Gas hydrates are acquainted as a significant topic to the oil and gas flow assurance, as it creates pipelines occlusions. The formation of gas hydrates can create many functional issues such as: stop of production, high preservation expenditures, environmental dangers and even loss of human beings. In this work five different amino acids such as: leucine, methionine, phenylalanine, glycine and asparagine examined if they work as kinetic inhibitors on mixture gas hydrate formation. The outcomes indicated that phenylalanine, asparagine and glycine (phenylalanine>asparagine>glycine) behaved as inhibitors following the rank from most powerful to less one while leucine and methionine behaved as promoters (leucine>methionine) for both hydrate formation and induction time.
{"title":"Examination of Five Amino Acids as Gas Hydrate Kinetic Inhibitors in Oil and Gas Industry","authors":"S. Longinos, Dimitra Longinou, Lei Wang","doi":"10.2118/209701-ms","DOIUrl":"https://doi.org/10.2118/209701-ms","url":null,"abstract":"\u0000 Gas hydrates are acquainted as a significant topic to the oil and gas flow assurance, as it creates pipelines occlusions. The formation of gas hydrates can create many functional issues such as: stop of production, high preservation expenditures, environmental dangers and even loss of human beings. In this work five different amino acids such as: leucine, methionine, phenylalanine, glycine and asparagine examined if they work as kinetic inhibitors on mixture gas hydrate formation. The outcomes indicated that phenylalanine, asparagine and glycine (phenylalanine>asparagine>glycine) behaved as inhibitors following the rank from most powerful to less one while leucine and methionine behaved as promoters (leucine>methionine) for both hydrate formation and induction time.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130509602","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}
Meng Wang, Ming-guang Che, Yun Jiang, Chunming He, Dingwei Weng, G. Zhu
There are more than 1300 horizontal wells in the Sichuan Basin shale reservoirsthat produce more than 20 billion cubic meters of gas in 2021. A test production of best-performing shale gas pad,so far in China, consisting of 8 horizontal wells, is over 4.7 × 106 m³/d (167.7 MMcf/d). The average EUR per well is estimated to exceed 2.0 × 108 m³(7.0 bcf).The underlying geological controlling factors including TOC content, porosity, gas saturation and brittle mineral content for these prolific wells were analyzed. The length of the well laterals drilling into the sweetest pay zone was characterized by well logging. The strategies of optimizing drilling and completion strategies used in these wells are discussed. In addition, the solutions to deal with the frequent occurrence of casing deformation are also proposed and adopted. Rate transient analysis was performed on these wells to assess the stimulation efficiency, which was further compared with those wells treated by conventional stimulationstrategies. It was found that the thickness and length of the completion in the highest quality pay zone are the two main geological controlling factors for the prolific wells. Different from the conventional stimulation strategies, the eight wells in one pad were all treated using higher intensity stimulation strategies. The average spacing between treated stages ranges from 85 m to 91 m, with tighter cluster spacing. Fracturing was temporarily plugged to passively treat sever deformation in two laterals consisting of 29 stages (total length of 2068m). Compared with the neighboring offset wells, the average bulk linear flow parameter of these eight well is 72% higher. Integration of geological designs (like sweet spot optimization) and engineering designs (such as tighter cluster spacing within longer stages, temporarily plugging fracturingand using more proppants), created a high-productivity template for the next stage of efficient developments of shale gas. The findings obtained in this study are also beneficial to unlock unconventional resources including shale oil and tight gas in China.
