Y. Nakagawa, Tomoya Inoue, Hakan Bilen, Konda Reddy Mopuri, Keisuke Miyoshi, Abe Shungo, R. Wada, Kouhei Kuroda, Hitoshi Tamamura
Pipe-sticking during drilling operations causes severe difficulties, including economic losses and safety issues. Therefore, stuck-pipe predictions are an important tool to preempt this problem and avoid the aforementioned troubles. In this study, we have developed a prediction technique based on artificial intelligence, in collaboration with industry, the government, and academia. This technique was an unsupervised learning model built using an encoder-decoder, long short-term memory architecture. The model was trained with the time series data of normal drilling operations and based on an important hypothesis: reconstruction errors between observed and predicted values are higher around the time of pipe sticking than during normal drilling operations. The trained model was then applied to 34 actual stuck-pipe events, where it was found that reconstruction errors increased prior to the pipe sticking in some cases (thereby partly confirming our hypothesis) and were sensitive to large variations in the drilling parameters.
{"title":"An Unsupervised Learning Model for Pipe Stuck Predictions Using a Long Short-Term Memory Autoencoder Architecture","authors":"Y. Nakagawa, Tomoya Inoue, Hakan Bilen, Konda Reddy Mopuri, Keisuke Miyoshi, Abe Shungo, R. Wada, Kouhei Kuroda, Hitoshi Tamamura","doi":"10.2118/205677-ms","DOIUrl":"https://doi.org/10.2118/205677-ms","url":null,"abstract":"\u0000 Pipe-sticking during drilling operations causes severe difficulties, including economic losses and safety issues. Therefore, stuck-pipe predictions are an important tool to preempt this problem and avoid the aforementioned troubles. In this study, we have developed a prediction technique based on artificial intelligence, in collaboration with industry, the government, and academia. This technique was an unsupervised learning model built using an encoder-decoder, long short-term memory architecture. The model was trained with the time series data of normal drilling operations and based on an important hypothesis: reconstruction errors between observed and predicted values are higher around the time of pipe sticking than during normal drilling operations. The trained model was then applied to 34 actual stuck-pipe events, where it was found that reconstruction errors increased prior to the pipe sticking in some cases (thereby partly confirming our hypothesis) and were sensitive to large variations in the drilling parameters.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79119740","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. Alkinani, A. T. Al-Hameedi, S. Dunn-Norman, M. A. Al-Alwani
Tensile strength (To) is an important parameter for creating geomechanical models, especially when tensile failure is the failure of interest. The most common way to estimate the tensile strength is by utilizing Brazilian tests. However, due to material limitation, cost, or time, To is sometimes assumed or estimated empirically. In this work, laboratory test data of To and Unconfined Compressive Strength (UCS) conducted for three zones in southern Iraq (Zubair sandstone, Zubair shale, and Nahr Umr shale) were utilized to create three regression models to estimate To from UCS. The reason for selecting UCS as the independent parameter is that static UCS, in most cases, has to be estimated from laboratory tests to create robust geomechanical models. In other words, UCS will be given the preference over Towhen there is the material limitation, cost, or time involved. The data of each zone were divided into training (80%) and testing (20%) to ensure the models can generalize for new data and avoid overfitting. Multiple least squares fits were tested, and linear least squares regression was selected since it provided the highest R2 and the lowest error. The models yielded training R2 of 0.983, 0.988, and 0.965 while the testing R2 were 0.978, 0.990, and 0.993 for Zubair sandstone, Zubair shale, and Nahr Umr shale, respectively. The errors were assessed using root mean squared error (RMSE) and mean absolute error (MAE), and they both have shown an acceptable margin of error for all three models. In short, the created three models showed the ability to estimate To from UCS when material limitation, cost, or time factors are involved or when executing a Brazilian test is not applicable. The proposed models can contribute to robust geomechanical models as well as minimizing cost, time, and material usage.
