R. Santoso, Xupeng He, M. AlSinan, H. Kwak, H. Hoteit
Automatic fracture recognition from borehole images or outcrops is applicable for the construction of fractured reservoir models. Deep learning for fracture recognition is subject to uncertainty due to sparse and imbalanced training set, and random initialization. We present a new workflow to optimize a deep learning model under uncertainty using U-Net. We consider both epistemic and aleatoric uncertainty of the model. We propose a U-Net architecture by inserting dropout layer after every "weighting" layer. We vary the dropout probability to investigate its impact on the uncertainty response. We build the training set and assign uniform distribution for each training parameter, such as the number of epochs, batch size, and learning rate. We then perform uncertainty quantification by running the model multiple times for each realization, where we capture the aleatoric response. In this approach, which is based on Monte Carlo Dropout, the variance map and F1-scores are utilized to evaluate the need to craft additional augmentations or stop the process. This work demonstrates the existence of uncertainty within the deep learning caused by sparse and imbalanced training sets. This issue leads to unstable predictions. The overall responses are accommodated in the form of aleatoric uncertainty. Our workflow utilizes the uncertainty response (variance map) as a measure to craft additional augmentations in the training set. High variance in certain features denotes the need to add new augmented images containing the features, either through affine transformation (rotation, translation, and scaling) or utilizing similar images. The augmentation improves the accuracy of the prediction, reduces the variance prediction, and stabilizes the output. Architecture, number of epochs, batch size, and learning rate are optimized under a fixed-uncertain training set. We perform the optimization by searching the global maximum of accuracy after running multiple realizations. Besides the quality of the training set, the learning rate is the heavy-hitter in the optimization process. The selected learning rate controls the diffusion of information in the model. Under the imbalanced condition, fast learning rates cause the model to miss the main features. The other challenge in fracture recognition on a real outcrop is to optimally pick the parental images to generate the initial training set. We suggest picking images from multiple sides of the outcrop, which shows significant variations of the features. This technique is needed to avoid long iteration within the workflow. We introduce a new approach to address the uncertainties associated with the training process and with the physical problem. The proposed approach is general in concept and can be applied to various deep-learning problems in geoscience.
{"title":"Uncertainty Quantification and Optimization of Deep Learning for Fracture Recognition","authors":"R. Santoso, Xupeng He, M. AlSinan, H. Kwak, H. Hoteit","doi":"10.2118/204863-ms","DOIUrl":"https://doi.org/10.2118/204863-ms","url":null,"abstract":"\u0000 Automatic fracture recognition from borehole images or outcrops is applicable for the construction of fractured reservoir models. Deep learning for fracture recognition is subject to uncertainty due to sparse and imbalanced training set, and random initialization. We present a new workflow to optimize a deep learning model under uncertainty using U-Net. We consider both epistemic and aleatoric uncertainty of the model. We propose a U-Net architecture by inserting dropout layer after every \"weighting\" layer. We vary the dropout probability to investigate its impact on the uncertainty response. We build the training set and assign uniform distribution for each training parameter, such as the number of epochs, batch size, and learning rate. We then perform uncertainty quantification by running the model multiple times for each realization, where we capture the aleatoric response. In this approach, which is based on Monte Carlo Dropout, the variance map and F1-scores are utilized to evaluate the need to craft additional augmentations or stop the process. This work demonstrates the existence of uncertainty within the deep learning caused by sparse and imbalanced training sets. This issue leads to unstable predictions. The overall responses are accommodated in the form of aleatoric uncertainty. Our workflow utilizes the uncertainty response (variance map) as a measure to craft additional augmentations in the training set. High variance in certain features denotes the need to add new augmented images containing the features, either through affine transformation (rotation, translation, and scaling) or utilizing similar images. The augmentation improves the accuracy of the prediction, reduces the variance prediction, and stabilizes the output. Architecture, number of epochs, batch size, and learning rate are optimized under a fixed-uncertain training set. We perform the optimization by searching the global maximum of accuracy after running multiple realizations. Besides the quality of the training set, the learning rate is the heavy-hitter in the optimization process. The selected learning rate controls the diffusion of information in the model. Under the imbalanced condition, fast learning rates cause the model to miss the main features. The other challenge in fracture recognition on a real outcrop is to optimally pick the parental images to generate the initial training set. We suggest picking images from multiple sides of the outcrop, which shows significant variations of the features. This technique is needed to avoid long iteration within the workflow. We introduce a new approach to address the uncertainties associated with the training process and with the physical problem. The proposed approach is general in concept and can be applied to various deep-learning problems in geoscience.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73690579","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 world is currently experiencing a rude awakening because of the COVID-19 pandemic and in a matter of months businesses averse to trust the benefits of remote working have been compelled to adapt. This advantage has enabled many Human Resource (HR) Professionals to revisit the dreaded topic of flexible working, as the new normal has shown that it is not where you work but the work you produce that matters. Ironically, the age-old question of work-life balance surfaces as individuals search for the purpose of life as the pandemic brings everyone to their knees and philosophically people question what exactly is this balance. For HR Professionals this question is not personal but a matter of their profession in providing companies with a wider lens to understand that in order to remain competitive they need to adapt to change. One of the ways is to develop an open mindset and flexibility to revise their policies on types of flexible working, which offers work-life balance and positively impacts their ability to retain and attract highly skilled talent. This article examines the concept of Digital Nomadism as one of the radical yet realistic ways to achieve work-life balance. Digital Nomadism puts a new spin on work arrangements and is a movement of highly mobile workers who dictate where they work, how they adapt to the demands of work to suit their lifestyle and find balance; with digital technologies. The concept has been around since 2014, the history of nomadism even longer but what is new, and why this subject adds value is the ingenuity of technology, how it makes this way of working a reality and the increasing numbers of digital nomads. The research suggests that approximately several hundred thousand of digital nomads exist throughout the world and numbers continues to rise due to globalization and the need for talent to be flexible with their lifestyles and work. Interestingly, while many companies are convinced of the technological disruptors and how it changes the face of work from a technical perspective, the flexibility of work patterns remains a hard sell in some cases. Consequently, recruiting for talent, employment contracts and the way work is organized, remains the same and lacks flexibility. This limits the opportunity to remain competitive, retain or attract top talent and drive innovation at all angles of the business. This paper will confirm whether the solution to work-life balance is the notion of digital nomadism, detailing how it works, its benefits and issues, with the intention to offer an option to forward thinking companies, reasons to adapt their flexible working policies.
