Day 1 Sun, February 19, 2023最新文献

{"title":"Integrated Rock Physics Model to Predict Sweet Spots in an Unconventional Jurassic Carbonate Source Rock","authors":"A. Mohammed, Y. Altowairqi","doi":"10.2118/213218-ms","DOIUrl":"https://doi.org/10.2118/213218-ms","url":null,"abstract":"\u0000 The exploration of unconventional hydrocarbon resources mainly targets the tight source rock reservoirs where hydraulic fracturing is needed for an effective hydrocarbon production. This project aims to predict new areas with high hydrocarbon production potential that can be effectively stimulated/fractured, known as sweet spots, in a tight Jurassic carbonate source rock.\u0000 A rock physics model was developed to link the seismic properties to rock properties of the target formation. Three main rock properties are used in this study to define the sweet spots: total organic content (TOC), Young's modulus (YM) and Poisson's ratio (PR). TOC is a geochemical property that is related to the production potential and is obtained in the laboratory from core, while YM and PR are rock elastic properties that are related to the frackability and are obtained from density and sonic (compressional and shear) logs. Sweet spots are generally characterized by high values of TOC, high values of YM and low values of PR. Using well data, these three properties were cross-plotted against two derivative elastic properties (lambda-rho and mu-rho) that are calculated using sonic (compressional and shear) and density logs to obtain a linear relationship. Lambda and mu are measures of incompressibility and shear rigidity, respectively, while rho is density. Cutoffs of lambda-rho and mu-rho were chosen to represent the sweet spots. The distribution of sweet spots in the study area was then mapped using a rock physics model that is built by integrating two inverted 3D seismic volumes; lambda-rho and mu-rho.\u0000 Results show that sweet spots are characterized by low values of lambda-rho and mu-rho, and are well distributed in the study area. In addition, results show that TOC has an inverse relationship with frackability which means that there should be a balance between reservoir quality and completion quality when targeting sweet spots for more economical hydrocarbon production.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130614899","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":"Comparison of Analytical Model Versus Numerical Model in Estimating EUR of Well Drilled and Completed in Unconventional Source Rock","authors":"Rabah Mesdour, Faisal Almalki, Qarni Mohammed, Dossary Mohammed, Albassam Mohamed","doi":"10.2118/213203-ms","DOIUrl":"https://doi.org/10.2118/213203-ms","url":null,"abstract":"\u0000 For the last decade shale gas has made a significant contribution to the oil and gas market by introducing multi-fractured horizontal wells. Forecasting the production for these wells is a challenging task due to reservoir properties and fracture network complexity created by hydraulic fracturing. Two methods ‘Analytical and simulation’ proposed in this paper to forecast the well performance, and quantify the differences one might expect to encounter in a well’s Estimated Ultimate Recovery \"EUR\". Analytical models are widely used as tools for history matching and forecasting production in unconventional resources due to the advantages of simplicity and efficiency. On the other hand there is an increasing interest in the use of numerical simulation for unconventional reservoirs to predict well performance and Estimated Ultimate Recovery \"EUR\". The two Methods used to match and predict the production of hydraulically fractured unconventional horizontal wells, and the results comparison was made to check on the efficiency and quality of these two methods.\u0000 This study will help to quantify the differences one might expect to encounter in a well’s Estimated Ultimate Recovery \"EUR\" when using analytical model-based Rate Transient Analysis \"RTA\" versus numerical simulation-based workflows in unconventional reservoirs. This workflow provides multiple history-matched models that are constrained by historical production data. The probabilistic forecast method employed in this work provides P90 (conservative), P50 (most likely), and P10 (optimistic) values for EUR. All the results obtained with the numerical method were compared to the analytical, the findings between these two methods will help to know which most reliable method to be used in predicting the future wells performance to Estimated \"EUR\". The operators looking for fast and reliable answer to predict the well performance for increasing the success of the models used in the completion, and help for better business planning. This study will help us to know what the most consistent method to use along with hydraulic fractures properties.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"84 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131681987","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":"Integrated Petrophysical Evaluation Using Organic Shale Petrophysics OSP Approch Based on NMR, Elemental Specrtoscopy, Electrical Borehole Image and Core Data Analysis, of the Unconventional Reservoirs in Kra Al Maru Field, West Kuwait","authors":"M. F. Shehab El Dein, K. Nguyen, M. Dasma, Said Beshry Mohamed, R. Quttainah","doi":"10.2118/213223-ms","DOIUrl":"https://doi.org/10.2118/213223-ms","url":null,"abstract":"\u0000 Najmah-Sargelu formations are unconventional reservoirs in West Kuwait in deep section of Kra Al Maru field. Various options were introduced to perform a petrophysical characterization of these unconventional reservoirs. Since a robust petrophysical model is critical for accurate reservoir characterization, a key objective of the current study was to obtain reliable well logging data that could support reservoir modeling and early wellsite decisions. Consequently, the logging program included conventional open hole logs, nuclear magnetic resonance (NMR), and elemental spectroscopy. The scope of the work is to assimilate data from the log sand generate a single integrated petrophysical model of the reservoir.