Pub Date : 2021-09-16DOI: 10.36548/jscp.2021.3.005
R. Sharma
Transformers are one of the primary device required for an AC (Alternating Current) distribution system which works on the principle of mutual induction without any rotating parts. There are two types of transformers are utilized in the distribution systems namely step up transformer and step down transformer. The step up transformers are need to be placed at some regular distances for reducing the line losses happening over the electrical transmission systems. Similarly the step down transformers are placed near to the destinations for regulating the electricity power for the commercial usage. Certain regular check-ups are must for a distribution transformer for increasing its operational life time. The proposed work is designed to regularize such health check-ups using IoT sensors for making a centralized remote monitoring system.
{"title":"Design of Distribution Transformer Health Management System using IoT Sensors","authors":"R. Sharma","doi":"10.36548/jscp.2021.3.005","DOIUrl":"https://doi.org/10.36548/jscp.2021.3.005","url":null,"abstract":"Transformers are one of the primary device required for an AC (Alternating Current) distribution system which works on the principle of mutual induction without any rotating parts. There are two types of transformers are utilized in the distribution systems namely step up transformer and step down transformer. The step up transformers are need to be placed at some regular distances for reducing the line losses happening over the electrical transmission systems. Similarly the step down transformers are placed near to the destinations for regulating the electricity power for the commercial usage. Certain regular check-ups are must for a distribution transformer for increasing its operational life time. The proposed work is designed to regularize such health check-ups using IoT sensors for making a centralized remote monitoring system.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82561974","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}
P. Chidambaram, P. Tiwari, P. A. Patil, S. Mohd Ali, Sharidah M Amin, R. Tewari, C. Tan, A. Widyanita, M. K. B A Hamid
Carbon sequestration is the process of capturing and storage of atmospheric carbon dioxide. The objective of any carbon sequestration project is to store CO2 safely for hundreds or thousands of years with a goal of reducing global climate change. A depleted hydrocarbon reservoir is one of the potential storage sites being considered for long-term CO2 storage. The dynamic, geochemical, and geomechanics changes that occur during CO2 injection are inter-related. For example, when injected CO2 causes dissolution of reservoir rock, on one hand, porosity increases while rock strength decreases. On the other hand, reduced rock strength could cause additional compaction thus reducing porosity, whereas increase in pressure due to injection could cause dilation. Hence, it is critical to have an integrated model that captures effect of all changes on the storage capacity and integrity of the reservoir. Three major depleted gas reservoirs in Central Luconia field, located offshore Sarawak, are being evaluated for future CO2 storage. A 3-way coupled modelling approach that integrates dynamic model, geochemistry model, and geomechanics model is utilized to obtain cumulative effect of all three changes. This integrated model provides a more accurate estimate of 1) CO2 storage capacity, 2) Caprock integrity evaluation, 3) CO2 plume migration path, and 4) Volume of CO2 stored through different storage mechanisms (viz. hydrodynamic trapping, capillary trapping, solubility trapping, and mineral trapping). Apart from providing storage capacity, this model also provides inputs for evaluating integrity of caprock, fault reactivation study, MMV (Measurement, Monitoring, and Verification) planning, and estimating potential leak rates through plugged and abandoned wells. Using a 3-way coupled model, it is estimated that there is an average reduction in porosity of 5-10% (of initial porosity). This translates to an equivalent reduction in CO2 storage capacity of 5-10% compared to dynamic model. It is observed that pore collapse as a result of pressure depletion is primarily responsible for this reduction in porosity. It has also been observed that the injection can be continued till initial reservoir pressure is reached without breaching caprock integrity. CO2 plume migration path significantly affects MMV planning. Potential leak rate estimation is critical in mitigation and contingency planning.