{"title":"Is Digital Nomadism the Answer to Work Life Balance?","authors":"Nicole Gustave, Abdullah AlArfaj","doi":"10.2118/204874-ms","DOIUrl":"https://doi.org/10.2118/204874-ms","url":null,"abstract":"\u0000 The world is currently experiencing a rude awakening because of the COVID-19 pandemic and in a matter of months businesses averse to trust the benefits of remote working have been compelled to adapt. This advantage has enabled many Human Resource (HR) Professionals to revisit the dreaded topic of flexible working, as the new normal has shown that it is not where you work but the work you produce that matters.\u0000 Ironically, the age-old question of work-life balance surfaces as individuals search for the purpose of life as the pandemic brings everyone to their knees and philosophically people question what exactly is this balance. For HR Professionals this question is not personal but a matter of their profession in providing companies with a wider lens to understand that in order to remain competitive they need to adapt to change. One of the ways is to develop an open mindset and flexibility to revise their policies on types of flexible working, which offers work-life balance and positively impacts their ability to retain and attract highly skilled talent. This article examines the concept of Digital Nomadism as one of the radical yet realistic ways to achieve work-life balance.\u0000 Digital Nomadism puts a new spin on work arrangements and is a movement of highly mobile workers who dictate where they work, how they adapt to the demands of work to suit their lifestyle and find balance; with digital technologies. The concept has been around since 2014, the history of nomadism even longer but what is new, and why this subject adds value is the ingenuity of technology, how it makes this way of working a reality and the increasing numbers of digital nomads. The research suggests that approximately several hundred thousand of digital nomads exist throughout the world and numbers continues to rise due to globalization and the need for talent to be flexible with their lifestyles and work.\u0000 Interestingly, while many companies are convinced of the technological disruptors and how it changes the face of work from a technical perspective, the flexibility of work patterns remains a hard sell in some cases. Consequently, recruiting for talent, employment contracts and the way work is organized, remains the same and lacks flexibility. This limits the opportunity to remain competitive, retain or attract top talent and drive innovation at all angles of the business. This paper will confirm whether the solution to work-life balance is the notion of digital nomadism, detailing how it works, its benefits and issues, with the intention to offer an option to forward thinking companies, reasons to adapt their flexible working policies.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73881672","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}
Chong Cao, Linsong Cheng, Xiangyang Zhang, P. Jia, Wenpei Lu
Permeability changes in the weakly consolidated sandstone formation, caused by sand migration, has a serious impact on the interpretation of well testing and production prediction. In this article, a two-zone comprehensive model is presented to describe the changes in permeability by integrating the produced sand, stress sensitivity characteristics. In this model, inner zone is modeled as a higher permeability radial reservoir because of the sand migration, while the outer zone is considered as a lower permeability reservoir. Besides, non-Newtonian fluid flow characteristics are considered as threshold pressure gradient in this paper. As a result, this bi-zone comprehensive model is built. The analytical solution to this composite model can be obtained using Laplace transformation, orthogonal transformation, and then the bottomhole pressure in real space can be solved by Stehfest and perturbation inversion techniques. Based on the oilfield cases validated in the oilfield data from the produced sand horizontal well, the flow regimes analysis shows seven flow regimes can be divided in this bi-zone model considering stress sensitive. In addition, the proposed new model is validated by the compassion results of traditional method without the complex factors. Besides, the effect related parameters of stress sensitivity coefficient, skin factor, permeability ratio and sanding radius on the typical curves of well-testing are analyzed. This work introduces two-zone composite model to reflect the variations of permeability caused by the produced sand in the unconsolidated sandstone formation, which can produce great influence on pressure transient behavior. Besides, this paper can also provide a more accurate reference for reservoir engineers in well test interpretation of loose sandstone reservoirs.