{"title":"What Have We Learn from the Most Prolific Pad of Shale Gas in the Sichuan Basin?","authors":"Meng Wang, Ming-guang Che, Yun Jiang, Chunming He, Dingwei Weng, G. Zhu","doi":"10.2118/209703-ms","DOIUrl":"https://doi.org/10.2118/209703-ms","url":null,"abstract":"\u0000 There are more than 1300 horizontal wells in the Sichuan Basin shale reservoirsthat produce more than 20 billion cubic meters of gas in 2021. A test production of best-performing shale gas pad,so far in China, consisting of 8 horizontal wells, is over 4.7 × 106 m³/d (167.7 MMcf/d). The average EUR per well is estimated to exceed 2.0 × 108 m³(7.0 bcf).The underlying geological controlling factors including TOC content, porosity, gas saturation and brittle mineral content for these prolific wells were analyzed. The length of the well laterals drilling into the sweetest pay zone was characterized by well logging. The strategies of optimizing drilling and completion strategies used in these wells are discussed. In addition, the solutions to deal with the frequent occurrence of casing deformation are also proposed and adopted. Rate transient analysis was performed on these wells to assess the stimulation efficiency, which was further compared with those wells treated by conventional stimulationstrategies. It was found that the thickness and length of the completion in the highest quality pay zone are the two main geological controlling factors for the prolific wells. Different from the conventional stimulation strategies, the eight wells in one pad were all treated using higher intensity stimulation strategies. The average spacing between treated stages ranges from 85 m to 91 m, with tighter cluster spacing. Fracturing was temporarily plugged to passively treat sever deformation in two laterals consisting of 29 stages (total length of 2068m). Compared with the neighboring offset wells, the average bulk linear flow parameter of these eight well is 72% higher. Integration of geological designs (like sweet spot optimization) and engineering designs (such as tighter cluster spacing within longer stages, temporarily plugging fracturingand using more proppants), created a high-productivity template for the next stage of efficient developments of shale gas. The findings obtained in this study are also beneficial to unlock unconventional resources including shale oil and tight gas in China.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"65 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120907920","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}
E. Gurina, Nikita Klyuchnikov, Ksenia Antipova, D. Koroteev
A significant proportion of capital and operational expenditures of oil and gas companies falls on the well construction. Unexpected situations inevitably happen during drilling regardless of the well's construction technology level and available information. These situations lead to more spending and noon-productive time. We present a machine learning (ML) algorithm for predicting accidents such as stuck, mud loss, and fluid show as the most common accidents in the industry. The model for forecasting the drilling accidents is based on the Bag-of-features approach, which implies labeling segments of surface telemetry data by the particular symbol, named codeword, from the defined codebook. Building histograms of symbols for the one-hour telemetry interval, one could use the histogram as an input for the machine learning algorithm. For the ML model training, we use data from more than 100 drilling accidents from different oil and gas wells, where we defined more than 3000 drilling accident predecessors and about 5000 normal drilling segments. Model performance was estimated using two major metrics.The coveragemetric, indicates the ratio of true forecasted events. Number of false alarms per day metricfor the specified probability threshold. Using different schemes of metric calculation, one could evaluate the model's ability to both forecast and detect accidents. Validation tests justify that our algorithm performs well on historical and real-time data. At each moment, the model analyzes the real-time data for the last hour and provides the probability of whether the segments contain the signs of drilling accident predecessors of a particular type. The prediction quality does not vary from field to field, so the ML model can be used in different fields without additional training. Nowadays model is tested in real oilfields in Russia. To operate the model, we developed software integrated with the Wellsite Information Transfer Standard Markup Language (WITSML) data server into clients' existing IT infrastructure. All calculations arein the cloud anddo not require significant additional computing power on client side.
{"title":"Application of Bag-of-Features Approach to Drilling Accidents Forecasting","authors":"E. Gurina, Nikita Klyuchnikov, Ksenia Antipova, D. Koroteev","doi":"10.2118/209643-ms","DOIUrl":"https://doi.org/10.2118/209643-ms","url":null,"abstract":"\u0000 A significant proportion of capital and operational expenditures of oil and gas companies falls on the well construction. Unexpected situations inevitably happen during drilling regardless of the well's construction technology level and available information. These situations lead to more spending and noon-productive time. We present a machine learning (ML) algorithm for predicting accidents such as stuck, mud loss, and fluid show as the most common accidents in the industry.\u0000 The model for forecasting the drilling accidents is based on the Bag-of-features approach, which implies labeling segments of surface telemetry data by the particular symbol, named codeword, from the defined codebook. Building histograms of symbols for the one-hour telemetry interval, one could use the histogram as an input for the machine learning algorithm. For the ML model training, we use data from more than 100 drilling accidents from different oil and gas wells, where we defined more than 3000 drilling accident predecessors and about 5000 normal drilling segments.\u0000 Model performance was estimated using two major metrics.The coveragemetric, indicates the ratio of true forecasted events. Number of false alarms per day metricfor the specified probability threshold. Using different schemes of metric calculation, one could evaluate the model's ability to both forecast and detect accidents. Validation tests justify that our algorithm performs well on historical and real-time data. At each moment, the model analyzes the real-time data for the last hour and provides the probability of whether the segments contain the signs of drilling accident predecessors of a particular type. The prediction quality does not vary from field to field, so the ML model can be used in different fields without additional training.\u0000 Nowadays model is tested in real oilfields in Russia. To operate the model, we developed software integrated with the Wellsite Information Transfer Standard Markup Language (WITSML) data server into clients' existing IT infrastructure. All calculations arein the cloud anddo not require significant additional computing power on client side.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"33 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120820896","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}