{"title":"Statistical Models to Predict Tensile Strength from Unconfined Compressive Strength: Case Study from Southern Iraq","authors":"H. Alkinani, A. T. Al-Hameedi, S. Dunn-Norman, M. A. Al-Alwani","doi":"10.2118/205589-ms","DOIUrl":"https://doi.org/10.2118/205589-ms","url":null,"abstract":"\u0000 Tensile strength (To) is an important parameter for creating geomechanical models, especially when tensile failure is the failure of interest. The most common way to estimate the tensile strength is by utilizing Brazilian tests. However, due to material limitation, cost, or time, To is sometimes assumed or estimated empirically. In this work, laboratory test data of To and Unconfined Compressive Strength (UCS) conducted for three zones in southern Iraq (Zubair sandstone, Zubair shale, and Nahr Umr shale) were utilized to create three regression models to estimate To from UCS. The reason for selecting UCS as the independent parameter is that static UCS, in most cases, has to be estimated from laboratory tests to create robust geomechanical models. In other words, UCS will be given the preference over Towhen there is the material limitation, cost, or time involved. The data of each zone were divided into training (80%) and testing (20%) to ensure the models can generalize for new data and avoid overfitting. Multiple least squares fits were tested, and linear least squares regression was selected since it provided the highest R2 and the lowest error. The models yielded training R2 of 0.983, 0.988, and 0.965 while the testing R2 were 0.978, 0.990, and 0.993 for Zubair sandstone, Zubair shale, and Nahr Umr shale, respectively. The errors were assessed using root mean squared error (RMSE) and mean absolute error (MAE), and they both have shown an acceptable margin of error for all three models. In short, the created three models showed the ability to estimate To from UCS when material limitation, cost, or time factors are involved or when executing a Brazilian test is not applicable. The proposed models can contribute to robust geomechanical models as well as minimizing cost, time, and material usage.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76609754","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}
Achmad Rocky Falach, Ageng Warasta, Alfandra Ihsan, Amalia Kusuma Dewi, Heri Safrizal, Randy Perfibita, Satria Panji Kauripan
One of the strategies to achieve Indonesia's main goal to produce one million barrels oil per day in 2030 is to maintain existing production volume. The key of maintain the existing production is to optimize artificial lift performance used in oil wells, because 96% of oil wells in Indonesia had installed artificial lifts and their performance will significantly affect the production decline rate. This approach aims to create a simple data visualization from macro perspective, to evaluate the artificial lift performance of all oil wells in Indonesia and to find a solution to optimize their performance. This method is started by collecting the main parameters that describes the artificial lift performance such as artificial lift type, historical run life, historical operating cost, production rate, reservoir depth, type of fluid as well as additional issues from each field in Indonesia. After the data is gathered, the next step is to cluster the usage of various artificial lifts in Indonesia, which have similarities such as area, crude type, depth, rate, and operational problems, in terms of comparison between the optimum case and non-optimum one. Finally, from the non-optimum one, it will be evaluated on more detailed programs for further optimization. This evaluation process is carried out by visualizing all the data gathered using some informative dashboards. The digitalization is expected to help the improvement of evaluation time and to support decision processes. By implementing this method, several success cases were demonstrated in 2020, like optimizing Sucker Rod Pump (SRP) component in one of the fields in Sumatra, with the gain around 120 BOPD, Gas lift and SRP to Electric Submersible Pump (ESP) conversion in one of the fields in Kalimantan with 160 BOPD production outcome, switching normal ESP rate to lower rate ESP which resulted from double run life compared with the previous one, and also conversion from SRP to HPU that can extend its run life, while creating cost efficiency. From those results, it shows the benefit of the dashboards created for artificial lift optimization, especially from Government point of view. Furthermore, there are around 50 wells that will be evaluated in detail for optimization program. The visual analytics of the dashboards, for example, will help the evaluation process all at once providing positive impacts on artificial lift optimalization program. In the future, we hope that these dashboards could be developed further, by combining the implementation of machine learning, like fuzzy logic methods or neural network, to enhance the operator performance and to improve production efficiency toward the achievement of one million barrels oil per day in 2030.