{"title":"A Comprehensive Model Integrating the Stress Sensitivity for Pressure Transient Behavior Study on the Two-Zone System for Offshore Loose Sandstone Reservoirs","authors":"Chong Cao, Linsong Cheng, Xiangyang Zhang, P. Jia, Wenpei Lu","doi":"10.2118/204793-ms","DOIUrl":"https://doi.org/10.2118/204793-ms","url":null,"abstract":"\u0000 Permeability changes in the weakly consolidated sandstone formation, caused by sand migration, has a serious impact on the interpretation of well testing and production prediction. In this article, a two-zone comprehensive model is presented to describe the changes in permeability by integrating the produced sand, stress sensitivity characteristics. In this model, inner zone is modeled as a higher permeability radial reservoir because of the sand migration, while the outer zone is considered as a lower permeability reservoir. Besides, non-Newtonian fluid flow characteristics are considered as threshold pressure gradient in this paper. As a result, this bi-zone comprehensive model is built. The analytical solution to this composite model can be obtained using Laplace transformation, orthogonal transformation, and then the bottomhole pressure in real space can be solved by Stehfest and perturbation inversion techniques. Based on the oilfield cases validated in the oilfield data from the produced sand horizontal well, the flow regimes analysis shows seven flow regimes can be divided in this bi-zone model considering stress sensitive. In addition, the proposed new model is validated by the compassion results of traditional method without the complex factors. Besides, the effect related parameters of stress sensitivity coefficient, skin factor, permeability ratio and sanding radius on the typical curves of well-testing are analyzed. This work introduces two-zone composite model to reflect the variations of permeability caused by the produced sand in the unconsolidated sandstone formation, which can produce great influence on pressure transient behavior. Besides, this paper can also provide a more accurate reference for reservoir engineers in well test interpretation of loose sandstone reservoirs.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83782746","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}
J. Wrobel-daveau, Rodney Barracloughy, Sarah Laird, Nicholas Matthies, Bilal Saeed, Khalid Shoaib, Zaheer Zafar
Exploration success in fold-and-thrust belts, like the Potwar petroleum province, is impacted by seismic imaging challenges and structural complexity. Success partly relies on the ability to validate subsurface models and model a range of properties, such as reservoir permeability. This is particularly important in the case of tight carbonate reservoirs such as the Eocene Sakesar Formation, where the recovery of economic quantities of hydrocarbons is conditioned by the presence of fracture-enhanced permeability. This requires the application of geological and geophysical modeling techniques to address these challenges, to minimize uncertainty and drive exploration success. The interpretation and structural validation of the Ratana structure presented here allows the proposal of a consistent and robust structural model even in areas of higher uncertainty in the data, such as along faults. The dynamically updatable, watertight, complex 3D structural framework created for the top Sakesar reservoir was used in combination with an assisted fault interpretation algorithm to characterize the fault and fracture pattern. The results showed a higher density of high amplitude fractures on the flanks of the structure rather than along the hinge. These results are supported by the incremental strain modeling based on the kinematic evolution of the structure. Together, this helped to characterize potential fracture corridors in areas of the seismic volume that previously proved challenging for human driven interpretation. Our results allow us to reduce the uncertainty related to the geometrical characteristics of the reservoir and provide insights into potential exploration well targets to maximize chances of success, suggesting that permeability and hydrocarbon flow may be higher at the margins of the Ratana structure, and not at the crest, which was the focus of previous exploration and production efforts.
