Day 1 Mon, February 12, 2024最新文献

{"title":"How Corporations Succeed by Solving World's Toughest Problems - Tackling Climate Change with an Elite Business Research Consortium and AI-Enhanced Leadership: Decision-Making Endeavor in the Face of Climate Change","authors":"Muhammad Affan Uddin Ali Khan, Clifford Louis, Abdul Ahad Manzoor, Syed Imran Ali, Shaine Muhammadali Laliji, Syed Muhammad Aun Ali, J. Haneef, Faiq Azhar Abbasi, Muhammad Sami Khan, Syed Talha Tirmizi, Muhamad Kamran","doi":"10.2523/iptc-24189-ms","DOIUrl":"https://doi.org/10.2523/iptc-24189-ms","url":null,"abstract":"\u0000 This study aims to contribute to the success of corporations in addressing global challenges, specifically focusing on climate change. The primary objective is to enhance the heat resistance capabilities of materials crucial for geothermal energy extraction, a key renewable energy source with minimal carbon footprint. Presently, Iceland leads in global geothermal energy production, emphasizing the significance of optimizing extraction methods. Previous research faced challenges due to suboptimal material selection, hindering drilling to greater depths. This study proposes a novel solution—employing innovative material coatings on drilling bits and pipes, utilizing metallic compounds with exceptional heat resistance properties. The coating strategy involves leaving pipes uncoated up to a depth where they naturally withstand heat, with subsequent application for greater depths. This approach promises cost-effective materials capable of enduring extreme conditions in geothermal drilling, fostering higher drilling depths and cost efficiency. Implementation projections suggest significant facilitation of geothermal energy extraction, particularly in abandoned wells near tectonic plate boundaries, reducing extraction costs. The study underscores the societal benefits of tapping into indigenous renewable energy sources, emphasizing the minimal carbon footprint of geothermal energy. The proposed material-coating approach aligns with global efforts to combat climate change and presents a strategic decision-making endeavor for corporations to contribute to environmental sustainability.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"26 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528028","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}

{"title":"Well Collision Risk Management by Fully Automated Wellbore Surveying","authors":"M. ElGizawy, N. Zackman, J. Hernandez, F. Gomez, A. Row","doi":"10.2523/iptc-23986-ms","DOIUrl":"https://doi.org/10.2523/iptc-23986-ms","url":null,"abstract":"\u0000 A survey program is designed for every well to meet the well objective of penetrating the target reservoir and avoid colliding with other offset wells. The selection of the wellbore survey tools within the survey program is limited in number and accuracy by the surveying technologies available in the industry currently. Quality Control QC measures are regularly in place to ensure the wellbore surveys’ accuracy is validated. However, wellbore surveys often delivered without conducting the full QC measures and sometime are delivered with failing QC measures. This increases the risk of missing the survey program's objective and more critical escalates the risk of the well collision with other wells.\u0000 Hence, quality control of survey correction is a key to the success of the overall objectives of the well construction. As automated survey-correction software is becoming commonplace among oil and gas operators it is important to consider its use in relation to the overall well risk management strategies. This paper is presenting the latest developed automation workflows to strictly guarantee the quality control and quality assurance of the wellbore survey while placing the well in real-time.\u0000 Automated Survey QC and correction platforms go a long way to reduce gross error or human related errors with algorithms and machine to machine data transfer protocols. Automated survey QC and correction platforms can be key components in robust risk management solutions for well construction. When implemented appropriately, they allow quick and automated quality check and corrections on wellbore trajectory position which is critical in Anti-Collision and tight target wells. Even though the correction platform is automated it still requires clarity and confidence in the algorithms. This can be achieved with features that are easily accessible, clear, and understandable to inexperienced users. In addition, there should be readily reachable domain experts who can confirm and further interpret the results quickly and clearly, especially when well objectives are in peril of not being met.\u0000 In this paper, automated survey QC and correction enablers are detailed. How quality control of survey correction are automated, strictly controlled and easily auditable. Additionally, case studies of well construction risk management are presented as well as the successful proof of eliminating human/gross error and non-compliance are demonstrated.\u0000 The wellbore position is calculated using wellbore surveys. The fact the surveys inherit errors due to tools and environment, the quality of surveys must be ensured and corrected in real-time. The presented technique automates the survey QC and correction process in real-time with a main objective to minimize the risk of colliding with another well or missing the production zone targets while being part of a robust risk management structure.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"18 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527794","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}