Mohamed Salim Al-Fazari, Abdullah Khalifa AL-Hinai, Hilal Mohammed AL-Ghefeili
Petroleum Development Oman LLC (PDO) is Oman's premier oil producer and operates several fields at "A". "A" East and "A" West are located on the eastern flank of the South Oman Salt Basin. As "A" thermal fields contain heavy oil, PDO plans to significantly increase oil recovery by increasing steam injection, which has high energy intensity. The objective of this paper is to demonstrate that the improvement in thermal EOR operation by initiating decarbonization initiatives resulted in a significant reduction in Green House Gases (GHG) emissions. Operational comparison of steam generation unit cost to produce one tonnage of steam for different combinations found that OTSGs is the most expensive combination as it is associated with higher taxation cost (i.e. 90% of total cost is from carbon tax). OT-HRSGs with Miraah Solar combination is found one of the best to reduce the overall unit cost and maximize the production. The Miraah Solar facility was built at "A" to cater for the steam growth requirement. The adaptation of Miraah shall reduce the annual gas usage related to steam production by utilizing the sun's radiation. This facility is one of the largest solar plants of its kind in the world. It has an energy production capacity of 330 MWe of peak thermal energy and daily steam output of 1,980 tons per day. An Energy Assessment (EA) had has been conducted for top energy consumers (e.g. OT-HRSGs, OTSGs, export pumps, etc.) to identify the top high GHG emitters and feature opportunities to reduce their carbon footprint. Miraah Solar enhancement was one of the identified opportunities that will result in GHG saving more than 100,000 TCO2e/yr. In 2021, a 41% improvement is seen in terms of production and GHG reduction. In addition, the Thermal Steam Integration System (SIS) is an integrated and novel system developed to allow all steam generators to be integrated into a system that will smooth the operation and enhance the availability of the steam system/network in both on-plot and off-plot.. This will allow us to reduce GHG emissions from steam systems by 80,000 tons CO2/year by 2030, as well as reduce power consumption by more than 36% from the base case.
{"title":"Decarbonizing Thermal Enhanced Oil Recovery Operations Through Improvements in Saturated Steam Distribution System","authors":"Mohamed Salim Al-Fazari, Abdullah Khalifa AL-Hinai, Hilal Mohammed AL-Ghefeili","doi":"10.2118/209674-ms","DOIUrl":"https://doi.org/10.2118/209674-ms","url":null,"abstract":"\u0000 Petroleum Development Oman LLC (PDO) is Oman's premier oil producer and operates several fields at \"A\". \"A\" East and \"A\" West are located on the eastern flank of the South Oman Salt Basin. As \"A\" thermal fields contain heavy oil, PDO plans to significantly increase oil recovery by increasing steam injection, which has high energy intensity.\u0000 The objective of this paper is to demonstrate that the improvement in thermal EOR operation by initiating decarbonization initiatives resulted in a significant reduction in Green House Gases (GHG) emissions.\u0000 Operational comparison of steam generation unit cost to produce one tonnage of steam for different combinations found that OTSGs is the most expensive combination as it is associated with higher taxation cost (i.e. 90% of total cost is from carbon tax). OT-HRSGs with Miraah Solar combination is found one of the best to reduce the overall unit cost and maximize the production.\u0000 The Miraah Solar facility was built at \"A\" to cater for the steam growth requirement. The adaptation of Miraah shall reduce the annual gas usage related to steam production by utilizing the sun's radiation. This facility is one of the largest solar plants of its kind in the world. It has an energy production capacity of 330 MWe of peak thermal energy and daily steam output of 1,980 tons per day.\u0000 An Energy Assessment (EA) had has been conducted for top energy consumers (e.g. OT-HRSGs, OTSGs, export pumps, etc.) to identify the top high GHG emitters and feature opportunities to reduce their carbon footprint. Miraah Solar enhancement was one of the identified opportunities that will result in GHG saving more than 100,000 TCO2e/yr. In 2021, a 41% improvement is seen in terms of production and GHG reduction.\u0000 In addition, the Thermal Steam Integration System (SIS) is an integrated and novel system developed to allow all steam generators to be integrated into a system that will smooth the operation and enhance the availability of the steam system/network in both on-plot and off-plot.. This will allow us to reduce GHG emissions from steam systems by 80,000 tons CO2/year by 2030, as well as reduce power consumption by more than 36% from the base case.