\u0000 The organic shale petrophysics (OSP) was applied to provide petrophysical evaluation based on triple-combo data that has been integrated with advanced logs and core data analysis. The porosity partioning was obtained from NMR data. A detailed mineralogy and organic content were obtained from the geochemical spectroscopy logging. The most relevant results of the petrophysical analysis in this work was to improve fluid saturation analysis using OSP. Kerogen identified with the OSP analysis and the NMR under call porosity were in good agreement. The occurrence of kerogen was supported by the presence of redox sensitive elements, such as uranium, nickel, and molybdenum from core XRF data anlysis.\u0000 Borehole Image used to identify and characterize types and density of fractures, which contribute to enhance porosity and permeability of these tight reservoirs. A geochemical tool has been designed and developed for the precise determination of formation mineralogy, and lithology, as well as the identification of total organic carbon (TOC).\u0000 This work proves that the OSP analysis integrated with Core analysis, NMR data is a key in the petrophysical evaluation of unconventional reservoirs including the water saturation. These results, along with geochemical elemental spectroscopy and Electrical Borehole Image analysis, can be used to obtain a more precise petrophysical evaluation.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121483715","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":"Optimum Design for Proppant Fracturing to Unlock Oil Potential in a Marginal Low Quality Burgan Sands in the Greater Burgan Field","authors":"O. Al-Zankawi, Dunya Jafaar, S. Al-Kandari, M. Yaser, R. Prakash","doi":"10.2118/213717-ms","DOIUrl":"https://doi.org/10.2118/213717-ms","url":null,"abstract":"\u0000 In Greater Burgan Field, Burgan formation is the main oil producing reservoir since the start of oil production and with the reservoir mostly depleted, the focus in the asset team is now on the lower quality Upper Burgan (BGSU) sands with substantial remaining oil. In view of this, a multidisciplinary team is formed to evaluate opportunities to stimulate the BGSU reservoir, establish and sustain production from this reservoir to meet the production targets. The objective is to unlock potential in these tight sands especially targeting to revive old wells back which have drained the underlaying BGSM sands and have significant opportunities in the BGSU. The best way to exploit the resource potential of BGSU for its remaining oil is through hydraulic fracturing technology with an emphasis of its implementation via a thorough review of reservoir, well and completion data maximizing wellbore utilization and minimizing CAPEX investment.\u0000 The review involves screening a batch of wells with low rock quality and low permeability, away from heavy oil zones and above bubble point pressure, with good shale barrier beneath to avoid fracture propagating into the underlying aquifer. In total, about 100 wells are reviewed from across the Greater Burgan Field for this exercise. Latest reservoir pressure and oil saturation maps for the target BGSU reservoir, built in-house by the asset technical team, are being used to identify wells for potential hydraulic fracturing implementation. Upon a review of historical Proppant fracturing jobs that were performed in five wells in 2015-16 in the BGSU sands, it was summarized that there was a substantial increment to the well productivity, in some cases up to four folds. After the review, detailed numerical well modeling of these five wells is performed with and without fracturing showed that well productivity increase by 2 to 3 times for most of the wells. Although the well productivity improved post stimulation, the wells had high drawdown pressures which resulted in early water breakthrough in few wells.\u0000 An optimum well productivity can be achieved with large proppant volume placement in the reservoir to connect with the sands away from the wellbore. However, with large volumes there is significant risk of frac propagating \"out of zone\" increasing the risk of early water breakthrough. Presence of a shale barrier above and below the target zone is an important criterion in candidate selection and design the proppant volume to keep the fracture growth within the target zones and not reach to the zones, especially the underlying BGSM formation, having water.