{"title":"Uncertainty Quantification and Management in Model Calibration and History Matching with Ensemble Kalman Methods","authors":"A. A. Al-Turki, K. J. Hammad, S. B. Sudirman, Z. N. Sawlan","doi":"10.2523/iptc-23786-ms","DOIUrl":"https://doi.org/10.2523/iptc-23786-ms","url":null,"abstract":"\u0000 History matching field performance is a time-consuming, complex and ill-posed inverse problem that yields multiple plausible solutions. This is due to the inherent uncertainty associated with geological and flow modeling. The history matching must be performed diligently with the ultimate objective of availing reliable prediction tools for managing the oil and gas assets. Our work capitalizes on the latest development in ensemble Kalman techniques, namely, the Ensemble Kalman Filter (EnKF) and Ensemble Smoother (ES) to properly quantify and manage reservoir models’ uncertainty throughout the process of calibration and history matching.\u0000 Iterative ensemble algorithms have been developed to overcome the shortcomings of the existing methods such as the lack of data assimilation capabilities and abilities to quantify and manage uncertainties, in addition to the huge number of simulations runs required to complete a study. In this work, NORNE benchmark model was used to generate an initial ensemble of 40 to 50 equally probable reservoir models was generated with variable areal, vertical permeability and porosity. The initial ensemble captured the most influencing reservoir properties, which will be propagated and honored by the subsequent ensemble iterations. Data misfits between the field historical data and simulation data are calculated for each of the realizations of reservoir models to quantify the impact of reservoir uncertainty, and to perform the necessary changes on horizontal, vertical permeability and porosity values for the next iteration. Each generation of the optimization process reduces the data misfit compared to the previous iteration. The process continues until a satisfactory field level and well level history match is reached or when there is no more improvement.\u0000 The application of the Iterative ensemble algorithms is demonstrated by history matching NORNE benchmark model. Multiple iterative ensemble smoothers with adaptive inflation and localization techniques were implemented and compared. The ES algorithms preserved key geological features of the reservoir model throughout the history matching process. During this study, ES served as a bridge between classical control theory solutions and Bayesian probabilistic solutions of sequential inverse problems. The methods demonstrated good tracking qualities while giving some estimate of uncertainty as well.\u0000 The updated reservoir properties (horizontal, vertical permeability and porosity values) are conditioned throughout the ES iterations (cycles), maintaining consistency with the initial geological understanding. The workflow resulted in enhanced history match quality in shorter turnaround time with much fewer simulation runs than the traditional genetic or evolutionary algorithms. The geological realism of the model is retained for robust prediction and development planning.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"32 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528176","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}

{"title":"Composite Repair Validation and Testing: Offshore and Onshore Pipeline Correlation and Findings","authors":"J. Petch, P. Suchada, T. Matina","doi":"10.2523/iptc-24583-ms","DOIUrl":"https://doi.org/10.2523/iptc-24583-ms","url":null,"abstract":"\u0000 Composite wrapping has seen increased usage in both offshore and onshore production assets for the purpose of addressing faults and repairing spots on piping, risers, and pipelines. Validation of repair techniques and products is crucial to ensure the effectiveness and reliability of composite materials utilization. The primary objectives of this study are to establish criteria for validating the Composite Wrap Repair technique, develop a framework for re-validation, and distinguish between materials and protocols used for onshore and offshore pipeline integrity repairs. This study is divided into two parts, examining the principles and standards of Composite Repair products and evaluating their performance in their intended environment. Our product line includes composite repair solutions for both onshore and offshore pipelines. Additionally, we provide a comprehensive analysis of non-destructive testing (NDT) procedures for inspecting and re-validating composite repairs. The project will investigate the use of composite materials for repairing pipelines located both offshore and onshore. We are currently conducting a study on Composite Repair Inspection Techniques, focusing on their on-site application, limitations, and any proof-of-concept findings. We are looking for excellent insights in this area. Through these two component investigations, revalidation criteria and a framework were obtained.\u0000 A study has been carried out on various composite repair materials and systems that are commonly used in the oil and gas industry. The main emphasis was on understanding their characteristics and evaluating their performance. The study resulted in a deeper understanding of the materials in question. This study sought to examine the mechanical parameters and performance of the chosen products in different load conditions and operating environments, both onshore and offshore. The main goal was to validate the failure mechanisms. Furthermore, a thorough assessment of the main elements has been conducted following the guidelines set by ASTM and ISO standards. This evaluation has been compared to enable further on-site inspections, ensuring the validation of composite wrap repairs currently in use. The evaluation of the proof-of-concept non-destructive testing (NDT) inspection procedures has identified four distinct and promising methods. These methods include contour and digital radiographic scan, infrared thermography, and CT scanner. These methods can be implemented and validated on-site, depending on the desired outcomes. The final section was evaluated to determine the criteria for validation and revalidation, as well as the process of developing them for future use. The study highlights the different reasons behind the failure of composite repair solutions for onshore and offshore pipelines, which are primarily related to the adhesive ingredients and fiber alignment. Prior to deploying each product on assets, a thorough analysis was conducted to as","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527637","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}