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130615758","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 presents field-scale compositional reservoir flow modeling in the DND tight gas field, to demonstrate the relative partitioning of 3 during and after CO2 injection. The model was developed to study the effect of structural trapping, solubility trapping, residual trapping, and mineralization trapping on the partitioning of CO2 in gas (free or residual), and brine phases over time. Furthermore, we investigated the impact of various injection scenarios, such as Injection pressure, Injection rate and Injection time, on the different trapping mechanisms. First, we used a high-resolution geo-model, which was constructed from wireline logs, seismic surveys, core data, and stratigraphic interpretation. As the initial distribution of fluids plays a vital role in CO2 partitioning, a comprehensive pressure-production history matching was completed. The hysteresis model was used to calculate the amount of CO2 trapped as residual. The water-rock reaction models among CO2 and minerals were added to analyze the mineralization trapping mechanism. CO2 solubility into brine was verified based on experiments. The model results show a new understanding of relative CO2 partitioning in porous media. Although it was believed that structural trapping is the largest of the trapping mechanisms during CO2 injection and post-injection, our results show that in sandstone tight gas field like DND tight gas field, the solubility of CO2 in gas plays a very important role, even in the first stage of CO2 injection. Porosity changes caused by the reaction among CO2 and different minerals during CO2 storage were also analyzed. Comprehensive models were run to estimate the amount of trapped CO2 during and after the injection period. The present work provides valuable insights for optimizing gas production and CO2 storage in sandstone reservoirs like DND tight gas field.
{"title":"Impact of Field Development Strategies on CO2 Trapping Mechanisms: A Case Study of CO2-EGR in the DND Tight Gas Field","authors":"Ying Jia, Lei Huang, Jin Yan","doi":"10.2118/209718-ms","DOIUrl":"https://doi.org/10.2118/209718-ms","url":null,"abstract":"\u0000 This paper presents field-scale compositional reservoir flow modeling in the DND tight gas field, to demonstrate the relative partitioning of 3 during and after CO2 injection. The model was developed to study the effect of structural trapping, solubility trapping, residual trapping, and mineralization trapping on the partitioning of CO2 in gas (free or residual), and brine phases over time. Furthermore, we investigated the impact of various injection scenarios, such as Injection pressure, Injection rate and Injection time, on the different trapping mechanisms. First, we used a high-resolution geo-model, which was constructed from wireline logs, seismic surveys, core data, and stratigraphic interpretation. As the initial distribution of fluids plays a vital role in CO2 partitioning, a comprehensive pressure-production history matching was completed. The hysteresis model was used to calculate the amount of CO2 trapped as residual. The water-rock reaction models among CO2 and minerals were added to analyze the mineralization trapping mechanism. CO2 solubility into brine was verified based on experiments. The model results show a new understanding of relative CO2 partitioning in porous media. Although it was believed that structural trapping is the largest of the trapping mechanisms during CO2 injection and post-injection, our results show that in sandstone tight gas field like DND tight gas field, the solubility of CO2 in gas plays a very important role, even in the first stage of CO2 injection. Porosity changes caused by the reaction among CO2 and different minerals during CO2 storage were also analyzed. Comprehensive models were run to estimate the amount of trapped CO2 during and after the injection period. The present work provides valuable insights for optimizing gas production and CO2 storage in sandstone reservoirs like DND tight gas field.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124825154","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}
Smart water injection (SWI) and carbonate water injection (CWI) have been successfully used in enhanced oil recovery (EOR) due to favorable crude oil-brine-rock interactions. In this study, these two EOR methods are combined as one hybrid EOR process namely carbonated smart water injection (CSWI). An attempt was made to study the EOR potential in sandstone reservoirs of Upper Assam Basin in India. The synergetic effects in CSIR arises due to analogy between CO2 solubility in brine and composition/concentration of brine. First, characterization of reservoir rock and fluids collected from major producing oilfields of Upper Assam Basin. Second, optimal smart water for the candidate reservoirs determined by measuring the contact angles and oil-water IFT at different compositions and concentrations of formation water. Third, preparation of carbonated smart water and effect on reservoir rock wettability. Fourth, screening optimal carbonated smart water solutions. Fifth, applicability of the CSWI method as an EOR technique in sandstone reservoirs investigated using lab-scale core flooding experiments and the results compared with the oil recovery by SWI and CWI methods. The analyses also marked the crude as medium gravity, acidic and suitable for alkaline flooding. The formation water analysis showed the presence of different types of dissolved cations and anions with total salinity of 9534 ppm. From the original oil-wet (ϴ = 115°) state of the core, wettability alteration to intermediate-wet (ϴ = 79°) conditions were achieved with smart water. The IFT experiments demonstrated the EOR potential of smart water as the oil-water was reduced by more than half from the initial 22.18 to 7.59 mN/m. The use of carbonated water on the core surface changed core wettability to a water-wet because there was a reduction in the pH of the aqueous phase, and this modified the charges on the oil/water, and water/rock interfaces, and hence the wettability of the system. Optimal CSWI formulations screened based on contact angle and IFT measurements were used for tertiary flooding resulted in incremental oil recovery of approximately 14.44 % oil in place. This recovery was sufficiently higher than the HSB and LSB flood recoveries of 35.98% and 45.38% respectively. Thus, the core flooding highlighted the EOR potential of CSWI in sandstone reservoirs. The combined CSWI process when applied to sandstone reservoirs increases the efficiency of wettability alteration due to the ability of carbonated smart water to modify the crude oil-brine-rock interactions. Thus, both CWI and SWI can be effectively combined and engineered to achieve improved oil recovery in sandstone reservoirs. Moreover, during CSWI processCO2 moves from the brine into the oil phase, which altered the reservoir rock characteristics and the physical properties of reservoir fluids.