{"title":"Importance of 3-Way Coupled Modelling for Carbon Dioxide Sequestration in Depleted Reservoir","authors":"P. Chidambaram, P. Tiwari, P. A. Patil, S. Mohd Ali, Sharidah M Amin, R. Tewari, C. Tan, A. Widyanita, M. K. B A Hamid","doi":"10.2118/206156-ms","DOIUrl":"https://doi.org/10.2118/206156-ms","url":null,"abstract":"\u0000 Carbon sequestration is the process of capturing and storage of atmospheric carbon dioxide. The objective of any carbon sequestration project is to store CO2 safely for hundreds or thousands of years with a goal of reducing global climate change. A depleted hydrocarbon reservoir is one of the potential storage sites being considered for long-term CO2 storage. The dynamic, geochemical, and geomechanics changes that occur during CO2 injection are inter-related. For example, when injected CO2 causes dissolution of reservoir rock, on one hand, porosity increases while rock strength decreases. On the other hand, reduced rock strength could cause additional compaction thus reducing porosity, whereas increase in pressure due to injection could cause dilation. Hence, it is critical to have an integrated model that captures effect of all changes on the storage capacity and integrity of the reservoir.\u0000 Three major depleted gas reservoirs in Central Luconia field, located offshore Sarawak, are being evaluated for future CO2 storage. A 3-way coupled modelling approach that integrates dynamic model, geochemistry model, and geomechanics model is utilized to obtain cumulative effect of all three changes. This integrated model provides a more accurate estimate of 1) CO2 storage capacity, 2) Caprock integrity evaluation, 3) CO2 plume migration path, and 4) Volume of CO2 stored through different storage mechanisms (viz. hydrodynamic trapping, capillary trapping, solubility trapping, and mineral trapping). Apart from providing storage capacity, this model also provides inputs for evaluating integrity of caprock, fault reactivation study, MMV (Measurement, Monitoring, and Verification) planning, and estimating potential leak rates through plugged and abandoned wells.\u0000 Using a 3-way coupled model, it is estimated that there is an average reduction in porosity of 5-10% (of initial porosity). This translates to an equivalent reduction in CO2 storage capacity of 5-10% compared to dynamic model. It is observed that pore collapse as a result of pressure depletion is primarily responsible for this reduction in porosity. It has also been observed that the injection can be continued till initial reservoir pressure is reached without breaching caprock integrity. CO2 plume migration path significantly affects MMV planning. Potential leak rate estimation is critical in mitigation and contingency planning.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75849598","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 objective of this study is to improve understanding of the geostatistics of vertical (bed-normal) permeability (kz) and its influence on reservoir performance during CO2 enhanced oil recovery (EOR) and storage. kz is scrutinized far less often than horizontal permeability (kx, ky) in most geological and reservoir modeling. However, our work indicates that it is equally important to understand kz characteristics to better evaluate their influence on CO2 EOR and storage performance prediction. We conducted this study on about 9,000 whole-core triaxial permeability (kx, ky, kz) measurements from 42 wells in a San Andres carbonate reservoir. We analyzed kz data, including heterogeneity, correlation, and sample sufficiency measures. We analyzed wells with the largest and smallest fractions of points with kz > kmax = max(kx, ky), to explore geological factors that coincided with large kz. We quantified these geological effects through conditional probabilities on potential permeability barriers (e.g., stylolites). Every well had at least some whole-cores where kz > kmax. This is a statistically justifiable result; only where Prob(kz > kmax) is statistically different from 1/3 are core samples non-isotropic. In conventional core data interpretation, however, modelers usually assume kz is less than kmax. For the well with the smallest fraction (11%) of cores where kz > kmax, the cumulative distribution functions differ and coincides with the presence of stylolites. We found that kz is about twice as variable as kx in many wells. This makes kz more difficult to interpret because it was (and usually is) heavily undersampled. To understand the influence of kz heterogeneity on CO2 flow, we built a series of flow simulation models that captured these geostatistical characteristics of permeability, while considering kz realizations, flow regimes (e.g., buoyant flow), CO2 injection strategies, and reservoir heterogeneity. CO2 flow simulations showed that, for viscous flow, assuming variable kx similar to the reservoir along with a constant kz/kx = 0.1 yields a close (within 0.5%) cumulative oil production to the simulation case with both kx and kz as uncorrelated variables. However, for buoyant flow, oil production differs by 10% (at 2.0 hydrocarbon pore volume HCPV of CO2 injected) between the two cases. Such flows could occur for small CO2 injection rates and long injection times, in interwell regions, and/or with vertically permeable conduits. Our geostatistical characterization demonstrates the controls on kz in a carbonate reservoir and how to improve conventional interpretation practices. This study can help CO2 EOR and storage operators refine injection development programs, particularly for reservoirs where buoyant flow exists. More broadly, the findings potentially apply to other similar subsurface buoyancy-driven flow displacements, including hydrogen storage, geothermal production, and aquifer CO2 sequestration.