{"title":"Development of a Mechanistic and Data-Driven Model for Multiphase Flow Leak Detection in Pipeline","authors":"A. Barooah, M. Khan, Mohammad Azizur Rahman, R. Hassan, I. Hassan, A. Sleiti, S. R. Gomari, Matthew Hamilton","doi":"10.2523/iptc-24574-ms","DOIUrl":"https://doi.org/10.2523/iptc-24574-ms","url":null,"abstract":"\u0000 Prompt and reliable detection of pipeline leaks is vital for human safety, the economy, the environment, and corporate reputation. However, a simple mechanistic model for accurately predicting leak characteristics in different flow regimes is lacking. To fill this gap, a novel methodology was used to develop a multiphase flow leak detection model using only inlet and outlet parameters.\u0000 The gas-liquid two-phase leak mass flow rate, location, and size are computed through iterative processes in the upstream and downstream sections of the leak. Data sets were generated for a wide range of geometric (3 – 5 inch pipe diameter, 2000 – 10000 feet pipe length, 500 – 1500 feet leak location, 0.2 – 3 inch leak opening diameter), hydrodynamic (Newtonian, air, CO2, N2) and operating conditions (0.3 – 0.628 outlet liquid fraction). These data sets were utilized to develop contour plots and a data-driven model using statistical analysis based solely on the inlet and outlet parameters.\u0000 The results indicate that a change in total mass flow rate and pressure in the inlet and the outlet section of the leak can be a good indicator for determining the location and size of the leak. The effect of different pressure constraints, pipe length, pipe diameter, two-phase fluid rheology, leak diameter, leak location, outlet liquid volume fraction, and flowing liquid hold-up on leak size, pressure, and flow rate is analyzed. Decreasing the liquid fraction in the outlet section of the leak leads to a slight increase (6% average) in the inlet mass flow rate and a significant decrease (50% average) in the outlet mass flow rate for fixed pressure constraints, resulting in an increased leak flow rate, pressure, and density. Similarly, longer pipe lengths, bigger pipe diameters, heavier gas phase, and lower liquid fraction at the outlet have higher leak pressure for the same leak locations due to higher leak flow rate. Furthermore, contour plots revealed that identifying a leak near the pipe inlet is easier, although determining its size remains challenging. On the other hand, detecting a leak near the pipe outlet is more difficult, but assessing its size is comparatively easier. The developed data-driven showed good agreement with different literature data sets with a MAPE of less than 20%.\u0000 The mechanistic model's key advantage lies in its reliance on fundamental equations and physics, making it applicable to various operating conditions for field applications. Moreover, the data-driven model is straightforward and accurate, eliminating the need for complex simulations. This study has the potential to assist industries in determining leak location, size, and pressure using only the inlet and outlet parameters, without requiring multiple sensors along pipelines.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"33 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528015","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}

{"title":"A Developed Robust Model and Artificial Intelligence Techniques to Predict Drilling Fluid Density and Equivalent Circulation Density in Real-Time","authors":"Mohammed Murif Al-Rubaii محمد مريف الربعي","doi":"10.2523/iptc-23904-ms","DOIUrl":"https://doi.org/10.2523/iptc-23904-ms","url":null,"abstract":"\u0000 When drilling deep wells, it is important to regulate the formation pressure and prevent kicks. This is achieved by controlling the equivalent circulation density (ECD), which becomes crucial in high-pressure and high-temperature wells. ECD is particularly important in formations where the pore pressure and fracture pressure are close from each other (narrow windows). However, the current methods for measuring ECD using downhole sensors can be expensive and limited by operational constraints such as high pressure and temperature. Therefore, to overcome this challenge, two novel models name as ECDeffc.m and MWeffc.m with approach was developed to predict ECD and mud weight (MW) from surface drilling parameters, including standpipe pressure, rate of penetration, drill string rotation, and mud properties. In addition, by utilizing an artificial neural network (ANN) and a support vector machine (SVM), ECD was estimated with a correlation co-efficient of 0.9947 and an average absolute percentage error of 0.23%. Meanwhile, a decision tree (DT) was employed to estimate MW with a correlation coefficient of 0.9353 and an average absolute percentage error of 0.001%. The two novel models were compared with the artificial intelligence (AI) techniques to evaluate the developed models. The results proved that the two novel models were more accurate with the value that obtained from pressure while drilling tools (PWD). These models can be utilized during well design and while drilling operation to evaluate and monitor the appropriate mud weight and equivalent circulation density for saving time and money by eliminating the need for expensive downhole equipment and commercial software.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"66 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528201","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}