{"title":"Carbonated Smart Water Injection for Enhanced Oil Recovery in Sandstone Reservoirs of Upper Assam Basin, India","authors":"Ramanpreet Singh Vadhan, R. Phukan","doi":"10.2118/209671-ms","DOIUrl":"https://doi.org/10.2118/209671-ms","url":null,"abstract":"\u0000 Smart water injection (SWI) and carbonate water injection (CWI) have been successfully used in enhanced oil recovery (EOR) due to favorable crude oil-brine-rock interactions. In this study, these two EOR methods are combined as one hybrid EOR process namely carbonated smart water injection (CSWI). An attempt was made to study the EOR potential in sandstone reservoirs of Upper Assam Basin in India. The synergetic effects in CSIR arises due to analogy between CO2 solubility in brine and composition/concentration of brine. First, characterization of reservoir rock and fluids collected from major producing oilfields of Upper Assam Basin. Second, optimal smart water for the candidate reservoirs determined by measuring the contact angles and oil-water IFT at different compositions and concentrations of formation water. Third, preparation of carbonated smart water and effect on reservoir rock wettability. Fourth, screening optimal carbonated smart water solutions. Fifth, applicability of the CSWI method as an EOR technique in sandstone reservoirs investigated using lab-scale core flooding experiments and the results compared with the oil recovery by SWI and CWI methods. The analyses also marked the crude as medium gravity, acidic and suitable for alkaline flooding. The formation water analysis showed the presence of different types of dissolved cations and anions with total salinity of 9534 ppm. From the original oil-wet (ϴ = 115°) state of the core, wettability alteration to intermediate-wet (ϴ = 79°) conditions were achieved with smart water. The IFT experiments demonstrated the EOR potential of smart water as the oil-water was reduced by more than half from the initial 22.18 to 7.59 mN/m. The use of carbonated water on the core surface changed core wettability to a water-wet because there was a reduction in the pH of the aqueous phase, and this modified the charges on the oil/water, and water/rock interfaces, and hence the wettability of the system. Optimal CSWI formulations screened based on contact angle and IFT measurements were used for tertiary flooding resulted in incremental oil recovery of approximately 14.44 % oil in place. This recovery was sufficiently higher than the HSB and LSB flood recoveries of 35.98% and 45.38% respectively. Thus, the core flooding highlighted the EOR potential of CSWI in sandstone reservoirs. The combined CSWI process when applied to sandstone reservoirs increases the efficiency of wettability alteration due to the ability of carbonated smart water to modify the crude oil-brine-rock interactions. Thus, both CWI and SWI can be effectively combined and engineered to achieve improved oil recovery in sandstone reservoirs. Moreover, during CSWI processCO2 moves from the brine into the oil phase, which altered the reservoir rock characteristics and the physical properties of reservoir fluids.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130347920","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 application and implementation of streamline derived rate targets have proven to increase oil production and reduce water cut with minimal investment (Kornberger & Thiele, 2014). The Matzen field, and in particular the 16.TH layer, has significant peripheral water injection as well as a large operating range on the production and injection wells, making it an ideal candidate for streamline based water flood optimization measures. A multidisciplinary approach was taken to modelling the 16.TH, incorporating and analyzing data including pressures, production & injection volumes as well as individual well operational envelopes. Several uncertainties surrounding the field were also addressed in the modelling approach, for example faults and their transmissibilities. As a result, robust streamline derived rate targets could be defined and implemented across approximately 30% of the active wells in the field (around 60 wells), which significantly improved the production performance. Following implementation, the performance was continuously monitored, with impressive results. Implementation of the rate targets, resulted in a field wide daily production rate increase of up to 5%, peaking at 26 m3/day (165 boe/day) with an increase of only 140 m3/day on the liquid production and an increase of 160 m3/day water injection, exceptional for a field with an average water cut of 98%. Despite the positive results, there were several lessons learned that are discussed in the paper and can be applied to future field implementation to improve the performance further. It has been again proven that implementation of streamline derived rate targets can provide significant value, and through a defined workflow and automatic model updates this value can be realized faster, more reliably and with less manpower, offering an effective method of managing a water flooded asset and maximizing its value.
