life Cycle, Policy and Technology Challenges and Project Management Complexity","authors":"Prasannakumar K. Purayil, Sujith Pratap Chandran","doi":"10.4043/31543-ms","DOIUrl":"https://doi.org/10.4043/31543-ms","url":null,"abstract":"Interest in Floating Offshore Wind Farm (FOWF) is regaining momentum as countries and energy producers vie for economic and innovative solutions to decarbonize products and operations with net zero targets in perspective. Typically tapping offshore wind is costlier in comparison to land based solutions, despite the flexibility it offers due to remote operations away from populated areas. Floating wind farms offer an attractive mix of flexibility and cost effectiveness by eliminating the need for large supporting structures and enabling further deep-sea installations and access to stronger winds. While floating wind turbine technology is promising, it needs further maturation along with favorable policy implementation on the part of regulators to make floating wind farms attractive to operators/investors. This paper investigates Technology, Project Management challenges and opportunities from a large, Joint Venture capital project context with net zero target perspectives. Conceptually, floating wind energy is generated by a cluster of floating wind turbines, as against conventional fixed-bottom turbines which account for the majority of wind installations today. Several recent technological advancements have led to innovative floating wind solutions and also driven the costs downward. However, technological challenges like mooring and anchoring systems suited for harsh environments and policy challenges still present barriers to increased investment decisions. In both cases, synergies could potentially be harnessed from existing Oil & Gas deep sea technology. This paper will attempt to address such technology and policy challenges, as well as project management perspectives in maturing floating wind technology. Further, the project development lifecycle will be analyzed from stakeholder and risk management, technology maturation, decision making, and complexity management perspectives. While alleviating cost and flexibility challenges related to stick-built fixed-base solutions, floating technologies may have strategic potential to unlock the full potential of offshore wind and to serve as a vehicle to achieve green transition goals. This paper summarizes the potential risks and opportunities from political, economic, socio-cultural, technological, legal and environmental (PESTLE) points of view. Potential stakeholder influences and a decision quality matrix will be identified and documented. FOWF, PESTLE, Project Management, Complexity Management","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82819832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For Deep Sea Mining (DSM), the current concept for the Vertical Transport System (VTS) has multiple lines for the return of water to the sea bottom. Such VTS resembles a drilling riser, which is a field-proven technology. Our objective is to compare a drilling riser with different boundary conditions, including hang-off configuration. Numerical simulation was calculated using commercial software for dynamic analysis of riser systems. The simulation included a 1, 500m long riser, sea current, irregular waves, and the platform motion calculated using Response Amplitude Operator. For the top tensioned configuration, the tensioning system is required to avoid the riser pipe's buckling and the Mathieu Instability at the bottom portion of the riser. On the other hand, the same phenomenon did not occur in the hang-off configuration. The LMRP and BOP attached to the bottom end kept the riser pipe tensioned during the whole simulation. Therefore, the hang-off configuration is an important alternative for DSM riser. Besides, a tensioning system shall be mandatory for VTS when supported or attached to the seafloor.