{"title":"Dynamic Flow Behavior Analysis of Wet Gas Pipelines","authors":"S. A. Putra","doi":"10.2523/iptc-24562-ms","DOIUrl":"https://doi.org/10.2523/iptc-24562-ms","url":null,"abstract":"\u0000 Corroded wet gas pipelines could be a result of inadequate flow and cause stagnant water along the pipeline. Evaluation of flow behavior in a pipeline is necessary to ensure the integrity of the pipeline is well maintained. This paper presents an evaluation through dynamic flow simulation analysis of the optimum flow range for avoiding low velocity and stagnant fluid in a wet-gas pipeline network. The determining factors include pressure drop, liquid and water holdup, as well as gas and liquid velocities.\u0000 To minimize the potential for corrosion due to stagnant water in contact with the pipe wall, the gas flow rate corresponding to a range of water holdup values along the pipeline, as well as the range of gas velocities, were evaluated. The variation in liquid velocity at these conditions was evaluated to confirm the stability of the flow. Additionally, the gas flow rates corresponding to the minimum holdup in the pipeline and overall pressure drop were obtained. Due to the dynamic nature of the flow, analysis required determination of maximum, minimum and average values associated with the gas flow rates. The impact of the elevation profile, various pipe sizes (4, 6, 8, and inches), and different gas properties were also considered for this analysis.\u0000 Analysis indicated that operating at a minimum pressure drop in the pipeline could increase the potential for corrosion due to increase in water holdup. Additionally, the analysis suggested that the minimum flow rate for operation of the pipelines should be based on flow stability and water wetting the wall, and on acceptable pressure drop, but not by liquid or water holdup/accumulation.\u0000 Dynamic flow behavior analysis in this paper shows flow stability corresponds to the gas flow rates for different pipeline sizes. Corrosion in pipelines may therefore be due to low flow or stagnant liquid along the pipeline, which is an important factor for assessing pipeline integrity.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"165 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528459","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}

{"title":"An Improved Method for Oil-Water Contact Determination in Connected Fractured-Caved Reservoir Modeling Restricted by Data of Oil Displacement by Cyclic Water Injection","authors":"Qi Zhang, Mengqin Li, Wen Cao, Ge Niu, Jing Zhang, Qi Wang","doi":"10.2523/iptc-24031-ms","DOIUrl":"https://doi.org/10.2523/iptc-24031-ms","url":null,"abstract":"\u0000 With complicated accumulation mechanism of fractured-caved carbonate formations, characterization of reservoir and fluid distribution has great uncertainty due to varied oil-water contact and discontinuous reservoir, which brings difficulties to refined reservoir characterization and development index prediction. However, wells are always completed in upper part of the reservoir, instead of drilled through the pay zone, leaving the oil-water contact unknown below the well. It's urgent for a reservoir unit to confirm the oil-water contact. In the study, a method is proposed to constrain the pore volume and aquifer volume in a fractured-caved model based on the projection of water injection data. A material balance equation set of cyclic water injection in the fractured-caved reservoir is used to calculate the total volume of the connected reservoir drained by wells and distinguish the volume proportion of water in the fluid, according to the formation pressure recovery caused by the certain water injection volume in each cycle. A geological model is built via multi-attribute modeling technology and then modified by the outcome of former dynamic reserve evaluation. The seismic attribute threshold of reservoir extraction is controlled by the total reservoir volume, thus the volume of geological model determined. The depth of oil-water contact is adjusted to fit the oil and water volumes related to the water volume ratio, finally a reasonable oil-water contact obtained. Fractured-caved reservoir model and oil-water contact depth are further verified and corrected by drilling and completion data, oil testing and water production data. The feasibility and reliability of the method are demonstrated by a case study in Tarim Oilfield, where the depth of oil-water contact is deduced as −6342m from the first producer in the reservoir unit, and the oil testing of second producer supports it. The method can be applied to single wells or well groups in fractured-caved reservoir that have not yet seen water breakthrough after water injection. It can improve the geological understanding of the reservoir, evaluate the development potential of water injection, and predict the water breakthrough, helpful to the adjustment of development measures.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"53 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527605","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}