{"title":"Towards 1 Million Barrels Oil Per Day in 2030: Visual Analytics for Artificial Lift Performance Optimization in Indonesia","authors":"Achmad Rocky Falach, Ageng Warasta, Alfandra Ihsan, Amalia Kusuma Dewi, Heri Safrizal, Randy Perfibita, Satria Panji Kauripan","doi":"10.2118/205793-ms","DOIUrl":"https://doi.org/10.2118/205793-ms","url":null,"abstract":"\u0000 One of the strategies to achieve Indonesia's main goal to produce one million barrels oil per day in 2030 is to maintain existing production volume. The key of maintain the existing production is to optimize artificial lift performance used in oil wells, because 96% of oil wells in Indonesia had installed artificial lifts and their performance will significantly affect the production decline rate. This approach aims to create a simple data visualization from macro perspective, to evaluate the artificial lift performance of all oil wells in Indonesia and to find a solution to optimize their performance.\u0000 This method is started by collecting the main parameters that describes the artificial lift performance such as artificial lift type, historical run life, historical operating cost, production rate, reservoir depth, type of fluid as well as additional issues from each field in Indonesia. After the data is gathered, the next step is to cluster the usage of various artificial lifts in Indonesia, which have similarities such as area, crude type, depth, rate, and operational problems, in terms of comparison between the optimum case and non-optimum one. Finally, from the non-optimum one, it will be evaluated on more detailed programs for further optimization. This evaluation process is carried out by visualizing all the data gathered using some informative dashboards. The digitalization is expected to help the improvement of evaluation time and to support decision processes.\u0000 By implementing this method, several success cases were demonstrated in 2020, like optimizing Sucker Rod Pump (SRP) component in one of the fields in Sumatra, with the gain around 120 BOPD, Gas lift and SRP to Electric Submersible Pump (ESP) conversion in one of the fields in Kalimantan with 160 BOPD production outcome, switching normal ESP rate to lower rate ESP which resulted from double run life compared with the previous one, and also conversion from SRP to HPU that can extend its run life, while creating cost efficiency. From those results, it shows the benefit of the dashboards created for artificial lift optimization, especially from Government point of view. Furthermore, there are around 50 wells that will be evaluated in detail for optimization program.\u0000 The visual analytics of the dashboards, for example, will help the evaluation process all at once providing positive impacts on artificial lift optimalization program. In the future, we hope that these dashboards could be developed further, by combining the implementation of machine learning, like fuzzy logic methods or neural network, to enhance the operator performance and to improve production efficiency toward the achievement of one million barrels oil per day in 2030.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82318339","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 describes how active and passive magnetic ranging logging used while drilling subsurface intervention wells shows characteristics of the target well casing integrity and damage. Over the course of the development of a novel active magnetic ranging system and through several years of commercial application, data has been collected and analyzed to understand the characteristics of casing damage. This paper explains the methods used in field operations to collect this data. Using the gathered information, various stages of casing damage and poor integrity are shown. Results obtained from active and passive magnetic ranging are presented in the context of identifying casing damage. This is a departure from the standard methods of interpreting the data as it is not focused on locating a wellbore but determining the integrity of the casing. Casing integrity in idle wells is usually understood by conventional logging techniques until there is a restriction or damage on the well. Magnetic ranging logging performed during the intervention to abandon these wells can give an indication to operators of the casing integrity that otherwise would have been unknown without access to the damaged well. This can help optimize subsequent abandonment procedures as well as assist with field planning into the future to mitigate issues stemming from casing integrity and to identify the causes of previously unknown critical casing damage. The paper reports surface experimental data and compares it with two field examples. In the first field example, the passive magnetic interference from a hundred-year-old casing in the offset well caused more than 100000nT deviation from the reference field approximately 1ft away from the offset well, suggesting severe casing damage. The active magnetic signature measured simultaneously approaches zero, pointing to a lack of electrical continuity in the offset casing caused by a complete break. The second field example shows an offset well segment with passive interference of 7000nT in the presence of a stable active magnetic signal at approximately 2ft separation between wells due to possible casing damage without complete separation. The passive interference increases to 14000 nT at deeper depth while the active signal approaches zero due to a complete casing break. Novel application using the data collected by active and passive magnetic ranging techniques is being applied for the understanding of issues related to casing integrity.