{"title":"Insights on Fractured Domains in Reservoirs Resulting from Modeling Complex Geology/Structures - Case Study of the Ratana Field in the Potwar Basin, Pakistan","authors":"J. Wrobel-daveau, Rodney Barracloughy, Sarah Laird, Nicholas Matthies, Bilal Saeed, Khalid Shoaib, Zaheer Zafar","doi":"10.2118/204737-ms","DOIUrl":"https://doi.org/10.2118/204737-ms","url":null,"abstract":"Exploration success in fold-and-thrust belts, like the Potwar petroleum province, is impacted by seismic imaging challenges and structural complexity. Success partly relies on the ability to validate subsurface models and model a range of properties, such as reservoir permeability. This is particularly important in the case of tight carbonate reservoirs such as the Eocene Sakesar Formation, where the recovery of economic quantities of hydrocarbons is conditioned by the presence of fracture-enhanced permeability. This requires the application of geological and geophysical modeling techniques to address these challenges, to minimize uncertainty and drive exploration success. The interpretation and structural validation of the Ratana structure presented here allows the proposal of a consistent and robust structural model even in areas of higher uncertainty in the data, such as along faults. The dynamically updatable, watertight, complex 3D structural framework created for the top Sakesar reservoir was used in combination with an assisted fault interpretation algorithm to characterize the fault and fracture pattern. The results showed a higher density of high amplitude fractures on the flanks of the structure rather than along the hinge. These results are supported by the incremental strain modeling based on the kinematic evolution of the structure. Together, this helped to characterize potential fracture corridors in areas of the seismic volume that previously proved challenging for human driven interpretation. Our results allow us to reduce the uncertainty related to the geometrical characteristics of the reservoir and provide insights into potential exploration well targets to maximize chances of success, suggesting that permeability and hydrocarbon flow may be higher at the margins of the Ratana structure, and not at the crest, which was the focus of previous exploration and production efforts.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76356952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Temizel, C. H. Canbaz, Hasanain Alsaheib, Kirill Yanidis, Karthik Balaji, Nouf Alsulaiman, Mustafa A. Basri, Nayif Jama
EUR (Estimated Ultimate Recovery) forecasting in unconventional fields has been a tough process sourced by its physics involved in the production mechanism of such systems which makes it hard to model or forecast. Machine learning (ML) based EUR prediction becomes very challenging because of the operational issues and the quality of the data in historical production. Geology-driven EUR forecasting, once established, offers EUR forecasting solutions that is not affected by operational issues such as shut-ins. This study illustrates the overall methodology in intelligent fields with real-time data flow and model update that enables optimization of well placement in addition to EUR forecasting for individual wells. A synthetic but realistic model which demonstrates the physics is utilized to generate input data for training the ML model where the spatially-distributed geological parameters including but not limited to porosity, permeability, saturation have been used to describe the production values and ultimately the EUR. The completion is given where the formation characteristics vary in the field that lead to location-dependent production performance leading to well placement optimization based on EUR forecasting from the geological parameters. The algorithm not only predicts the EUR of an individual well and makes decision for the optimum well locations. As the training model includes data of interfering wells, the model is capable of capturing the pattern in the well interference. Even though a synthetic but realistic reservoir model is constructed to generate the data for the aim of assisting the ML model, in practice, it is not an easy task to (1) obtain the input parameters to build a robust reservoir simulation model and (2) understanding and modeling of physics of fluid flow and production in unconventionals is a complex and time-consuming task to build real models. Thus, data-driven approaches like this help to speed up reservoir management and development decisions with reasonable approximations compared to numerical models and solutions. Application of machine learning in intelligent fields is also explained where the models are dynamically-updated and trained with the new data. Geology-driven EUR forecasting has been applied and relatively-new in the industry. In. this study, we are extending it to optimize well placement in intelligent fields in unconventionals beyond other existing studies in the literature.
{"title":"Geology-Driven EUR Forecasting in Unconventional Fields","authors":"C. Temizel, C. H. Canbaz, Hasanain Alsaheib, Kirill Yanidis, Karthik Balaji, Nouf Alsulaiman, Mustafa A. Basri, Nayif Jama","doi":"10.2118/204583-ms","DOIUrl":"https://doi.org/10.2118/204583-ms","url":null,"abstract":"\u0000 EUR (Estimated Ultimate Recovery) forecasting in unconventional fields has been a tough process sourced by its physics involved in the production mechanism of such systems which makes it hard to model or forecast. Machine learning (ML) based EUR prediction becomes very challenging because of the operational issues and the quality of the data in historical production. Geology-driven EUR forecasting, once established, offers EUR forecasting solutions that is not affected by operational issues such as shut-ins. This study illustrates the overall methodology in intelligent fields with real-time data flow and model update that enables optimization of well placement in addition to EUR forecasting for individual wells.\u0000 A synthetic but realistic model which demonstrates the physics is utilized to generate input data for training the ML model where the spatially-distributed geological parameters including but not limited to porosity, permeability, saturation have been used to describe the production values and ultimately the EUR. The completion is given where the formation characteristics vary in the field that lead to location-dependent production performance leading to well placement optimization based on EUR forecasting from the geological parameters. The algorithm not only predicts the EUR of an individual well and makes decision for the optimum well locations. As the training model includes data of interfering wells, the model is capable of capturing the pattern in the well interference.\u0000 Even though a synthetic but realistic reservoir model is constructed to generate the data for the aim of assisting the ML model, in practice, it is not an easy task to (1) obtain the input parameters to build a robust reservoir simulation model and (2) understanding and modeling of physics of fluid flow and production in unconventionals is a complex and time-consuming task to build real models. Thus, data-driven approaches like this help to speed up reservoir management and development decisions with reasonable approximations compared to numerical models and solutions. Application of machine learning in intelligent fields is also explained where the models are dynamically-updated and trained with the new data.\u0000 Geology-driven EUR forecasting has been applied and relatively-new in the industry. In. this study, we are extending it to optimize well placement in intelligent fields in unconventionals beyond other existing studies in the literature.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86533191","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}