{"title":"Implementation of Streamline Derived Rate Targets Improved Oil Production of Mature Field","authors":"S. Adamson, I. Giden, Ronald Matzka-Pöll","doi":"10.2118/209679-ms","DOIUrl":"https://doi.org/10.2118/209679-ms","url":null,"abstract":"\u0000 The application and implementation of streamline derived rate targets have proven to increase oil production and reduce water cut with minimal investment (Kornberger & Thiele, 2014). The Matzen field, and in particular the 16.TH layer, has significant peripheral water injection as well as a large operating range on the production and injection wells, making it an ideal candidate for streamline based water flood optimization measures.\u0000 A multidisciplinary approach was taken to modelling the 16.TH, incorporating and analyzing data including pressures, production & injection volumes as well as individual well operational envelopes. Several uncertainties surrounding the field were also addressed in the modelling approach, for example faults and their transmissibilities. As a result, robust streamline derived rate targets could be defined and implemented across approximately 30% of the active wells in the field (around 60 wells), which significantly improved the production performance.\u0000 Following implementation, the performance was continuously monitored, with impressive results. Implementation of the rate targets, resulted in a field wide daily production rate increase of up to 5%, peaking at 26 m3/day (165 boe/day) with an increase of only 140 m3/day on the liquid production and an increase of 160 m3/day water injection, exceptional for a field with an average water cut of 98%.\u0000 Despite the positive results, there were several lessons learned that are discussed in the paper and can be applied to future field implementation to improve the performance further.\u0000 It has been again proven that implementation of streamline derived rate targets can provide significant value, and through a defined workflow and automatic model updates this value can be realized faster, more reliably and with less manpower, offering an effective method of managing a water flooded asset and maximizing its value.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132288836","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}
History matching methods are widely used to extract relative permeability curves as well as other uncertain parameters, which cannot be measured accurately through laboratory analysis. This study presents the results of gas flooding experiments in composite chalk cores and seeks a systematic approach toward overcoming the challenges encountered during history matching of the performed experiments. Two vertical core flooding experiments are conducted on tight chalk composite cores at two different pressures providing immiscible and near-miscible conditions for the natural gas and live oil used. An EoS (equation of state) model tuned with routine PVT tests as well as swelling data is used to simulate the experiments by Eclipse compositional simulator E300. Difficulties encountered in the process of history matching are addressed, and a proper method to be implemented to resolve each of the problems is proposed and investigated in detail. A common drawback in compositional simulation of gas injection processes is the excessive vaporization of oil into gas due to local equilibrium assumption, which leads to over-predicting the oil production. It is shown that using a proper technique such as the Sorm method (available in Eclipse via SOR keyword) can be an efficient solution to overcome this issue. It is also established that in the absence of enough reliable data for absolute and relative permeability, these parameters can be subjected to modification and improvement based on experimental observations such as gas breakthrough time and the pressure difference across the core. Furthermore, the change of relative permeability due to the reduction of IFT (interfacial tension) at near-miscible conditions is studied in detail, and the contradicting findings in this area reported by various authors in the literature are elaborately discussed. Different approaches for correcting the relative permeability of the wetting and non-wetting phases are examined in the history matching process and the obtained results are evaluated by being compared to the experimental results of this study. The findings of this work can help to identify and resolve some of the most common problems in compositional simulation of gas injection processes. These results should specifically be taken into consideration in upscaling the reservoir characteristics and performing field-scale simulations in order to obtain reliable results for the future performance of the field.