{"title":"Casing Integrity Evaluation in Complex Subsurface Intervention Abandonment Wells Using Magnetic Ranging","authors":"Georgy Rassadkin, Douglas Ridgway, J. Dorey","doi":"10.2118/205699-ms","DOIUrl":"https://doi.org/10.2118/205699-ms","url":null,"abstract":"\u0000 This paper describes how active and passive magnetic ranging logging used while drilling subsurface intervention wells shows characteristics of the target well casing integrity and damage.\u0000 Over the course of the development of a novel active magnetic ranging system and through several years of commercial application, data has been collected and analyzed to understand the characteristics of casing damage. This paper explains the methods used in field operations to collect this data. Using the gathered information, various stages of casing damage and poor integrity are shown.\u0000 Results obtained from active and passive magnetic ranging are presented in the context of identifying casing damage. This is a departure from the standard methods of interpreting the data as it is not focused on locating a wellbore but determining the integrity of the casing. Casing integrity in idle wells is usually understood by conventional logging techniques until there is a restriction or damage on the well. Magnetic ranging logging performed during the intervention to abandon these wells can give an indication to operators of the casing integrity that otherwise would have been unknown without access to the damaged well. This can help optimize subsequent abandonment procedures as well as assist with field planning into the future to mitigate issues stemming from casing integrity and to identify the causes of previously unknown critical casing damage.\u0000 The paper reports surface experimental data and compares it with two field examples. In the first field example, the passive magnetic interference from a hundred-year-old casing in the offset well caused more than 100000nT deviation from the reference field approximately 1ft away from the offset well, suggesting severe casing damage. The active magnetic signature measured simultaneously approaches zero, pointing to a lack of electrical continuity in the offset casing caused by a complete break. The second field example shows an offset well segment with passive interference of 7000nT in the presence of a stable active magnetic signal at approximately 2ft separation between wells due to possible casing damage without complete separation. The passive interference increases to 14000 nT at deeper depth while the active signal approaches zero due to a complete casing break.\u0000 Novel application using the data collected by active and passive magnetic ranging techniques is being applied for the understanding of issues related to casing integrity.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89590823","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. A. Azmi, Nur Ermayani Abu Zar, R. Ismail, N. Zulkifli, N. Hardikar, Ivan Y. Nugraha Putra, Jos Pragt, Olufemi A. Adegbola, Fadzilazri Shapiei, Manh Hung Nguyen
Sampling While Drilling has undergone significant changes since its advent early this decade. The continuum of applications has primarily been due to the ability to access highly deviated wellbores, to collect PVT quality and volume of formation fluids. The increased confidence is also a result of numerous applications with varied time-on-wall without ever being stuck. This paper demonstrates the contribution of this technology for reservoir fluid mapping that proved critical to update the resource assessment in a brown field through three infill wells that were a step-out to drill unpenetrated blocks and confirm their isolation from the main block of the field. As a part of the delineation plan, the objective was to confirm the current pressure regime and reservoir fluid type when drilling the S-profile appraisal wells with 75 degrees inclination. Certain sand layers were prone to sanding as evidenced from the field's long production history. Due to the proven record of this technology in such challenges, locally and globally, pipe-conveyed wireline was ruled out. During pre-job planning, there were concerns about sanding, plugging and time-on-wall and stuck tools. Empirical modeling was performed to provide realistic estimates to secure representative fluid samples. The large surface area pad was selected, due to its suitability in highly permeable yet unconsolidated formations. For the first well operation, the cleanup for confirming formation oil began with a cautious approach considering possible sanding. An insurance sample was collected after three hours. For the next target, drawing on the results of the first sampling, the pump rate was increased early in time, and a sample was collected in half the time. Similar steps were followed for the remaining two wells, where water samples were collected. Oil, water, and gas gradients were calculated. Lessons learnt and inputs from Geomechanics were used in aligning the probe face and reference to the critical drawdown pressure (CDP). A total of 4,821 feet (1,469 meters) was drilled. 58 pressures were acquired, with six formation fluid samples and five cleanup cycles for fluid identification purpose. The pad seal efficiency was 95%. The data provided useful insights into the current pressure regime and fault connectivity, enabling timely decisions for well completion. The sampling while drilling deployment was successful in the highly deviated S-profile wells and unconsolidated sand, with no nonproductive time. Because of the continuous circulation, no event of pipe sticking occurred, thereby increasing the confidence, especially in the drilling teams. The sampling while drilling operations were subsequent, due to batch drilling, with minimal time in between the jobs for turning the tools around. The technology used the latest generation sensors, algorithms, computations and was a first in Malaysia. The campaign re-instituted the clear value of information in the given environment and savin