{"title":"Analysis of Vertical Permeability and Its Influence on CO2 EOR and Storage in a Carbonate Reservoir","authors":"Bo Ren, J. Jensen, L. Lake, I. Duncan, Frank Male","doi":"10.2118/205995-ms","DOIUrl":"https://doi.org/10.2118/205995-ms","url":null,"abstract":"\u0000 The objective of this study is to improve understanding of the geostatistics of vertical (bed-normal) permeability (kz) and its influence on reservoir performance during CO2 enhanced oil recovery (EOR) and storage. kz is scrutinized far less often than horizontal permeability (kx, ky) in most geological and reservoir modeling. However, our work indicates that it is equally important to understand kz characteristics to better evaluate their influence on CO2 EOR and storage performance prediction.\u0000 We conducted this study on about 9,000 whole-core triaxial permeability (kx, ky, kz) measurements from 42 wells in a San Andres carbonate reservoir. We analyzed kz data, including heterogeneity, correlation, and sample sufficiency measures. We analyzed wells with the largest and smallest fractions of points with kz > kmax = max(kx, ky), to explore geological factors that coincided with large kz. We quantified these geological effects through conditional probabilities on potential permeability barriers (e.g., stylolites).\u0000 Every well had at least some whole-cores where kz > kmax. This is a statistically justifiable result; only where Prob(kz > kmax) is statistically different from 1/3 are core samples non-isotropic. In conventional core data interpretation, however, modelers usually assume kz is less than kmax. For the well with the smallest fraction (11%) of cores where kz > kmax, the cumulative distribution functions differ and coincides with the presence of stylolites. We found that kz is about twice as variable as kx in many wells. This makes kz more difficult to interpret because it was (and usually is) heavily undersampled.\u0000 To understand the influence of kz heterogeneity on CO2 flow, we built a series of flow simulation models that captured these geostatistical characteristics of permeability, while considering kz realizations, flow regimes (e.g., buoyant flow), CO2 injection strategies, and reservoir heterogeneity. CO2 flow simulations showed that, for viscous flow, assuming variable kx similar to the reservoir along with a constant kz/kx = 0.1 yields a close (within 0.5%) cumulative oil production to the simulation case with both kx and kz as uncorrelated variables. However, for buoyant flow, oil production differs by 10% (at 2.0 hydrocarbon pore volume HCPV of CO2 injected) between the two cases. Such flows could occur for small CO2 injection rates and long injection times, in interwell regions, and/or with vertically permeable conduits.\u0000 Our geostatistical characterization demonstrates the controls on kz in a carbonate reservoir and how to improve conventional interpretation practices. This study can help CO2 EOR and storage operators refine injection development programs, particularly for reservoirs where buoyant flow exists. More broadly, the findings potentially apply to other similar subsurface buoyancy-driven flow displacements, including hydrogen storage, geothermal production, and aquifer CO2 sequestration.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"643 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74732715","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}
Recent studies have shown the utility of the Fast Marching Method and the Diffusive Time of Flight for the rapid simulation and analysis of Unconventional reservoirs, where the time scale for pressure transients are long and field developments are dominated by single well performance. We show that similar fast simulation and multi-well modeling approaches can be developed utilizing the PSS pressure as a spatial coordinate, providing an extension to both Conventional and Unconventional reservoir analysis. We reformulate the multi-dimensional multi-phase flow equations using the PSS pressure drop as a spatial coordinate. Properties are obtained by coarsening and upscaling a fine scale 3D reservoir model, and are then used to obtain fast single well simulation models. We also develop new 1D solutions to the Eikonal equation that are aligned with the PSS discretization, which better represent superposition and finite sized boundary effects than the original 3D Eikonal equation. These solutions allow the use of superposition to extend the single well results to multiple wells. The new solutions to the Eikonal equation more accurately represent multi-fracture interference for a horizontal MTFW well, the effects of strong heterogeneity, and finite reservoir extent than those obtained by the Fast Marching Method. The new methodologies are validated against a series of increasingly heterogeneous synthetic examples, with vertical and horizontal wells. We find that the results are systematically more accurate than those based upon the Diffusive Time of Flight, especially as the wells are placed closer to the reservoir boundary or as heterogeneity increases. The approach is applied to the Brugge benchmark study. We consider the history matching stage of the study and utilize the multi-well fast modeling approach to determine the rank quality of the 100+ static realizations provided in the benchmark dataset against historical data. The multi-well calculation uses superposition to obtain a direct calculation of the interaction of the rates and pressures of the wells without the need to explicitly solve flow equations within the reservoir model. The ranked realizations are then compared against full field simulation to demonstrate the significant reduction in simulation cost and the corresponding ability to explore the subsurface uncertainty more extensively. We demonstrate two completely new methods for rapid reservoir analysis, based upon the use of the PSS pressure as a spatial coordinate. The first approach demonstrates the utility of rapid single well flow simulation, with improved accuracy compared to the use of the Diffusive Time of Flight. We are also able to reformulate and solve the Eikonal equation in these coordinates, giving a rapid analytic method of transient flow analysis for both single and multi-well modeling.