{"title":"Novel Pipeline Inspection Multiparametric Sensor","authors":"William Palozzo, C. Passucci, Emilio D'Alessandro, Simone Arca, A. Leoni, G. Barile, Vincenzo Stornelli","doi":"10.2523/iptc-24587-ms","DOIUrl":"https://doi.org/10.2523/iptc-24587-ms","url":null,"abstract":"\u0000 Pipelines represent the most reliable and safe means of transport of hydrocarbons and are designed to grant the material distribution under several stress conditions. However, structural ageing, human interaction and natural occurrences can damage the fluid transport network causing leakage. Detection and localization of anomalies in pipeline structures is a fundamental operation, in order to avoid economic and commodity losses, safety problems and equipment failure. Hence, periodic monitoring is needed to save resources, which may imply great expenditures both in terms of economy and maintenance effort. Asset integrity monitoring of pipelines by means of conventional methods is expensive, invasive and not always applicable, due to the harsh environmental conditions, especially in underground lines, and the extensive length of the pipelines. This work proposes a low-cost pipeline inspection system, based on a multi-sensory device that can be inserted directly into the conduct alone or bonded to cleaning or inspection pigs. The aforementioned device can measure pipelines internal parameters such as pressure, and 3 axial accelerations during its rout inside the pipeline, allowing less invasive monitoring with respect to other methods. The user manages the system and collects useful data at a high level by means of a dedicated software application. The devices recharge and communication is completely wireless in order to obtain an intrinsic protection of the electronics from the environment. The device developed allow for measuring pressure ranging from 1 to 200 bar, temperature ranging from -20 to 80°C 3 axial acceleration ranging from 1g to 16g, 3 axial rotation ranging from 1 to 2000 dps, a sampling frequency settable from 1 to 200 Hz and a battery ranging from 48 to 72h. The device has been realized built in a special epoxy resin oil-proof, gas-proof, and water-proof and capable to withstand the chemical harsh environment typical of a pipeline. It is also equipped with an optional floating shell capable to make the same floatable and thus free flowing inside the oil stream. Such device has been successfully tested in various pipeline reporting fundamental date related to pipeline deposits, cleaning, geometry etc. with mission's length varied from 400-600 m to 25-30 km, with mission time ranging from few minutes several hours.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527627","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}

{"title":"Digital Solution for Well Surveillance in Stacked Reservoirs with Near-Critical Fluid Systems","authors":"K. Mogensen, C. Mata, S. Samajpati, P. Cremades, J. E. L. Uribe, M. Al Zaabi","doi":"10.2523/iptc-23912-ms","DOIUrl":"https://doi.org/10.2523/iptc-23912-ms","url":null,"abstract":"\u0000 Fully compositional integrated asset models (FC-IAM) are being deployed for an increasing number of fields in the company's portfolio. Field A described in this work comprises four stacked reservoirs, each containing a near-critical fluid system with significant compositional depth gradient. Augmenting the FC-IAM with high-frequency sensor data as well as proprietary tools to actively monitor well performance helps identify and pursue opportunities to maximize the oil production rate from the field, subject to several system constraints.\u0000 Fluid properties were modelled with a cubic equation of state tuned to laboratory data to address some key challenges: Near-critical fluid systems giving rise to compositional variation versus depth.Injection of produced gas that develops multi-contact miscibility with the original reservoir fluids.Blending of fluids at surface from four stacked reservoirs.Operational requirement to maintain the bottom-hole pressure above saturation pressure.Validation of raw well test data before shrinkage correction (line conditions).\u0000 Compositional surface network models are run automatically on hourly basis and compared against real-time data. A surveillance algorithm identifies opportunities and assigns them to well owners. Activities are managed through a high-level tracking and value-capture system.\u0000 The asset team is consistently maintaining the well and surface network models assisted by the digital solution. The surveillance automation engine creates a feedback loop with the engineers which ensures that the models are of sufficient quality for production optimization. Models reproduce the actual oil and gas produced rates within the accepted accuracy range and are used routinely in optimization scenarios. The surface network model is also run in transient mode to study and optimize flow in two large subsea multiphase pipelines. Total value generation from implementation of the complete framework therefore exceeds expectation based on the steady-state production gain. The intangible value associated to reducing engineers’ workload, better data accessibility, HS&E and efficiency of operations has set a strong foundation for the strategy of the company to grow its enterprise value through increased volume and cost reduction.\u0000 Implementation of a compositional model framework is still uncommon as most integrated asset models rely on a black-oil formulation for the fluid property description. Near-critical fluid systems undergoing miscible gas injection add an additional layer of complexity in terms of modeling and surveillance efforts. Real-time data have proven indispensable for keeping the IAM up to date and for identifying opportunities for optimizing the production.","PeriodicalId":519056,"journal":{"name":"Day 1 Mon, February 12, 2024","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527609","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}