H. Zhong, Xin Gao, Z. Qiu, Weian Huang, Wenlei Liu, Jiaxin Ma, Shusen Li
Due to the rapid degradation of conventional biopolymer or synthetic polymeric additives at high temperature (HT) or ultra-high temperatures (ultra-HT), effective control of water-based drilling fluid filtration in HT or Ultra-HT environment is still a great challenge in drilling operation. β-cyclodextrin polymer microspheres (β-CPMs), generally using for drug release and waste water treatment, are evaluated as environmentally friendly ultra-HT filtration reducer. The impact of the microspheres on water-based drilling fluids’ properties including rheology and filtration prior to and after hot rolling at different temperatures ranging from 120 to 240°C was investigated. The high temperature and high pressure (HTHP) filtration properties of the microspheres compared to several commercial high temperature filtration reducers were conducted according to the API recommended procedures. The filtration controlling mechanism was analyzed from zeta potential measurement, particle size distribution measurement, and scanning electron microscope observation of filter cake. The results indicated that the β-CPMs exhibited peculiar filtration behavior differently from conventional additives. When the hot rolling temperature was below 160℃, β-CPMs performed a 30% filtration reduction at 1 w/v% content in comparison with control sample. Once the hot rolling temperature was above 160℃, the capacity of filtration control was further improved with increasing temperatures. This is contrast with conventional filtration reducers that the filtration control capacity deteriorate with increasing temperatures. The microspheres still exhibited superior filtration control after exposure to 240℃. Furthermore, β-CPMs showed little effect on the drilling fluid's rheology. When the temperature was below 160℃, the filtration reduction was obtained by water absorption and swelling of β-CPMs. When the temperature was above 160℃, hydrothermal reaction occurred for β-CPMs. Numerous micro- and nano-sized carbon spheres formed, which bridge across micro and nanopores within filter cake and reduce the filter cake permeability effectively. When the temperature was higher than 160℃, hydrothermal reaction occurs. Carbon spheres generated by the hydrothermal degradation of the β-CPMs, which are responsible for the effective filtration control. The hydrothermal reaction changes the adverse effect of high temperature into favorable improvement of filtration control, which provides a novel avenue for HT and ultra-HT filtration control. The β-CPMs show potential application in deep well drilling as environmental friendly and high temperature filtration reducers.
{"title":"Minimization of Ultra-High Temperature Filtration Loss for Water-Based Drilling Fluid with ß-Cyclodextrin Polymer Microspheres","authors":"H. Zhong, Xin Gao, Z. Qiu, Weian Huang, Wenlei Liu, Jiaxin Ma, Shusen Li","doi":"10.2118/204763-ms","DOIUrl":"https://doi.org/10.2118/204763-ms","url":null,"abstract":"\u0000 Due to the rapid degradation of conventional biopolymer or synthetic polymeric additives at high temperature (HT) or ultra-high temperatures (ultra-HT), effective control of water-based drilling fluid filtration in HT or Ultra-HT environment is still a great challenge in drilling operation.\u0000 β-cyclodextrin polymer microspheres (β-CPMs), generally using for drug release and waste water treatment, are evaluated as environmentally friendly ultra-HT filtration reducer. The impact of the microspheres on water-based drilling fluids’ properties including rheology and filtration prior to and after hot rolling at different temperatures ranging from 120 to 240°C was investigated. The high temperature and high pressure (HTHP) filtration properties of the microspheres compared to several commercial high temperature filtration reducers were conducted according to the API recommended procedures. The filtration controlling mechanism was analyzed from zeta potential measurement, particle size distribution measurement, and scanning electron microscope observation of filter cake.\u0000 The results indicated that the β-CPMs exhibited peculiar filtration behavior differently from conventional additives. When the hot rolling temperature was below 160℃, β-CPMs performed a 30% filtration reduction at 1 w/v% content in comparison with control sample. Once the hot rolling temperature was above 160℃, the capacity of filtration control was further improved with increasing temperatures. This is contrast with conventional filtration reducers that the filtration control capacity deteriorate with increasing temperatures. The microspheres still exhibited superior filtration control after exposure to 240℃. Furthermore, β-CPMs showed little effect on the drilling fluid's rheology. When the temperature was below 160℃, the filtration reduction was obtained by water absorption and swelling of β-CPMs. When the temperature was above 160℃, hydrothermal reaction occurred for β-CPMs. Numerous micro- and nano-sized carbon spheres formed, which bridge across micro and nanopores within filter cake and reduce the filter cake permeability effectively.\u0000 When the temperature was higher than 160℃, hydrothermal reaction occurs. Carbon spheres generated by the hydrothermal degradation of the β-CPMs, which are responsible for the effective filtration control. The hydrothermal reaction changes the adverse effect of high temperature into favorable improvement of filtration control, which provides a novel avenue for HT and ultra-HT filtration control. The β-CPMs show potential application in deep well drilling as environmental friendly and high temperature filtration reducers.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86359572","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}
Downhole power harvesting is an enabling technology for a wide range of future production systems and applications, including self-powered downhole monitoring, downhole robotics, and wireless intelligent completions. This paper presents the field experience of an innovative energy harvesting system that was successfully deployed and tested in the harsh downhole conditions of an oil producer. There is a critical need for robust and reliable downhole power generation and storage technologies to push the boundaries of downhole sensing and control. This paper provides an analysis of available ambient energy sources in the downhole environment, and various energy harvesting techniques that can be employed to provide a reliable solution. Advantages and limitations of conventional technique like turbine are compared to advanced energy harvesting technologies. The power requirements and technical challenges related to different downhole applications have also been addressed. The field experience of the novel flow-based energy harvesting system are presented, including the details of both the lab and field prototype design, deployment and testing.