{"title":"Development and Application of Fast Simulation Based on the PSS Pressure as a Spatial Coordinate","authors":"Kenta Nakajima, Michael King","doi":"10.2118/206085-ms","DOIUrl":"https://doi.org/10.2118/206085-ms","url":null,"abstract":"\u0000 Recent studies have shown the utility of the Fast Marching Method and the Diffusive Time of Flight for the rapid simulation and analysis of Unconventional reservoirs, where the time scale for pressure transients are long and field developments are dominated by single well performance. We show that similar fast simulation and multi-well modeling approaches can be developed utilizing the PSS pressure as a spatial coordinate, providing an extension to both Conventional and Unconventional reservoir analysis.\u0000 We reformulate the multi-dimensional multi-phase flow equations using the PSS pressure drop as a spatial coordinate. Properties are obtained by coarsening and upscaling a fine scale 3D reservoir model, and are then used to obtain fast single well simulation models.\u0000 We also develop new 1D solutions to the Eikonal equation that are aligned with the PSS discretization, which better represent superposition and finite sized boundary effects than the original 3D Eikonal equation. These solutions allow the use of superposition to extend the single well results to multiple wells. The new solutions to the Eikonal equation more accurately represent multi-fracture interference for a horizontal MTFW well, the effects of strong heterogeneity, and finite reservoir extent than those obtained by the Fast Marching Method.\u0000 The new methodologies are validated against a series of increasingly heterogeneous synthetic examples, with vertical and horizontal wells. We find that the results are systematically more accurate than those based upon the Diffusive Time of Flight, especially as the wells are placed closer to the reservoir boundary or as heterogeneity increases.\u0000 The approach is applied to the Brugge benchmark study. We consider the history matching stage of the study and utilize the multi-well fast modeling approach to determine the rank quality of the 100+ static realizations provided in the benchmark dataset against historical data. The multi-well calculation uses superposition to obtain a direct calculation of the interaction of the rates and pressures of the wells without the need to explicitly solve flow equations within the reservoir model. The ranked realizations are then compared against full field simulation to demonstrate the significant reduction in simulation cost and the corresponding ability to explore the subsurface uncertainty more extensively.\u0000 We demonstrate two completely new methods for rapid reservoir analysis, based upon the use of the PSS pressure as a spatial coordinate. The first approach demonstrates the utility of rapid single well flow simulation, with improved accuracy compared to the use of the Diffusive Time of Flight. We are also able to reformulate and solve the Eikonal equation in these coordinates, giving a rapid analytic method of transient flow analysis for both single and multi-well modeling.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75205611","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}
A. Salehi, I. Arslan, Lichi Deng, H. Darabi, Johanna Smith, S. Suicmez, D. Castineira, E. Gringarten
Horizontal well development often increases field production and recovery due to increased reservoir contact, reduced drawdown in the reservoir, and a more efficient drainage pattern. Successful field development requires an evergreen backlog of opportunities that can be pursued, which is extremely challenging and laborious to generate using traditional workflows. Here, we present a data-driven methodology to automatically deliver a feasible, actionable inventory by combining geological knowledge, reservoir performance, production history, completion information, and multi-disciplinary expertise. This technology relies on automated geologic and engineering workflows to identify areas with high relative probability of success (RPOS) and therefore productivity potential. The workflow incorporates multiple configuration and trajectory constraints for placement of the horizontal wells, such as length/azimuth/inclination range, zone-crossing, fault-avoidance, etc. The optimization engine is initialized with an ensemble of initial guesses generated with Latin-Hypercube Sampling (LHS) to ensure all regions of POS distribution in the model are evenly considered. The advanced optimization algorithm identifies potential target locations with 3D pay tracking globally, and the segments are further optimized using an interference analysis that selects the best set of non-interfering targets to maximize production. Advanced AI-based computational algorithms are implemented under numerous physical constraints to identify the best segments that maximize the RPOS. Statistical and machine learning techniques are combined to assess neighborhood performance and geologic risks, along with physics-based analytical and upscaled parametric models to forecast phase-based production and pressure behavior. Finally, a comprehensive vetting and sorting framework is presented to ensure the final set of identified opportunities is feasible for the field development plan, given the operational constraints. This methodology has been successfully applied to a mature field in the Middle East with more than 90 vertical well producers and 50 years of production history to identify horizontal target opportunities. Rapid decline in oil production and a subpar recovery factor were the primary incentives behind switching to horizontal development. The search covered both shorter laterals accessible as a side-track from existing wells to minimize water encroachment, and longer laterals that could be drilled as new wells. After filtering based on geo-engineering attributes and rigorous vetting by domain experts, the final catalog consisted of 32 horizontal targets. After careful consideration, the top five candidates were selected for execution in the short term with an estimated total oil gain of 40,000 STB/D. The introduced AI-based methodology has many advantages over traditional simulation-centric workflows that take months to build and calibrate a model. This framework automates