{"title":"Study on Riser System in Hang-Off Configuration for Deep-Sea Mining","authors":"Marcio Yamamoto, J. Yamamoto, Sotaro Masanobu","doi":"10.4043/31672-ms","DOIUrl":"https://doi.org/10.4043/31672-ms","url":null,"abstract":"\u0000 For Deep Sea Mining (DSM), the current concept for the Vertical Transport System (VTS) has multiple lines for the return of water to the sea bottom. Such VTS resembles a drilling riser, which is a field-proven technology. Our objective is to compare a drilling riser with different boundary conditions, including hang-off configuration.\u0000 Numerical simulation was calculated using commercial software for dynamic analysis of riser systems. The simulation included a 1, 500m long riser, sea current, irregular waves, and the platform motion calculated using Response Amplitude Operator.\u0000 For the top tensioned configuration, the tensioning system is required to avoid the riser pipe's buckling and the Mathieu Instability at the bottom portion of the riser. On the other hand, the same phenomenon did not occur in the hang-off configuration. The LMRP and BOP attached to the bottom end kept the riser pipe tensioned during the whole simulation. Therefore, the hang-off configuration is an important alternative for DSM riser. Besides, a tensioning system shall be mandatory for VTS when supported or attached to the seafloor.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90116681","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}
Muhd Akram Kamaruzaman, Mohd Saifullah Din, Ernyza Endot, P. Sim, Chrissie Lojikim, C. Chang, Mohd Faiz Mohd Ramli
Central Luconia has been explored with hundreds of well since the 1950s. During that time, all offshore wells were drilled using hyperbolic positioning system which has lower accuracy compare to current satellite positioning system, which was only introduced in early 1990s. With this knowledge, the old exploration well's locations (which was drilled in 1970s) pose potential hazards in terms of seabed obstruction and potential well collision during the future development wells drilling. Without a reliable seismic to well tie, interpreter has difficulty in identifying the top of carbonate event for depth conversion, thus impacting the well delivery, static model building and subsurface reserves estimation. Onsite verification was carried out using a multibeam echosounder (MBES), a Side Scan Sonar (SSS), and a Sub Bottom Profiler (SBP) in accordance with standard site survey procedures, but the existing wellhead location was unable to be detected because the wells had been abandoned and cut off at the seabed level. Magnetometer was deployed to further investigate the existing wellhead location; the sensor was towed approximately about three (3) times water depth from the stern of the vessel and altitude 10m from the seabed. To navigate the towed sensor, Ultra Short Baseline (USBL) transponder was attached close to the sensor to get real time underwater positioning. Five (5) survey lines were designed centered at the suspected existing wellhead location with the coverage of 60m radius. During data acquisition, the magnetic anomalies were recorded in the system via receiver and total magnetic data was used for further analysis to derive the as-found wellhead location. During the interpretation, the area of ambient magnetic field distortion was identified and marked as anomaly which represents "area of suspected wellhead". The magnitude and pattern of such distortion was used for interpretation and combined with the coordinates from the positioning system (surface and underwater) onboard the survey vessel. The general total magnetic field reading is ranging between 40920nT and 41130nT with the magnetic anomaly/wellhead had magnetic value from 100nT to 115nT. The total magnetic field analytical signal value is ranging from 0 to 3.5. The target magnetic anomaly refers to the area with greatest analytical signal value where it is also the area with most drastic change of the total magnetic field. From the survey results, the as-found wellhead position varies from 48m - 53m compared to existing wellhead position. With the confirmation on the old wellhead location, this helps to derisk the well collisions study for future development well and also improves the seismic to well tie analysis to provide higher confidence in the Top Carbonate pick and a better inverted seismic match in the reservoir interval for properties distribution.
{"title":"Magnetometer Survey: Multi-Discipline Collaboration Impacting Bottom Line","authors":"Muhd Akram Kamaruzaman, Mohd Saifullah Din, Ernyza Endot, P. Sim, Chrissie Lojikim, C. Chang, Mohd Faiz Mohd Ramli","doi":"10.4043/31628-ms","DOIUrl":"https://doi.org/10.4043/31628-ms","url":null,"abstract":"\u0000 Central Luconia has been explored with hundreds of well since the 1950s. During that time, all offshore wells were drilled using hyperbolic positioning system which has lower accuracy compare to current satellite positioning system, which was only introduced in early 1990s. With this knowledge, the old exploration well's locations (which was drilled in 1970s) pose potential hazards in terms of seabed obstruction and potential well collision during the future development wells drilling. Without a reliable seismic to well tie, interpreter has difficulty in identifying the top of carbonate event for depth conversion, thus impacting the well delivery, static model building and subsurface reserves estimation.