{"title":"Bringing the Best of Sampling While Drilling in Highly Deviated S-Profile Wells: Case Studies from a Brown Field, Sabah, Offshore Malaysia","authors":"A. A. Azmi, Nur Ermayani Abu Zar, R. Ismail, N. Zulkifli, N. Hardikar, Ivan Y. Nugraha Putra, Jos Pragt, Olufemi A. Adegbola, Fadzilazri Shapiei, Manh Hung Nguyen","doi":"10.2118/205656-ms","DOIUrl":"https://doi.org/10.2118/205656-ms","url":null,"abstract":"\u0000 Sampling While Drilling has undergone significant changes since its advent early this decade. The continuum of applications has primarily been due to the ability to access highly deviated wellbores, to collect PVT quality and volume of formation fluids. The increased confidence is also a result of numerous applications with varied time-on-wall without ever being stuck. This paper demonstrates the contribution of this technology for reservoir fluid mapping that proved critical to update the resource assessment in a brown field through three infill wells that were a step-out to drill unpenetrated blocks and confirm their isolation from the main block of the field.\u0000 As a part of the delineation plan, the objective was to confirm the current pressure regime and reservoir fluid type when drilling the S-profile appraisal wells with 75 degrees inclination. Certain sand layers were prone to sanding as evidenced from the field's long production history. Due to the proven record of this technology in such challenges, locally and globally, pipe-conveyed wireline was ruled out. During pre-job planning, there were concerns about sanding, plugging and time-on-wall and stuck tools. Empirical modeling was performed to provide realistic estimates to secure representative fluid samples. The large surface area pad was selected, due to its suitability in highly permeable yet unconsolidated formations.\u0000 For the first well operation, the cleanup for confirming formation oil began with a cautious approach considering possible sanding. An insurance sample was collected after three hours. For the next target, drawing on the results of the first sampling, the pump rate was increased early in time, and a sample was collected in half the time. Similar steps were followed for the remaining two wells, where water samples were collected. Oil, water, and gas gradients were calculated. Lessons learnt and inputs from Geomechanics were used in aligning the probe face and reference to the critical drawdown pressure (CDP).\u0000 A total of 4,821 feet (1,469 meters) was drilled. 58 pressures were acquired, with six formation fluid samples and five cleanup cycles for fluid identification purpose. The pad seal efficiency was 95%. The data provided useful insights into the current pressure regime and fault connectivity, enabling timely decisions for well completion. The sampling while drilling deployment was successful in the highly deviated S-profile wells and unconsolidated sand, with no nonproductive time. Because of the continuous circulation, no event of pipe sticking occurred, thereby increasing the confidence, especially in the drilling teams.\u0000 The sampling while drilling operations were subsequent, due to batch drilling, with minimal time in between the jobs for turning the tools around. The technology used the latest generation sensors, algorithms, computations and was a first in Malaysia. The campaign re-instituted the clear value of information in the given environment and savin","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89805792","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}
N. I. Kechut, J. Groot, M. A. Mustafa, J. Groenenboom
Foam-Assisted-Water-Alternating-Gas (FAWAG) injection has been proposed to improve the inherent unfavorable mobility ratio of gas and liquid in WAG process. The foam reduces gravity override and gas channeling as to improve volumetric sweep efficiency and thus oil recovery. There are still a lot of uncertainties yet to be understood in foam dynamics, surfactant adsorption, and foam stability when contacting oil, which impact the actual foam propagation into the reservoir. Although some insights are gained from laboratory and field experiments, the performance, and design of the injection strategy and facilities as part of the field development of FAWAG is not trivial and field data is sparse. Extensive laboratory experiments and simulation studies are necessary to de-risk enhanced oil recovery (EOR) application, but these processes are time consuming and expensive. For this reason, a screening study is normally conducted to increase the possibility of selecting high potential candidates prior to embarking on the detailed feasibility studies. Unfortunately for FAWAG, the screening criteria are not readily established nor commonly available in commercial screening tools unlike for other matured EOR methods, largely contributed by the limited database on FAWAG field implementations worldwide. This paper presents a robust FAWAG screening tool which accounts for important reservoir properties, uncertainties in foam model parameters, as well as various reservoir conditions of oil and gas production and injection plans. The FAWAG process is modelled from the assumption of local equilibrium of foam creation and coalescence using an Implicit Texture model. Relevant foam scan experiments/steady state coreflood data were analyzed to derive parameters that characterize foam dynamics. The sensitivity study in this paper ranks and identifies the main risks and opportunities for the FAWAG process, quantifies the reliability of the model and increases the understanding of the effective dynamic behaviour. The sensitivity study was the basis for the development and validation of a proxy model by design of experiments. The screening tool employs this proxy model to generate immediate screening results without the need to run additional simulations. The screening tool was further validated with upscaled experimental data. A set of prediction results on the range of oil recovery for numerous plausible field scenarios was established; these screening criteria will be used as the basis for high-level decision making.