{"title":"A Data-Driven Workflow for Identifying Optimum Horizontal Subsurface Targets","authors":"A. Salehi, I. Arslan, Lichi Deng, H. Darabi, Johanna Smith, S. Suicmez, D. Castineira, E. Gringarten","doi":"10.2118/205837-ms","DOIUrl":"https://doi.org/10.2118/205837-ms","url":null,"abstract":"\u0000 Horizontal well development often increases field production and recovery due to increased reservoir contact, reduced drawdown in the reservoir, and a more efficient drainage pattern. Successful field development requires an evergreen backlog of opportunities that can be pursued, which is extremely challenging and laborious to generate using traditional workflows. Here, we present a data-driven methodology to automatically deliver a feasible, actionable inventory by combining geological knowledge, reservoir performance, production history, completion information, and multi-disciplinary expertise.\u0000 This technology relies on automated geologic and engineering workflows to identify areas with high relative probability of success (RPOS) and therefore productivity potential. The workflow incorporates multiple configuration and trajectory constraints for placement of the horizontal wells, such as length/azimuth/inclination range, zone-crossing, fault-avoidance, etc. The optimization engine is initialized with an ensemble of initial guesses generated with Latin-Hypercube Sampling (LHS) to ensure all regions of POS distribution in the model are evenly considered. The advanced optimization algorithm identifies potential target locations with 3D pay tracking globally, and the segments are further optimized using an interference analysis that selects the best set of non-interfering targets to maximize production. Advanced AI-based computational algorithms are implemented under numerous physical constraints to identify the best segments that maximize the RPOS. Statistical and machine learning techniques are combined to assess neighborhood performance and geologic risks, along with physics-based analytical and upscaled parametric models to forecast phase-based production and pressure behavior. Finally, a comprehensive vetting and sorting framework is presented to ensure the final set of identified opportunities is feasible for the field development plan, given the operational constraints.\u0000 This methodology has been successfully applied to a mature field in the Middle East with more than 90 vertical well producers and 50 years of production history to identify horizontal target opportunities. Rapid decline in oil production and a subpar recovery factor were the primary incentives behind switching to horizontal development. The search covered both shorter laterals accessible as a side-track from existing wells to minimize water encroachment, and longer laterals that could be drilled as new wells. After filtering based on geo-engineering attributes and rigorous vetting by domain experts, the final catalog consisted of 32 horizontal targets. After careful consideration, the top five candidates were selected for execution in the short term with an estimated total oil gain of 40,000 STB/D.\u0000 The introduced AI-based methodology has many advantages over traditional simulation-centric workflows that take months to build and calibrate a model. This framework automates","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75328387","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. W. Senters, S. Jayakumar, Mark N. Warren, M. Wells, Rachel Harper, R. S. Leonard, R. Woodroof
The application of data science remains relatively new to the oil and gas industry but continues to gain traction on many projects due to its potential to assist in solving complex problems. The amount and quality of the right type of data can be as much of a limitation as the complex algorithms and programing required. The scope of any data science project should look for easy wins early on and not attempt an all-encompassing solution with the click of a button (although that would be amazing). This paper focuses on several specific applications of data applied to a sizable database to extract useful solutions and provide an approach for data science on future projects. The first step when applying data analytics is to build a suitable database. This might appear rudimentary at first glance, but historical data is seldom catalogued optimally for future projects. This is especially true if specific portions of the recorded data were not known to be of use in solving future problems. The approach to improving the quality of the database for this paper is to establish requirements for the data science objectives and apply this to past, present and future data. Once the data are in the right "format", the extensive process of quality control can begin. Although this part of the paper is not the most exciting, it might be the most important, as most programing yields the same "garbage in = garbage out" equation. After the data have found a home and are quality checked, the data science can be applied. Case studies are presented based on the application of diagnostic data from an extensive project/well database. To leverage historical data in new projects, metrics are created as a benchmarking tool. The case studies in this paper include metrics such as the Known Lateral Contribution (KLC), Heel-to-Toe Ratio (HTR), Communication Intensity (CI), Proppant Efficiency (PE) and stage level performance. These results are compared to additional stimulation and geological information. This paper includes case studies that apply data science to diagnostics on a large scale to deliver actionable results. The results discussed will allow for the utilization of this approach in future projects and provide a roadmap to better understand diagnostic results as they relate to drilling and completion activity.