{"title":"Immiscible and Near-Miscible Gas Flooding in Tight Chalk: Laboratory Experiments and Compositional Simulation","authors":"S. Mirazimi, D. Olsen, E. Stenby, Wei Yan","doi":"10.2118/209683-ms","DOIUrl":"https://doi.org/10.2118/209683-ms","url":null,"abstract":"\u0000 History matching methods are widely used to extract relative permeability curves as well as other uncertain parameters, which cannot be measured accurately through laboratory analysis. This study presents the results of gas flooding experiments in composite chalk cores and seeks a systematic approach toward overcoming the challenges encountered during history matching of the performed experiments.\u0000 Two vertical core flooding experiments are conducted on tight chalk composite cores at two different pressures providing immiscible and near-miscible conditions for the natural gas and live oil used. An EoS (equation of state) model tuned with routine PVT tests as well as swelling data is used to simulate the experiments by Eclipse compositional simulator E300. Difficulties encountered in the process of history matching are addressed, and a proper method to be implemented to resolve each of the problems is proposed and investigated in detail.\u0000 A common drawback in compositional simulation of gas injection processes is the excessive vaporization of oil into gas due to local equilibrium assumption, which leads to over-predicting the oil production. It is shown that using a proper technique such as the Sorm method (available in Eclipse via SOR keyword) can be an efficient solution to overcome this issue. It is also established that in the absence of enough reliable data for absolute and relative permeability, these parameters can be subjected to modification and improvement based on experimental observations such as gas breakthrough time and the pressure difference across the core. Furthermore, the change of relative permeability due to the reduction of IFT (interfacial tension) at near-miscible conditions is studied in detail, and the contradicting findings in this area reported by various authors in the literature are elaborately discussed. Different approaches for correcting the relative permeability of the wetting and non-wetting phases are examined in the history matching process and the obtained results are evaluated by being compared to the experimental results of this study.\u0000 The findings of this work can help to identify and resolve some of the most common problems in compositional simulation of gas injection processes. These results should specifically be taken into consideration in upscaling the reservoir characteristics and performing field-scale simulations in order to obtain reliable results for the future performance of the field.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127833244","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}
Low salinity waterflood (LSWF) injection is an enhanced oil recovery (EOR) method proven effective through extensive experimental studies. Correct implementation of this method in reservoir-scale simulations requires reliable estimation of changes in relative permeability data associated with LSWF. For this purpose, a few models have been suggested based on geochemical interactions, such as the cation exchange capacity of clay, which are case dependent and cannot be applied to all systems. This study presents a novel semi-empirical model based on incremental oil recovery measured during low salinity injection. Therefore, it can be applied to all rock types, fluid systems, and wettability conditions regardless of the active mechanism. Some mechanisms proposed in the literature relate the additional oil recovery during low salinity injection to measurable parameters such as micro-dispersion. As a result, the kr curves can be constructed using this new methodology by measuring the micro-dispersion. This method has been validated against five sets of secondary and tertiary coreflood experiments published in the literature. First, the high salinity kr data is obtained by history matching using the CMOST module of CMG software. Then the proposed method and the measured value of additional oil recovery were used to estimate the kr data of low salinity injection. The results showed that the suggested method could predict the oil recovery and pressure drop in secondary and tertiary modes. The high-salinity relative permeability was shifted towards a more water-wet condition in tertiary mode. The kr curve of secondary LSWF showed a significant shift towards a more water-wet condition than tertiary mode, implying lower residual oil saturation. Since the additional oil recovery versus micro-dispersion curve was reported for this rock sample, one can simply predict the kr values of LSWF for other values of micro-dispersion. Due to the ongoing debate regarding the dominant mechanism during LSWF, there is no universal model for estimating the relative permeability of LSWF in all systems. The model presented in this paper provides a powerful tool for engineers to simulate the LSWF kr data in both tertiary and secondary flooding regardless of the active mechanism.