{"title":"Field Experience of an Innovative Downhole Energy Harvesting System","authors":"M. Arsalan, Jarl André Fellinghaug","doi":"10.2118/204592-ms","DOIUrl":"https://doi.org/10.2118/204592-ms","url":null,"abstract":"\u0000 Downhole power harvesting is an enabling technology for a wide range of future production systems and applications, including self-powered downhole monitoring, downhole robotics, and wireless intelligent completions. This paper presents the field experience of an innovative energy harvesting system that was successfully deployed and tested in the harsh downhole conditions of an oil producer.\u0000 There is a critical need for robust and reliable downhole power generation and storage technologies to push the boundaries of downhole sensing and control. This paper provides an analysis of available ambient energy sources in the downhole environment, and various energy harvesting techniques that can be employed to provide a reliable solution. Advantages and limitations of conventional technique like turbine are compared to advanced energy harvesting technologies. The power requirements and technical challenges related to different downhole applications have also been addressed. The field experience of the novel flow-based energy harvesting system are presented, including the details of both the lab and field prototype design, deployment and testing.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83480690","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}
Controlling the excessive water production from the high water cut gravel packing horizontal well is a challenge. The approach which uses regular packers or packers with ICD screens to control the unwanted water does not function well. This is mainly because of the length limitation of packers which will make the axial flow resistance insufficient. In this paper, a successful case that unwanted water is shutoff by using continuous pack-off particles with ICD screens (CPI) in the whole horizontal section in an offshore oilfield of Bohai bay is presented. The reservoir of this case is the bottom-water high viscosity reservoir. The process is to run 2 3/8" ICD screen string into the 4" screen string originally in place, then to pump the pack-off particles into the annulus between the two screens, and finally form the 360m tightly compacted continuous pack-off particle ring. The methodology behind the process is that the 2-3/8" ICD screens limit the flow rate into the pipes as well as the continuous pack-off particle ring together with the gravel ring outside the original 4" screens to prevent the water channeling into the oil zone along the horizontal section. This is the first time this process is applied in a high water cut gravel packed horizontal well. After the treatment, the water rate decreased from 6856BPD to 836.6BPD, the oil rate increased from 44BPD to 276.8BPD. In addition, the duration of this performance continued a half year until March 21, 2020. The key of this technology is to control the unwanted water by using the continuous pack-off particles instead of the parkers, which will bring 5 advantages, a) higher efficiency in utilizing the production interval; b) no need to find the water source and then fix it; c) the better ability to limit the axial flow; d) effective to multi-WBT (water break though) points and potential WBT points; e) more flexible for further workover. The technology of this successful water preventing case can be reference to other similar high water cut gravel packed wells. Also, it has been proved that the well completion approach of using CPI can have good water shutoff and oil incremental result. Considering the experiences of historical applications, CPI which features good sand control, water shutoff and anti-clogging is a big progress compared to the current completion technologies.
{"title":"A Successful Application of Continuous Pack-Off Technology to Water Shutoff Recompletion for High-WCT Gravel-Packed Horizontal Well","authors":"An Jiang, Yunpeng Li, Xinge Liu, Fengli Zhang, Tianhui Wang, Yuezhong Liu, Lianhe Han, Bailin Pei, Yingying Chen","doi":"10.2118/204838-ms","DOIUrl":"https://doi.org/10.2118/204838-ms","url":null,"abstract":"\u0000 \u0000 \u0000 Controlling the excessive water production from the high water cut gravel packing horizontal well is a challenge. The approach which uses regular packers or packers with ICD screens to control the unwanted water does not function well. This is mainly because of the length limitation of packers which will make the axial flow resistance insufficient.\u0000 \u0000 \u0000 \u0000 In this paper, a successful case that unwanted water is shutoff by using continuous pack-off particles with ICD screens (CPI) in the whole horizontal section in an offshore oilfield of Bohai bay is presented. The reservoir of this case is the bottom-water high viscosity reservoir. The process is to run 2 3/8\" ICD screen string into the 4\" screen string originally in place, then to pump the pack-off particles into the annulus between the two screens, and finally form the 360m tightly compacted continuous pack-off particle ring.\u0000 \u0000 \u0000 \u0000 The methodology behind the process is that the 2-3/8\" ICD screens limit the flow rate into the pipes as well as the continuous pack-off particle ring together with the gravel ring outside the original 4\" screens to prevent the water channeling into the oil zone along the horizontal section. This is the first time this process is applied in a high water cut gravel packed horizontal well. After the treatment, the water rate decreased from 6856BPD to 836.6BPD, the oil rate increased from 44BPD to 276.8BPD. In addition, the duration of this performance continued a half year until March 21, 2020.\u0000 \u0000 \u0000 \u0000 The key of this technology is to control the unwanted water by using the continuous pack-off particles instead of the parkers, which will bring 5 advantages, a) higher efficiency in utilizing the production interval; b) no need to find the water source and then fix it; c) the better ability to limit the axial flow; d) effective to multi-WBT (water break though) points and potential WBT points; e) more flexible for further workover. The technology of this successful water preventing case can be reference to other similar high water cut gravel packed wells. Also, it has been proved that the well completion approach of using CPI can have good water shutoff and oil incremental result. Considering the experiences of historical applications, CPI which features good sand control, water shutoff and anti-clogging is a big progress compared to the current completion technologies.\u0000","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"160 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86213984","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}