{"title":"Robust Screening Criteria for Foam-Assisted Water-Alternating Gas FAWAG Injection","authors":"N. I. Kechut, J. Groot, M. A. Mustafa, J. Groenenboom","doi":"10.2118/205813-ms","DOIUrl":"https://doi.org/10.2118/205813-ms","url":null,"abstract":"\u0000 Foam-Assisted-Water-Alternating-Gas (FAWAG) injection has been proposed to improve the inherent unfavorable mobility ratio of gas and liquid in WAG process. The foam reduces gravity override and gas channeling as to improve volumetric sweep efficiency and thus oil recovery. There are still a lot of uncertainties yet to be understood in foam dynamics, surfactant adsorption, and foam stability when contacting oil, which impact the actual foam propagation into the reservoir. Although some insights are gained from laboratory and field experiments, the performance, and design of the injection strategy and facilities as part of the field development of FAWAG is not trivial and field data is sparse.\u0000 Extensive laboratory experiments and simulation studies are necessary to de-risk enhanced oil recovery (EOR) application, but these processes are time consuming and expensive. For this reason, a screening study is normally conducted to increase the possibility of selecting high potential candidates prior to embarking on the detailed feasibility studies. Unfortunately for FAWAG, the screening criteria are not readily established nor commonly available in commercial screening tools unlike for other matured EOR methods, largely contributed by the limited database on FAWAG field implementations worldwide.\u0000 This paper presents a robust FAWAG screening tool which accounts for important reservoir properties, uncertainties in foam model parameters, as well as various reservoir conditions of oil and gas production and injection plans. The FAWAG process is modelled from the assumption of local equilibrium of foam creation and coalescence using an Implicit Texture model. Relevant foam scan experiments/steady state coreflood data were analyzed to derive parameters that characterize foam dynamics.\u0000 The sensitivity study in this paper ranks and identifies the main risks and opportunities for the FAWAG process, quantifies the reliability of the model and increases the understanding of the effective dynamic behaviour. The sensitivity study was the basis for the development and validation of a proxy model by design of experiments. The screening tool employs this proxy model to generate immediate screening results without the need to run additional simulations. The screening tool was further validated with upscaled experimental data. A set of prediction results on the range of oil recovery for numerous plausible field scenarios was established; these screening criteria will be used as the basis for high-level decision making.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90408771","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}
Timbul Suryatin, Hercules Sitanggang, A. Budiman, P. Frieze
Conventional jacket structures are normally equipped with mat foundations for support during offshore installation when the jacket sits on the seabed before piling. An efficient mudmat design is required to support the jacket since the weight of the mudmat contributes about 20% to the overall structural weight. It is challenging to analyze and to find an exact solution when calculating the bearing capacity of the soil beneath the mudmat because the seabed conditions vary from hard to very soft soil: this is especially true for a relatively slender jacket on very soft soil. The paper presents an efficient method for conducting such design.
{"title":"An Efficient Solution to Mudmat Design for Jacket Structures in Soft Seabed Soil","authors":"Timbul Suryatin, Hercules Sitanggang, A. Budiman, P. Frieze","doi":"10.2118/205529-ms","DOIUrl":"https://doi.org/10.2118/205529-ms","url":null,"abstract":"\u0000 Conventional jacket structures are normally equipped with mat foundations for support during offshore installation when the jacket sits on the seabed before piling. An efficient mudmat design is required to support the jacket since the weight of the mudmat contributes about 20% to the overall structural weight. It is challenging to analyze and to find an exact solution when calculating the bearing capacity of the soil beneath the mudmat because the seabed conditions vary from hard to very soft soil: this is especially true for a relatively slender jacket on very soft soil. The paper presents an efficient method for conducting such design.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88825728","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}
Norah W. Aljuryyed, A. M. A. Moajil, S. Alghamdi, Sajjad Aldarweesh
Development of retarded acid recipes that can have both adequate dissolving power and controllable reaction rate is desired to maximize the effectiveness of matrix stimulation treatments for oil and gas wells. Hydrochloric acid (HCl) has high dissolving power, however, the reaction rate with carbonate rock is uncontrollable and can cause face dissolution. Organic acids have low dissolving power and controllable reaction rate. The objective of this paper was to compare the effectiveness of three low viscosity retarded acid recipes with dissolving powers of 15 wt% and >20 wt% HCl equivalent. The examined acid recipes were 15/28 wt% emulsified acids, retarded acid recipes #1, #2 and #3, and 15/26 wt% HCl. The emulsified acids were at 30:70 ratio of diesel to acid. The retarded acid recipes were prepared at different dissolving power. Retarded acid recipe #3 was equivalent to 15 wt% HCl while retarded acid recipes #1 and #2 were equivalent to >20 wt% HCl. The calcite disc dissolution rate with retarded acids #1 and #2 was significantly lower than 26 wt% HCl and comparable to 15 wt% HCl at 75°F. The solubility of calcite discs in the retarded acid recipe #3 showed acid retardation higher than retarded acid recipes #1 and #2. The corrosion rate of retarded acid recipes #1 and #2 were 0.003-0.015 lb/ft2 at 250°F and 6 hrs, lower than both examined 26-28 wt% HCl and emulsified acids. The pitting indices of retarded acid recipes #1, #2, and #3 were 4, 2, and 1 respectively at 300°F. The pore volumes to breakthrough (PVBT) of retarded acid recipes #1 and #2 were slightly higher than retarded acid recipes #3 at 200°F. The PVBT values for 15 wt% and 28 wt% emulsified acid was comparable to retarded acid recipes #1, #2, and #3, confirming their retardation was effective.