\u0000 With the lessons-learnt from the past fracturing jobs, detailed modeling and simulation of well performance, a refined list of potential hydraulic fracturing candidates can be generated combined with advancements in the fracturing technology which will greatly enhance the success probability of the stimulation with maximizing well productivity. The successful implem","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131636764","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":"Automated Geomechanics Modelling Workflow Supports Real-Time Decision Making and Risk Mitigation in Challenging Horizontal Wells","authors":"Arnott Dorantes, Nata Franco, Rawan AlSameen, S. Amer, F. Karpfinger, Mauricio Corona, Mansoor Abdul Kader","doi":"10.2118/213308-ms","DOIUrl":"https://doi.org/10.2118/213308-ms","url":null,"abstract":"Drilling in KSA with a 15 rigs fleet under LSTK project allows the implementation of technologies to reduce the exposure to drilling hazards and reduce the NPT and well costs. Geomechanics in real time requires multidiscipline team and various software to be run in real time. In the case of KSA drilling long lateral section for gas reservoir with high porosity increases the risk of differential stuck pipe events.\u0000 During the planning phase with a given trajectory it is possible to construct a predrill model which identifies the hazards associated to the wellbore stability information. This predrill model is passed to the monitoring center, which run the algorithms with the new datasets available while drilling allowing to identify and confirm the high porosity intervals and compare them with the initial plan, with the updated data enables the team to reassess the hazards to take the preventive actions.\u0000 This process has been part of the real time portfolio tools during the last 8 months. The collaboration between the monitoring center and geomechanics allows us to identify the critical intervals, bore hole conditions, wellbores instability, porosity and provide a clear map for high-medium-low differential sticking risk.\u0000 This information is well communicated using internal communication protocols that involves from the Drilling Analyst, Geomechanics, Well Engineer, Drilling Superintendent and all the team in the rig, allowing them to define clear strategies for drilling ang tripping. A set of best drilling practices has been reviewed by our experts as such as, connection practices, sticky tendency test, maximum overpull, tripping speeds, connection times, maximum time for bha static, backreaming procedures among others that are properly monitored and analyzed in real time in the monitoring center. In case of any deviation from the agreed an automated warning system is activated and informs the team the deviation and the risk associated.\u0000 The conjunction in between the geomechanics predrill model integrated to the monitoring center workflows creates a unique interaction of disciplines that understand and predict the risk and how to react to avoid stuck pipe events. The complexity is only solved when digital combines with an effective communication protocol and all the stake holders are aligned with the same objective. The reduction of NPT caused for stuck pipe events has been significantly since the workflow was put in place.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132566714","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 Comparison of Machine Learning Algorithms for Rate of Penetration Prediction for Directional Wells","authors":"Chengxi Li, Pengyu Cheng, Chris Cheng","doi":"10.2118/213321-ms","DOIUrl":"https://doi.org/10.2118/213321-ms","url":null,"abstract":"\u0000 One of the biggest challenges facing oil and gas companies is to lower the cost of drilling operations. The most critical parameter affecting drilling cost is the rate of penetration (ROP). Improving the ROP and reducing the drilling cycle can be significant for companies to reduce drilling costs and risks, thus enhancing market competitiveness. In the present study, we evaluate the accuracy and effectiveness of different machine learning algorithms for directional wells. We collect many field drilling datasets such as bit type, bit drilling time, revolutions per minute (RPM), weight on bit, torque, formation type, rock properties, and hydraulic and drilling mud properties. We input these data to the machine learning model to be trained, validated, and tested for predicting ROP. The machine learning models we used include linear regression, Artificial Neural Networks (ANN), Support Vector Machine (SVM), and Random Forest (RF) algorithms. In this study, we implement the Genetic Algorithm (GA) to optimize the hyper-parameters of the five machine learning algorithms. We also apply Savitzky-Golay (SG) smoothing filter to reduce the noise in the original dataset. We use accuracy metrics such as root mean square error, mean absolute error, and regression coefficient (R2) to compare the accuracy of several machine learning models. At last, we select the best-performing algorithm as the prediction tool for ROP. We conduct 50 cases for each machine learning model, where we evaluate the performance of the models and measure the time required for the models to be trained for the prediction tasks. The comparative study shows that implementing the GA optimization algorithm increased the accuracy of individual ROP models. We find that optimizing only a few hyper-parameters can significantly improve the machine models’ accuracy. We also compare the results from the model trained by the data processed with the SG smoothing filter with those trained by the original data. The study demonstrates that the SG algorithm effectively improves the accuracy of the machine learning models. Among the four machine learning models, ANN has the highest accuracy after GA optimization, reaching 97% on average. The overall training time for all four algorithms is between two and four minutes, considered a reasonable time frame for a real-time training and prediction task. We compare several machine learning methods’ accuracies in predicting ROP in real-time. We find that ML-based prediction models, especially ANN with hyper-parameters optimized by Genetic Algorithm, can accurately predict ROP in real-time and provide the operator with suggestions for appropriate measures.