{"title":"A Universal Method for Predicting the Relative Permeability Data of Low Salinity Injection","authors":"Abdulla Aljaberi, S. Aghabozorgi, M. Sohrabi","doi":"10.2118/209661-ms","DOIUrl":"https://doi.org/10.2118/209661-ms","url":null,"abstract":"\u0000 Low salinity waterflood (LSWF) injection is an enhanced oil recovery (EOR) method proven effective through extensive experimental studies. Correct implementation of this method in reservoir-scale simulations requires reliable estimation of changes in relative permeability data associated with LSWF. For this purpose, a few models have been suggested based on geochemical interactions, such as the cation exchange capacity of clay, which are case dependent and cannot be applied to all systems.\u0000 This study presents a novel semi-empirical model based on incremental oil recovery measured during low salinity injection. Therefore, it can be applied to all rock types, fluid systems, and wettability conditions regardless of the active mechanism. Some mechanisms proposed in the literature relate the additional oil recovery during low salinity injection to measurable parameters such as micro-dispersion. As a result, the kr curves can be constructed using this new methodology by measuring the micro-dispersion.\u0000 This method has been validated against five sets of secondary and tertiary coreflood experiments published in the literature. First, the high salinity kr data is obtained by history matching using the CMOST module of CMG software. Then the proposed method and the measured value of additional oil recovery were used to estimate the kr data of low salinity injection. The results showed that the suggested method could predict the oil recovery and pressure drop in secondary and tertiary modes. The high-salinity relative permeability was shifted towards a more water-wet condition in tertiary mode. The kr curve of secondary LSWF showed a significant shift towards a more water-wet condition than tertiary mode, implying lower residual oil saturation. Since the additional oil recovery versus micro-dispersion curve was reported for this rock sample, one can simply predict the kr values of LSWF for other values of micro-dispersion.\u0000 Due to the ongoing debate regarding the dominant mechanism during LSWF, there is no universal model for estimating the relative permeability of LSWF in all systems. The model presented in this paper provides a powerful tool for engineers to simulate the LSWF kr data in both tertiary and secondary flooding regardless of the active mechanism.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115310063","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 average recovery factor of current producing oil reservoirs is about 35-50% worldwide. Enhanced Oil Recovery (EOR) methods such as Water Alternating Gas (WAG) target the oil left in place and improve the final recovery of the developed fields. In a WAG injection plan, some reservoir blocks experience simultaneous gas and water flow. Therefore, Simultaneous Water And Gas (SWAG) injection experiments are performed to understand and simulate the fluid flow behaviour in these blocks more accurately. The experimental data we analyzed in this manuscript were obtained by performing a SWAG experiment using real reservoir rock and fluid (mixed-wet carbonate rock extracted from the Abu-Dhabi field). In miscible and immiscible experiments, the injected gas was Methane and CO2, respectively. We tried to simulate the experiments using Stone's, Baker's, and Stone's exponent models to evaluate the performance of these models in simulating SWAG experiments. It was shown that SWAG displacement can be simulated using Stone's first model and changing two-phase kr data as a matching parameter. The results showed that we do not need to correct the three-phase relative permeability in the low oil saturation region for simulating SWAG experiments. The study presented in this paper is novel in two aspects: first, the SWAG experiments were conducted in reservoir carbonate samples using real reservoir fluids; and second, even though many researchers have simulated the WAG experiments, not many have discussed the simulation of SWAG experiments. The results presented in this paper is of utmost importance for decision making, designing, and simulating CO2-EOR plans in giant Abu-Dhabi carbonate reservoirs.
{"title":"Investigation and Simulation of SWAG injections Performed in Mixed-Wet Carbonate Rocks.","authors":"Latifa Obaid Alnuaimi, S. Aghabozorgi, M. Sohrabi","doi":"10.2118/209651-ms","DOIUrl":"https://doi.org/10.2118/209651-ms","url":null,"abstract":"\u0000 The average recovery factor of current producing oil reservoirs is about 35-50% worldwide. Enhanced Oil Recovery (EOR) methods such as Water Alternating Gas (WAG) target the oil left in place and improve the final recovery of the developed fields. In a WAG injection plan, some reservoir blocks experience simultaneous gas and water flow. Therefore, Simultaneous Water And Gas (SWAG) injection experiments are performed to understand and simulate the fluid flow behaviour in these blocks more accurately.\u0000 The experimental data we analyzed in this manuscript were obtained by performing a SWAG experiment using real reservoir rock and fluid (mixed-wet carbonate rock extracted from the Abu-Dhabi field). In miscible and immiscible experiments, the injected gas was Methane and CO2, respectively. We tried to simulate the experiments using Stone's, Baker's, and Stone's exponent models to evaluate the performance of these models in simulating SWAG experiments. It was shown that SWAG displacement can be simulated using Stone's first model and changing two-phase kr data as a matching parameter. The results showed that we do not need to correct the three-phase relative permeability in the low oil saturation region for simulating SWAG experiments.\u0000 The study presented in this paper is novel in two aspects: first, the SWAG experiments were conducted in reservoir carbonate samples using real reservoir fluids; and second, even though many researchers have simulated the WAG experiments, not many have discussed the simulation of SWAG experiments. The results presented in this paper is of utmost importance for decision making, designing, and simulating CO2-EOR plans in giant Abu-Dhabi carbonate reservoirs.","PeriodicalId":148855,"journal":{"name":"Day 4 Thu, June 09, 2022","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115518162","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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