{"title":"Practical Applications of Diagnostic Data Science in Drilling and Completions","authors":"C. W. Senters, S. Jayakumar, Mark N. Warren, M. Wells, Rachel Harper, R. S. Leonard, R. Woodroof","doi":"10.2118/206234-ms","DOIUrl":"https://doi.org/10.2118/206234-ms","url":null,"abstract":"\u0000 The application of data science remains relatively new to the oil and gas industry but continues to gain traction on many projects due to its potential to assist in solving complex problems. The amount and quality of the right type of data can be as much of a limitation as the complex algorithms and programing required. The scope of any data science project should look for easy wins early on and not attempt an all-encompassing solution with the click of a button (although that would be amazing). This paper focuses on several specific applications of data applied to a sizable database to extract useful solutions and provide an approach for data science on future projects.\u0000 The first step when applying data analytics is to build a suitable database. This might appear rudimentary at first glance, but historical data is seldom catalogued optimally for future projects. This is especially true if specific portions of the recorded data were not known to be of use in solving future problems. The approach to improving the quality of the database for this paper is to establish requirements for the data science objectives and apply this to past, present and future data. Once the data are in the right \"format\", the extensive process of quality control can begin. Although this part of the paper is not the most exciting, it might be the most important, as most programing yields the same \"garbage in = garbage out\" equation. After the data have found a home and are quality checked, the data science can be applied.\u0000 Case studies are presented based on the application of diagnostic data from an extensive project/well database. To leverage historical data in new projects, metrics are created as a benchmarking tool. The case studies in this paper include metrics such as the Known Lateral Contribution (KLC), Heel-to-Toe Ratio (HTR), Communication Intensity (CI), Proppant Efficiency (PE) and stage level performance. These results are compared to additional stimulation and geological information.\u0000 This paper includes case studies that apply data science to diagnostics on a large scale to deliver actionable results. The results discussed will allow for the utilization of this approach in future projects and provide a roadmap to better understand diagnostic results as they relate to drilling and completion activity.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"151 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75688512","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 public domain contains many work efforts that document the advantages of expandable drilling and completions systems within the industry (Filippov 1999, Lohoefer 2000). The ability to place a solid steel liner or patch into a well and transform it by cold working to a larger diameter provides an opportunity to drill deeper while maintaining sufficient wellbore diameter. The use of expandable technology has led to the development of a formable and retractable-segmented cone. The cone supports an expandable system capable of passing through the drift of a base casing that can then result in an expansion providing the equivalent drift diameter. The technology allows the placement of additional liner points in a well that can extend liner lengths as well as isolate sections of open hole that were previously impossible to isolate due to wellbore geometry restriction. There are no limitations on the number of open hole patches installed in a given well which are helpful when wells experience multiple drilling hazards. Each patch can pass through a previously installed patch. The idea of monodiameter expandable liners began in the early 2000s (Dupal 2002, Dean 2003). This paper presents the technical challenges, solutions, and testing of a novel monodiameter system that expands 11-3/4 in. 47 lb/ft pipe which can result in a post-expansion drift diameter of 12-1/4 in. Finite element analysis helped transform the concept from the theoretical system to field execution. The work efforts show the successful testing of the monobore system at surface, and the resulting field trials demonstrate the ability of the technology to fulfil the installation objectives. In addition, the success of the methodology has led to the development of additional monobore system sizes.
公共领域包含许多工作成果，记录了可扩展钻井和完井系统在行业中的优势(Filippov 1999, Lohoefer 2000)。将实心钢尾管或补片放入井中，并通过冷加工将其改造成更大的直径，这为在保持足够井筒直径的同时钻得更深提供了机会。可扩展技术的使用导致了可成形和可伸缩分段锥体的发展。锥筒支撑一个可扩展的系统，该系统能够通过基础套管的漂移，从而产生膨胀，提供等效的漂移直径。该技术允许在井中放置额外的尾管点，从而延长尾管长度，并隔离裸眼井中由于井筒几何形状限制而无法隔离的部分。在一口井中安装裸眼补丁的数量没有限制，当井遇到多种钻井危险时，这是很有帮助的。每个补丁都可以通过以前安装的补丁。单直径膨胀尾管的概念始于21世纪初(Dupal 2002, Dean 2003)。本文介绍了一种新型单径系统的技术挑战、解决方案和测试，该系统可扩展至11-3/4 in。47磅/英尺的管道，膨胀后的通径可达12-1/4英寸。有限元分析帮助将概念从理论系统转变为现场执行。工作成果表明，单孔系统在地面上的测试取得了成功，由此产生的现场试验表明，该技术能够实现安装目标。此外，该方法的成功还导致了更多单孔系统尺寸的开发。
{"title":"The Same Drift Monodiameter Completion System in Solving Drilling and Well Infrastructure Challenges","authors":"M. Godfrey, R. Baker","doi":"10.2118/205961-ms","DOIUrl":"https://doi.org/10.2118/205961-ms","url":null,"abstract":"\u0000 The public domain contains many work efforts that document the advantages of expandable drilling and completions systems within the industry (Filippov 1999, Lohoefer 2000). The ability to place a solid steel liner or patch into a well and transform it by cold working to a larger diameter provides an opportunity to drill deeper while maintaining sufficient wellbore diameter. The use of expandable technology has led to the development of a formable and retractable-segmented cone. The cone supports an expandable system capable of passing through the drift of a base casing that can then result in an expansion providing the equivalent drift diameter. The technology allows the placement of additional liner points in a well that can extend liner lengths as well as isolate sections of open hole that were previously impossible to isolate due to wellbore geometry restriction. There are no limitations on the number of open hole patches installed in a given well which are helpful when wells experience multiple drilling hazards. Each patch can pass through a previously installed patch.\u0000 The idea of monodiameter expandable liners began in the early 2000s (Dupal 2002, Dean 2003). This paper presents the technical challenges, solutions, and testing of a novel monodiameter system that expands 11-3/4 in. 47 lb/ft pipe which can result in a post-expansion drift diameter of 12-1/4 in. Finite element analysis helped transform the concept from the theoretical system to field execution. The work efforts show the successful testing of the monobore system at surface, and the resulting field trials demonstrate the ability of the technology to fulfil the installation objectives. In addition, the success of the methodology has led to the development of additional monobore system sizes.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72733247","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}
This paper provides an overview of methods for dealing with mechanical impurities, justifies the choice of a suitable method and prototype for the conditions of the field. A methodology for designing cyclone separators of JSC "NIIOGAS" is presented, in accordance with which a theoretical calculation of the design of a cyclone separator was carried out. A solid model of a computational cyclone separator in the SolidWorks software was created, a computer simulation of a gas flow with the presence of mechanical impurities of various granulometric composition was carried out, based on the results of which conclusions were made.