{"title":"Evaluation of High Dissolving-Power Retarded Acid Recipes for Carbonate Acidizing","authors":"Norah W. Aljuryyed, A. M. A. Moajil, S. Alghamdi, Sajjad Aldarweesh","doi":"10.2118/205542-ms","DOIUrl":"https://doi.org/10.2118/205542-ms","url":null,"abstract":"\u0000 Development of retarded acid recipes that can have both adequate dissolving power and controllable reaction rate is desired to maximize the effectiveness of matrix stimulation treatments for oil and gas wells. Hydrochloric acid (HCl) has high dissolving power, however, the reaction rate with carbonate rock is uncontrollable and can cause face dissolution. Organic acids have low dissolving power and controllable reaction rate. The objective of this paper was to compare the effectiveness of three low viscosity retarded acid recipes with dissolving powers of 15 wt% and >20 wt% HCl equivalent.\u0000 The examined acid recipes were 15/28 wt% emulsified acids, retarded acid recipes #1, #2 and #3, and 15/26 wt% HCl. The emulsified acids were at 30:70 ratio of diesel to acid. The retarded acid recipes were prepared at different dissolving power. Retarded acid recipe #3 was equivalent to 15 wt% HCl while retarded acid recipes #1 and #2 were equivalent to >20 wt% HCl.\u0000 The calcite disc dissolution rate with retarded acids #1 and #2 was significantly lower than 26 wt% HCl and comparable to 15 wt% HCl at 75°F. The solubility of calcite discs in the retarded acid recipe #3 showed acid retardation higher than retarded acid recipes #1 and #2. The corrosion rate of retarded acid recipes #1 and #2 were 0.003-0.015 lb/ft2 at 250°F and 6 hrs, lower than both examined 26-28 wt% HCl and emulsified acids. The pitting indices of retarded acid recipes #1, #2, and #3 were 4, 2, and 1 respectively at 300°F. The pore volumes to breakthrough (PVBT) of retarded acid recipes #1 and #2 were slightly higher than retarded acid recipes #3 at 200°F. The PVBT values for 15 wt% and 28 wt% emulsified acid was comparable to retarded acid recipes #1, #2, and #3, confirming their retardation was effective.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91284114","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}
Fuchao Sun, X. Pei, Xubo Gai, Shuang Sun, Shifeng Hu
Polymer flood is proved an effective method for EOR in China. Traditional segmented polymer injection technique cannot obtain continuous layer parameters. Real-time monitoring is necessary for polymer flood because downhole pressure and flowrate vary more often than waterflood. Existing technique for layered monitoring and flowrate adjustment is wireline test. There is no smart technique which can realize real-time monitoring and automatic flowrate control. In this paper, a smart segmented injection technique for polymer flood well is introduced. A smart distributor is permanently placed in each layer. It is composed of flowmeter, temperature sensor, two pressure sensors, downhole choke and electrical control unit. The special flowmeter is adopted for polymer flowrate test. All the distributors are connected together by a single control line which is set outside of the tubing string. Operator can read the data of each layer and adjust the flowrate whenever needed at any time which makes the technique a smart one. The smart technique for polymer flood wells has been implemented in a polymer well in Daqing oilfield of China. A case study for smart segmented polymer injection pilot is introduced in detail including technical principle, indoor test results, construction process and adjustment process. The application results show that the operator on the ground can easily obtain downhole tubing pressure, layer annulus pressure, temperature and flowrate on line. The sample time can be set to any one between 1-65536s according to geological engineer's advice. There is no limitation caused by battery power because the distributor is powered by cable on the ground. In terms of adjustment, the flowrate can be adjusted according to the target value. And it can also be regulated at any time manually, just needing pushing the mouse in the office. The application also displays that the smart segmented technique has the advantage for polymer injection because of larger change of layered parameters. It can provide more real-time data for oil development engineer and the data are beneficial for better understanding and optimization of the reservoir. Therefore, the smart segmented polymer injection has a great potential for EOR based on polymer flood.