\u0000 Onsite verification was carried out using a multibeam echosounder (MBES), a Side Scan Sonar (SSS), and a Sub Bottom Profiler (SBP) in accordance with standard site survey procedures, but the existing wellhead location was unable to be detected because the wells had been abandoned and cut off at the seabed level. Magnetometer was deployed to further investigate the existing wellhead location; the sensor was towed approximately about three (3) times water depth from the stern of the vessel and altitude 10m from the seabed. To navigate the towed sensor, Ultra Short Baseline (USBL) transponder was attached close to the sensor to get real time underwater positioning. Five (5) survey lines were designed centered at the suspected existing wellhead location with the coverage of 60m radius. During data acquisition, the magnetic anomalies were recorded in the system via receiver and total magnetic data was used for further analysis to derive the as-found wellhead location. During the interpretation, the area of ambient magnetic field distortion was identified and marked as anomaly which represents \"area of suspected wellhead\". The magnitude and pattern of such distortion was used for interpretation and combined with the coordinates from the positioning system (surface and underwater) onboard the survey vessel.\u0000 The general total magnetic field reading is ranging between 40920nT and 41130nT with the magnetic anomaly/wellhead had magnetic value from 100nT to 115nT. The total magnetic field analytical signal value is ranging from 0 to 3.5. The target magnetic anomaly refers to the area with greatest analytical signal value where it is also the area with most drastic change of the total magnetic field. From the survey results, the as-found wellhead position varies from 48m - 53m compared to existing wellhead position. With the confirmation on the old wellhead location, this helps to derisk the well collisions study for future development well and also improves the seismic to well tie analysis to provide higher confidence in the Top Carbonate pick and a better inverted seismic match in the reservoir interval for properties distribution.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75926617","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}
Seismic forward modelling is typically done using the finite difference (FD) approach. However, this method suffers from numerical dispersion problems which translates into less focused stacks and a decrease in bandwidth coverage. To mitigate this problem, the pseudo analytical method formulated by Etgen and Brandersberg-Dahl in 2009 was utilized. This paper demonstrates that pseudo analytics’ pseudo differential operator that utilizes velocity interpolation allows it to be more robust towards varying velocity and grid sizes while providing better amplitudes for shot gathers compared to the FD modelling scheme. FD and pseudo analytically generated gathers were then migrated using the reverse time migration (RTM) algorithm and showed that the pseudo analytically generated shot gathers were better at preserving shallower and higher frequency reflectors while at the same time better suppressed migration artifacts at the steeply dipping salt flank. The pseudo analytically generated gathers also provided an improved amplitude spectrum compared to FD especially in the lower frequency range of around 25-50 Hz. Various test cases demonstrate that the pseudo analytical method was shown to be a viable alternative to the typically used FD method in imaging at challenging geological environments such as salt.
{"title":"Comparison Between the Pseudo-Analytical and Finite Difference Method for Seismic Modelling and Imaging","authors":"M. Muhammed, M. Isa, S. Mishra","doi":"10.4043/31687-ms","DOIUrl":"https://doi.org/10.4043/31687-ms","url":null,"abstract":"\u0000 Seismic forward modelling is typically done using the finite difference (FD) approach. However, this method suffers from numerical dispersion problems which translates into less focused stacks and a decrease in bandwidth coverage. To mitigate this problem, the pseudo analytical method formulated by Etgen and Brandersberg-Dahl in 2009 was utilized. This paper demonstrates that pseudo analytics’ pseudo differential operator that utilizes velocity interpolation allows it to be more robust towards varying velocity and grid sizes while providing better amplitudes for shot gathers compared to the FD modelling scheme. FD and pseudo analytically generated gathers were then migrated using the reverse time migration (RTM) algorithm and showed that the pseudo analytically generated shot gathers were better at preserving shallower and higher frequency reflectors while at the same time better suppressed migration artifacts at the steeply dipping salt flank. The pseudo analytically generated gathers also provided an improved amplitude spectrum compared to FD especially in the lower frequency range of around 25-50 Hz. Various test cases demonstrate that the pseudo analytical method was shown to be a viable alternative to the typically used FD method in imaging at challenging geological environments such as salt.","PeriodicalId":11081,"journal":{"name":"Day 2 Wed, March 23, 2022","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75226832","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}
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}
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