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132229339","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 the 2D 3D Plastic Volumetric Strain Around a Borehole Using Elastoplastic and Thermo-Elastoplastic Modeling Approaches","authors":"O. Hamid, Rowa Tawfiq","doi":"10.2118/213298-ms","DOIUrl":"https://doi.org/10.2118/213298-ms","url":null,"abstract":"\u0000 The applied forces on the wellbore axis lead to stress and strain concentration around it. These resultant stresses and strains will develop in the preferred orientation depending on the stress fault regime and will cause a rock failure in that direction. When these forces exceed the strength of the mechanical strength of the formation, the rock will fail otherwise, the yielded zones will be developed. The objective of this study is to model these yielded zones using elastoplastic and thermo-elastoplastic modeling approaches.\u0000 The finite element modeling (FEM) approach model will be used to predict the development of the yielded zone in terms of plastic volumetric strain. The Drücker-Prager (DP) and Mohr-Coulomb (M-C) failure criterion were used to characterize rock failure. Rock mechanical properties of tight sandstone formation, in-situ stresses, formation pressure, drilling mud weight properties, and temperature together with borehole information were used as input parameters. Different mud weight, rock strength, and temperature were used for sensitivity analysis.\u0000 2D/3D volumetric strain and yielded zones have been modeled around a borehole. The results showed the sensitivity of rock strength, mud weight density, and temperature variation on the size of the damage zones. The normalized yielded zone (NYZ) for all simulations was evaluated, while the critical NYZ results of one were plotted to quantify the degree of damage around the borehole.\u0000 The role of geomechanics in the damage mechanics has been analyzed by studying the rock failure mechanism using Mohr-Coulomb and Drücker-Drager failure criterion. This study uses elastoplastic and thermo-elastoplastic modeling approaches to evaluate the potential yielded failure around a borehole. The yielded zone sensitivity analysis showed that these potential failures depend on the geomechanical parameters, drilling fluid properties, and temperature differential between these fluids and reservoir rock. This work will provide strong recommendations for the controllable parameters such as mud weight density and drilling mechanics to avoid the development of damage zones around the wellbores.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132289269","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":"In-line Partition Coefficient Measurement for Oil Field Tracers Utilizing Microfluidic Mixing Chip","authors":"Sehoon Chang, Gawain Thomas, Wei Wang","doi":"10.2118/213459-ms","DOIUrl":"https://doi.org/10.2118/213459-ms","url":null,"abstract":"\u0000 Oil field tracers are extensively utilized to evaluate and understand production data, pressure test analysis, inter-well connectivity, as well as enhanced oil recovery (EOR). One of the important properties of the tracer is the partition coefficient, which is the ratio of tracer concentrations in the oil and water phases at equilibrium state. Therefore, partitioning coefficient measurement is necessary for both partitioning and non-partitioning tracer development. However, the current technology for the measurement requires large quantities of organic solvent and long measurement time. Here, we developed the fast, portable, low-solvent and sustainable device so called in-line partition coefficient measurement system for oil field tracers utilizing a microfluidic chip and oil/water separator.\u0000 To minimize the amount of sample, solvent, measurement time and cost, microfluidic technology has been used for the miniaturization of the partition coefficient measurement. Utilizing microfluidic chip and oil/water separator decreased the characteristic length of diffusion and therefore time required to complete the experiment. The in-line optical property measurement such as UV-Vis, fluorescence, or time-resolved fluorescence has been used for the tracer in water solution at various concentrations for the reference curves. The tracer in water solution was injected into the teardrop microfluidic mixing chip using syringe pump and the crude oil was injected concurrently using a separate syringe pump. Fluid samples were thoroughly mixed in microfluidic mixing chip then the solution flows into a membrane-based oil/water phase separator system (Zaiput, inc). After separation, only the water phase flows into in-line HPLC UV-Vis or fluorescence, time-resolved fluorescence detector.\u0000 The measurement results of both partitioning and non- partitioning tracers showed similar to the calculated value of the partitioning coefficient and the value from the literature that used the conventional shake-flask method. Especially, the in-line partition coefficient measurement takes only tens of minutes, which is much faster than the conventional shake-flask method (couple of days). Also, the developed measurement is cost-effective saving a large amount of expensive organic solvent utilized for the conventional measurement. The developed in-line microfluidic mixing chip aided partitioning coefficient measurement process facilitates measurement of essential properties of oil field chemicals because we can estimate the value simply by switching from the flow of water itself to the flow of mixture solution.