{"title":"Smart Segmented Polymer Injection Pilot: A Case Study","authors":"Fuchao Sun, X. Pei, Xubo Gai, Shuang Sun, Shifeng Hu","doi":"10.2118/205702-ms","DOIUrl":"https://doi.org/10.2118/205702-ms","url":null,"abstract":"\u0000 Polymer flood is proved an effective method for EOR in China. Traditional segmented polymer injection technique cannot obtain continuous layer parameters. Real-time monitoring is necessary for polymer flood because downhole pressure and flowrate vary more often than waterflood. Existing technique for layered monitoring and flowrate adjustment is wireline test. There is no smart technique which can realize real-time monitoring and automatic flowrate control. In this paper, a smart segmented injection technique for polymer flood well is introduced. A smart distributor is permanently placed in each layer. It is composed of flowmeter, temperature sensor, two pressure sensors, downhole choke and electrical control unit. The special flowmeter is adopted for polymer flowrate test. All the distributors are connected together by a single control line which is set outside of the tubing string. Operator can read the data of each layer and adjust the flowrate whenever needed at any time which makes the technique a smart one. The smart technique for polymer flood wells has been implemented in a polymer well in Daqing oilfield of China. A case study for smart segmented polymer injection pilot is introduced in detail including technical principle, indoor test results, construction process and adjustment process. The application results show that the operator on the ground can easily obtain downhole tubing pressure, layer annulus pressure, temperature and flowrate on line. The sample time can be set to any one between 1-65536s according to geological engineer's advice. There is no limitation caused by battery power because the distributor is powered by cable on the ground. In terms of adjustment, the flowrate can be adjusted according to the target value. And it can also be regulated at any time manually, just needing pushing the mouse in the office. The application also displays that the smart segmented technique has the advantage for polymer injection because of larger change of layered parameters. It can provide more real-time data for oil development engineer and the data are beneficial for better understanding and optimization of the reservoir. Therefore, the smart segmented polymer injection has a great potential for EOR based on polymer flood.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82468909","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, Hakki Aydin, Bahar F. Hosgor, Deniz Yagmur Kayhan, Raul Moreno
Digital transformation is one of the most discussed themes across the globe. The disruptive potential arising from the joint deployment of IoT, robotics, AI and other advanced technologies is projected to be over $300 trillion over the next decade. With the advances and implementation of these technologies, they have become more widely-used in all aspects of oil and gas industry in several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still trying to adapt to IR 4.0. This paper examines the value that Industry 4.0 brings to the oil and gas upstream industry. It delineates key Industry 4.0 solutions and analyzes their impact within this segment. A comprehensive literature review has been carried out to investigate the IR 4.0 concept's development from the beginning, the technologies it utilizes, types of technologies transferred from other industries with a longer history of use, robustness and applicability of these methods in oil and gas industry under current conditions and the incremental benefits they provide depending on the type of the field are addressed. Real field applications are illustrated with applications indifferent parts of the world with challenges, advantages and drawbacks discussed and summarized that lead to conclusions on the criteria of application of machine learning technologies.
{"title":"A Comprehensive Review of the Fourth Industrial Revolution IR 4.0 in Oil and Gas Industry","authors":"C. Temizel, C. H. Canbaz, Hakki Aydin, Bahar F. Hosgor, Deniz Yagmur Kayhan, Raul Moreno","doi":"10.2118/205772-ms","DOIUrl":"https://doi.org/10.2118/205772-ms","url":null,"abstract":"\u0000 Digital transformation is one of the most discussed themes across the globe. The disruptive potential arising from the joint deployment of IoT, robotics, AI and other advanced technologies is projected to be over $300 trillion over the next decade. With the advances and implementation of these technologies, they have become more widely-used in all aspects of oil and gas industry in several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still trying to adapt to IR 4.0. This paper examines the value that Industry 4.0 brings to the oil and gas upstream industry. It delineates key Industry 4.0 solutions and analyzes their impact within this segment. A comprehensive literature review has been carried out to investigate the IR 4.0 concept's development from the beginning, the technologies it utilizes, types of technologies transferred from other industries with a longer history of use, robustness and applicability of these methods in oil and gas industry under current conditions and the incremental benefits they provide depending on the type of the field are addressed. Real field applications are illustrated with applications indifferent parts of the world with challenges, advantages and drawbacks discussed and summarized that lead to conclusions on the criteria of application of machine learning technologies.","PeriodicalId":10970,"journal":{"name":"Day 1 Tue, October 12, 2021","volume":"2007 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86197263","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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