{"title":"Simulation of a Cyclone Separator to Improve the Efficiency of Gas Purification from Mechanical Impurities","authors":"Khasan Abrorov","doi":"10.2118/208629-stu","DOIUrl":"https://doi.org/10.2118/208629-stu","url":null,"abstract":"\u0000 This paper provides an overview of methods for dealing with mechanical impurities, justifies the choice of a suitable method and prototype for the conditions of the field. A methodology for designing cyclone separators of JSC \"NIIOGAS\" is presented, in accordance with which a theoretical calculation of the design of a cyclone separator was carried out. A solid model of a computational cyclone separator in the SolidWorks software was created, a computer simulation of a gas flow with the presence of mechanical impurities of various granulometric composition was carried out, based on the results of which conclusions were made.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74417271","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}
Muhammad Yazuwan Sallij Muhammad Yasin, Irsyad Muhammad, Wan Fatin Izyan Wan Mohd Zamri, Shahrul Nizam Bin Mohd Radzi
In maturing an Area Development Plan (ADP), most of the data used are incomplete, too fragmented, or sometime due to time constraint; need to be deduced down to assumptions. Due to this fact, an ADP is bound to have updates, even during the course of maturing it. This is where the issue starts. Since the conventional approach is "bottom-up", room to accommodate changes is limited; at times require the whole proposal to be reworked. This is because it focuses on getting the best development concept for a given field first before rolling it up to study the network/interrelationship between fields. A "top-down" approach in maturing an ADP intends to better assist any given team to be agile whilst focusing on value added solutions from a strategic bird's eye point of view. The approach in discussion was adopted and tested to a regional ADP study in year 2020 which initially involves more than 1000 fields (discovered, prospects, and leads). This approach allows for any changes throughout the course of maturing the ADP because, its main focus is to get the best network/interrelationship between fields first, before focusing on the development concept of each of the fields. Other benefits that can be observed by adopting the approach in discussion is a shorter study duration. Based on the case study, the study duration was reduced from 10 months to 6.5 months. With shorter duration too, can help the Company in better manage its manpower resources to focus on things that matters.
{"title":"Top-Down Approach to Area Development Plan Maturation","authors":"Muhammad Yazuwan Sallij Muhammad Yasin, Irsyad Muhammad, Wan Fatin Izyan Wan Mohd Zamri, Shahrul Nizam Bin Mohd Radzi","doi":"10.2118/206054-ms","DOIUrl":"https://doi.org/10.2118/206054-ms","url":null,"abstract":"\u0000 In maturing an Area Development Plan (ADP), most of the data used are incomplete, too fragmented, or sometime due to time constraint; need to be deduced down to assumptions. Due to this fact, an ADP is bound to have updates, even during the course of maturing it. This is where the issue starts. Since the conventional approach is \"bottom-up\", room to accommodate changes is limited; at times require the whole proposal to be reworked. This is because it focuses on getting the best development concept for a given field first before rolling it up to study the network/interrelationship between fields.\u0000 A \"top-down\" approach in maturing an ADP intends to better assist any given team to be agile whilst focusing on value added solutions from a strategic bird's eye point of view. The approach in discussion was adopted and tested to a regional ADP study in year 2020 which initially involves more than 1000 fields (discovered, prospects, and leads). This approach allows for any changes throughout the course of maturing the ADP because, its main focus is to get the best network/interrelationship between fields first, before focusing on the development concept of each of the fields.\u0000 Other benefits that can be observed by adopting the approach in discussion is a shorter study duration. Based on the case study, the study duration was reduced from 10 months to 6.5 months. With shorter duration too, can help the Company in better manage its manpower resources to focus on things that matters.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74819481","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}
Reduction of CO2 emissions has become a key component of many E&P company strategies, reflecting the accelerating demands of interest groups, activist investors, and country specific legislation for specific targets and measures of carbon footprint reduction. Underlying this requirement for change are the existing investments and cash flows resulting from the core ‘conventional’ business opportunities, that while potentially carbon heavy generate the cashflows needed to sustain and grow the business. Our work with several major energy firms has shown that assumptions and decisions impacting the pace of needed change need to be carefully tested, as many of the optimal decisions are counter intuitive. An example at a large integrated company was the insight that expansion of its shale resource investments accelerated the transition to a lower carbon footprint, given the cashflow generation and potential to advance low