\u0000 The developed method demonstrates an improvement on conventional partitioning coefficient measurements for a variety of oil field tracers in terms of sustainability. The microfluidic in-line partition coefficient measurement not only minimizes cost and human intervention, but also provides enhanced sample analysis throughput. This technology is ready to be validated for the","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132898675","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":"Enhanced Field Sustainable Oil Production Rate Forecast Using Integrated Asset Operating Model for Production Efficiency Improvement","authors":"Erismar Rubio, N. Reddicharla, Mayada Ali Sultan Ali, Mohamed Ali AL Attar, R. Davila, Avnish Kumar","doi":"10.2118/213641-ms","DOIUrl":"https://doi.org/10.2118/213641-ms","url":null,"abstract":"\u0000 As hydrocarbon fields are maturing, field sustainable oil production rate (FSOPR) assurance is a challenge for operators to deliver the demands while adhering reservoir management guidelines after accounting for all well & facility downtimes and system inefficiencies. As part of digital transformation journey, ADNOC Onshore has embarked on an initiative to automate FSOPR forecast while eliminating inefficiencies in current process, standardization, leveraging robust data integration and analytics.\u0000 FSOPR forecast is probably the most complex task performed by oil companies as involved the orchestration of all support and technical departments from the field to the terminal. Effective FSOPR estimation is an integrated effort from reservoir/petroleum engineering, drilling/well services, operations, oil movement, planning, maintenance, engineering and reliability teams. The assurance process requires a structured and integrated approach of data gathering, review, and simulations to produce a reliable forecasts. Before, data/process integration and reporting was time-consuming representing a real challenge as it was managed through manual data-loading in spreadsheets & emails with low visibility to all stakeholders. Now FSOPR is estimated using up-to-date well/network models, including contribution from newly drilled & well reactivation plans, well-performance deterioration and production restoration from field activities. Similarly planned/unplanned losses from reservoir management (RM), field activities & facility maintenance jobs are optimized through the solution, offering integration with reliability models. The automated web-page solution leverages business process engine enabled by intelligent data integration from various workflow elements and allows all stakeholders to collaborate in one portal to have on single version of the truth. The data abstraction layer retrieves information and presented in the solution from legacy systems, production modelling workflows and SAP. The base plan & optimization cases are tracked by process health KPIs and approved using Business process management workflow.\u0000 FSOPR automation system has been successfully piloted in one ADNOC Onshore assets. This automation was an enabler for better planning and scheduling of maintenance and RM activities and also provides assurance of monthly oil quota achievement by highlighting early potential threats that can hinder the realization of the FSOPR plan, thus corrective action can be taken on time considering best RM practices. The whole process of data gathering, planning, activity scheduling, optimization and approval has been reduced by 60% along with a more rigorous and errorless process. The added value besides enhancing efficiency, it has minimized well downtime and production deferment avoidance of 1-2%. This automation paved the path for FSOPR assurance process standardization across company portfolio of assets.\u0000 The initiative is aligned with ADNOC digital tran","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"443 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132931977","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":"Thermal Investigation of ESP Motor Temperature Rise with Focus on Heavy Oil Applications","authors":"K. Najmi, R. Teves, Nahun Zarate Guzman, David Zhu, Howard Thompson, Shawn N. Gunter","doi":"10.2118/213627-ms","DOIUrl":"https://doi.org/10.2118/213627-ms","url":null,"abstract":"The generated heat inside a motor is one of the main factors limiting a motor operation. Electrical submersible pump (ESP) motor is not an exception from this limiting factor. Running an ESP motor above the rated temperature can cause serious mechanical and electrical damages to the motor and finally result in motor failure. Therefore, an accurate prediction of motor internal temperature can help not only with expansion of ESP operating envelope, enhancement of motor reliability and run life, but also reduces operating costs and power consumption (carbon reduction).\u0000 In addition to industry wide challenges to cool down motors, ESP motors have certain characteristics that make motor thermal management more challenging. ESP motors generally generate a lot of heat and heat dissipation is subject to environmental conditions (such as dynamic well multiphase fluid conditions, well bore geometry and chemistry etc.) that are not easily manageable.","PeriodicalId":396949,"journal":{"name":"Day 1 Sun, February 19, 2023","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122358023","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}