Samba Ba, M. Ignova, K. Mantle, Adrien Chassard, Tao Yu, Sylvain Chambon, Ziad Akkaoui, Lu Jiang, Richard Harmer, Olivia Barcelata, Jinsoo Kim, Mustapha Rhazaf
Today, directional drilling is considered a mix between art and science only performed by experts in the field. In this paper, we present an autonomous directional drilling framework using an industry 4.0 platform that is built on intelligent planning and execution capabilities and is supported by surface and downhole automation technologies to achieve consistently performing directional drilling operations accessible for easy remote operations. Intelligent planning builds on standard planning activities that are needed for directional drilling applications and advances them with rich data pipelines that feed predictive and prescriptive machine-learning (ML) models; this enables more accurate BHA tendencies, operating parameters, and trajectory plans that ultimately reduce executional risk and uncertainty. Intelligent execution provides technologies that facilitate decision-making activities, whether they be from the wellsite or town, by leveraging the digital-drilling program that is generated from the intelligent planning activities. The program connects planning expectations, real-time execution data from the surface and downhole equipment, and generates insights from data analytics, physics-based simulations, and offset analysis to achieve consistent directional drilling performance that is transparent to all stakeholders. This new framework enables a self-steering BHA for directional drilling operations. The workflow involves an automated evaluation of the current bit position with respect to the initial plan, automated evaluation of the maximum dogleg capability of the BHA, and the capability to examine the health of the BHA tools and, if needed, an automated re-planning of an optimized working plan. This is accomplished on a system level with interdependencies on the different elements that make up the complete workflow. This new autonomous directional drilling framework will minimize operational risk and cost-per-foot drilled; maximize performance, procedural adherence, and establish consistent results across fields, rigs, and trajectories while enabling modern remote operations.
{"title":"Autonomous Directional Drilling Planning and Execution Using an Industry 4.0 Platform","authors":"Samba Ba, M. Ignova, K. Mantle, Adrien Chassard, Tao Yu, Sylvain Chambon, Ziad Akkaoui, Lu Jiang, Richard Harmer, Olivia Barcelata, Jinsoo Kim, Mustapha Rhazaf","doi":"10.2118/204607-ms","DOIUrl":"https://doi.org/10.2118/204607-ms","url":null,"abstract":"\u0000 Today, directional drilling is considered a mix between art and science only performed by experts in the field. In this paper, we present an autonomous directional drilling framework using an industry 4.0 platform that is built on intelligent planning and execution capabilities and is supported by surface and downhole automation technologies to achieve consistently performing directional drilling operations accessible for easy remote operations.\u0000 Intelligent planning builds on standard planning activities that are needed for directional drilling applications and advances them with rich data pipelines that feed predictive and prescriptive machine-learning (ML) models; this enables more accurate BHA tendencies, operating parameters, and trajectory plans that ultimately reduce executional risk and uncertainty.\u0000 Intelligent execution provides technologies that facilitate decision-making activities, whether they be from the wellsite or town, by leveraging the digital-drilling program that is generated from the intelligent planning activities. The program connects planning expectations, real-time execution data from the surface and downhole equipment, and generates insights from data analytics, physics-based simulations, and offset analysis to achieve consistent directional drilling performance that is transparent to all stakeholders.\u0000 This new framework enables a self-steering BHA for directional drilling operations. The workflow involves an automated evaluation of the current bit position with respect to the initial plan, automated evaluation of the maximum dogleg capability of the BHA, and the capability to examine the health of the BHA tools and, if needed, an automated re-planning of an optimized working plan. This is accomplished on a system level with interdependencies on the different elements that make up the complete workflow.\u0000 This new autonomous directional drilling framework will minimize operational risk and cost-per-foot drilled; maximize performance, procedural adherence, and establish consistent results across fields, rigs, and trajectories while enabling modern remote operations.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77592856","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}
Reddy B. S., Ramana Rao U. V, S. T, Ramakrishna C H, Ramya Sri A. R, A. Bandyopadhyay, Raj Kumar, J. Zacharia, Vibhu Kumar