carbon alternatives in parallel. A portfolio model has been developed that replicates many of the options a company might assess in developing a strategy for carbon reduction and energy transition. This includes estimations of carbon generation from existing businesses as well as carbon reducing strategies ranging from carbon capture to new clean energy sources such as wind, solar, or hydrogen. A case study is used to represent the existing performance delivery and expectations for a large, integrated oil firm as it ‘transitions’ into a cleaner, low-carbon company. This modelling provides a window into the complexity of timing trade-offs, criticality in specific early investments, and drivers to the decisions surrounding a transitional business. The impacts of stasis, premature ‘forced’ transition, and errors in new clean energy ‘bets’ are assessed and tested, providing insights into risk mitigation strategies and alternatives. The case study clarifies the complexity in trade-offs within what appears to be a ‘simple’ energy transition strategy. This highlights the value and insights resulting from quantitative modelling of these decision structures. This paper provides examples of current methods of quantifying and assessing carbon reducing strategies. As the actual costs of generation depends on political considerations and societal demands, a wide range of typical company assumptions is outlined. In assessing alternative sources, the paper outlines the related ‘costs’ in the most touted clean-energy alternatives, both in the costs of implementation as well as the possible costs or charges resulting from future carbon generation. While most integrated energy companies have considered carbon reduction within their strategic plans for many years now, the investments in carbon reduction are for the most part negligible in comparison to conventional investments. International attention to carbon reduction and changes in societal expectations are putting additional pressures on companies to adapt more rapidly. However, transition int
{"title":"Energy Transition: Optimizing Existing E&P Value and Clean Energy Potential","authors":"P. Allan, Richard Brogan","doi":"10.2118/206175-ms","DOIUrl":"https://doi.org/10.2118/206175-ms","url":null,"abstract":"\u0000 Reduction of CO2 emissions has become a key component of many E&P company strategies, reflecting the accelerating demands of interest groups, activist investors, and country specific legislation for specific targets and measures of carbon footprint reduction. Underlying this requirement for change are the existing investments and cash flows resulting from the core ‘conventional’ business opportunities, that while potentially carbon heavy generate the cashflows needed to sustain and grow the business. Our work with several major energy firms has shown that assumptions and decisions impacting the pace of needed change need to be carefully tested, as many of the optimal decisions are counter intuitive. An example at a large integrated company was the insight that expansion of its shale resource investments accelerated the transition to a lower carbon footprint, given the cashflow generation and potential to advance low carbon alternatives in parallel.\u0000 A portfolio model has been developed that replicates many of the options a company might assess in developing a strategy for carbon reduction and energy transition. This includes estimations of carbon generation from existing businesses as well as carbon reducing strategies ranging from carbon capture to new clean energy sources such as wind, solar, or hydrogen. A case study is used to represent the existing performance delivery and expectations for a large, integrated oil firm as it ‘transitions’ into a cleaner, low-carbon company. This modelling provides a window into the complexity of timing trade-offs, criticality in specific early investments, and drivers to the decisions surrounding a transitional business. The impacts of stasis, premature ‘forced’ transition, and errors in new clean energy ‘bets’ are assessed and tested, providing insights into risk mitigation strategies and alternatives.\u0000 The case study clarifies the complexity in trade-offs within what appears to be a ‘simple’ energy transition strategy. This highlights the value and insights resulting from quantitative modelling of these decision structures. This paper provides examples of current methods of quantifying and assessing carbon reducing strategies. As the actual costs of generation depends on political considerations and societal demands, a wide range of typical company assumptions is outlined. In assessing alternative sources, the paper outlines the related ‘costs’ in the most touted clean-energy alternatives, both in the costs of implementation as well as the possible costs or charges resulting from future carbon generation.\u0000 While most integrated energy companies have considered carbon reduction within their strategic plans for many years now, the investments in carbon reduction are for the most part negligible in comparison to conventional investments. International attention to carbon reduction and changes in societal expectations are putting additional pressures on companies to adapt more rapidly. However, transition int","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77371101","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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