Permo-Triassic formations in Mandapetta field from eastern onshore, India possesses historical drilling challenges in terms of wellbore instability, non-productive time and poor hole condition in deep higher stressed formations. Lack of acquiring reliable log data and problems in recovering good quality cores present difficulties in proper formation evaluation and zone selection for testing. Historical well test results in target K-Formation has been not encouraging despite good gas shows during drilling. Estimated formation pressure gradient ranges 1.45sg-1.52sg. Layered shale with coal and tight sandstone in same open hole section pose risks of mud losses and poor cement job. Present study highlights the workflow adopted to improve drilling and completion in open hole section of more than 1000 m with varying lithology being drilled successfully. Advanced 3D anisotropic acoustic measurements acquired are used to estimate anisotropic elastic properties (vertical and horizontal Young's modulus and Poisson's ratio) in the overlying shales. Horizontal tectonics has been determined across stress induced anisotropic layers. This approach provides better understanding of formations and stress distribution. Thomsen Gamma values range 0.1 to 0.4 in shale layers of overburden formations. In order to minimize uncertainty in 8.5inch section while drilling, advanced logs were acquired in 12.25inch hole section to estimate tectonics at well location while constraining ratio of horizontal to vertical Young's modulus and Poisson Ratio in shale layers based on Thomsen Gamma and clay volume. Analysis suggested typical VTI anisotropy of 15%-20% in shale layers. Inverted direct horizontal strain parameters at well location suggested the ratio of maximum to minimum horizontal stress to vary 1.15-1.23. Mud weight used while drilling 8.5inch section ranged 1.49sg1.52sg against the recommended mud weight of 1.50sg-1.52sg while pumping sealing agents to prevent mud losses in coal layers. Flow rate was maintained on lower values to minimize ECD values. Hole condition improved significantly with no issues in logging. Post-drill anisotropic rock mechanics model suggested good quality sandstone in target source formation with usual conventional reservoir in shallower formation. Zone was selected based on permeability, breakdown and completion quality for perforations. Analysis of high-quality sonic slowness helped to identify possible gas reservoir in laminated source rock. There was stress contrast of 2000psi-2500psi among reservoir layers and shale stress barriers. Implemented workflow and successful execution helped to drill the well 5 days earlier than plan with no major drilling incidents. Successful core recovery for Shale Gas evaluation was also possible due to better wellbore quality. Initial testing of K-Formation produced gas with significant improved flow rate by 150% without any stimulation for the 1st time in the history of the field.
{"title":"Paradigm Shift in Drilling to Completion in Unconventional Reservoir, Eastern Onshore, India","authors":"Reddy B. S., Ramana Rao U. V, S. T, Ramakrishna C H, Ramya Sri A. R, A. Bandyopadhyay, Raj Kumar, J. Zacharia, Vibhu Kumar","doi":"10.2118/204625-ms","DOIUrl":"https://doi.org/10.2118/204625-ms","url":null,"abstract":"\u0000 Permo-Triassic formations in Mandapetta field from eastern onshore, India possesses historical drilling challenges in terms of wellbore instability, non-productive time and poor hole condition in deep higher stressed formations. Lack of acquiring reliable log data and problems in recovering good quality cores present difficulties in proper formation evaluation and zone selection for testing. Historical well test results in target K-Formation has been not encouraging despite good gas shows during drilling. Estimated formation pressure gradient ranges 1.45sg-1.52sg. Layered shale with coal and tight sandstone in same open hole section pose risks of mud losses and poor cement job. Present study highlights the workflow adopted to improve drilling and completion in open hole section of more than 1000 m with varying lithology being drilled successfully. Advanced 3D anisotropic acoustic measurements acquired are used to estimate anisotropic elastic properties (vertical and horizontal Young's modulus and Poisson's ratio) in the overlying shales. Horizontal tectonics has been determined across stress induced anisotropic layers. This approach provides better understanding of formations and stress distribution. Thomsen Gamma values range 0.1 to 0.4 in shale layers of overburden formations. In order to minimize uncertainty in 8.5inch section while drilling, advanced logs were acquired in 12.25inch hole section to estimate tectonics at well location while constraining ratio of horizontal to vertical Young's modulus and Poisson Ratio in shale layers based on Thomsen Gamma and clay volume. Analysis suggested typical VTI anisotropy of 15%-20% in shale layers. Inverted direct horizontal strain parameters at well location suggested the ratio of maximum to minimum horizontal stress to vary 1.15-1.23. Mud weight used while drilling 8.5inch section ranged 1.49sg1.52sg against the recommended mud weight of 1.50sg-1.52sg while pumping sealing agents to prevent mud losses in coal layers. Flow rate was maintained on lower values to minimize ECD values. Hole condition improved significantly with no issues in logging. Post-drill anisotropic rock mechanics model suggested good quality sandstone in target source formation with usual conventional reservoir in shallower formation. Zone was selected based on permeability, breakdown and completion quality for perforations. Analysis of high-quality sonic slowness helped to identify possible gas reservoir in laminated source rock. There was stress contrast of 2000psi-2500psi among reservoir layers and shale stress barriers. Implemented workflow and successful execution helped to drill the well 5 days earlier than plan with no major drilling incidents. Successful core recovery for Shale Gas evaluation was also possible due to better wellbore quality. Initial testing of K-Formation produced gas with significant improved flow rate by 150% without any stimulation for the 1st time in the history of the field.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75871200","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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