Steam chamber expanding processes and bottom water invading characteristics during steam flooding in heavy oil reservoirs

Pang, Zhanxi; Wang, Luting; Yin, Fanghao; Lyu, Xiaocong

doi:10.1016/j.energy.2021.121214

Cited by 35 publications

(12 citation statements)

References 35 publications

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“…Pang [24] quantitatively analysed the expansion of the steam cavity and water intrusion at the bottom of the steam cavity during the steam flooding process. The analysis results were used to establish a novel method to study the expansion law of the steam cavity by utilising the energy conservation rate.…”

Section: Introductionmentioning

confidence: 99%

Steam Cavity Expansion Model for Steam Flooding in Deep Heavy Oil Reservoirs

Zhang

et al. 2022

Energies

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Steam flooding is crucial for the development of heavy oil reservoirs, and the development of the steam cavity significantly determines the efficiency of steam flooding. Previous studies have elucidated the concept of steam overburden and pseudomobility ratio; however, the thermal energy loss in deep heavy oil reservoirs during steam injection needs further investigation. Therefore, in this study, the vapour–liquid interface theory and mathematical integration were used to establish a steam cavity expansion model. The wellbore heat loss rate coefficient, steam overlay, and pseudomobility ratio were used to accurately describe the development of the steam cavity in deep heavy oil reservoirs. The proposed model was experimentally validated, and it was observed that the model could accurately reflect the actual mine conditions. In addition, the pressure gradient distribution of the steam belt and the heat dissipation areas of the top and bottom layers of the steam cavity were evaluated. The results showed that the influence of the wellbore heat loss rate coefficient on the pressure gradient of the oil layer was primarily in the range of 5–20 m away from the steam injection well. Furthermore, it was observed that the pseudomobility ratio is inversely proportional to the development of the steam cavity. As the wellbore heat loss rate coefficient increased, the wellbore heat loss increased. The larger the area ratio, the more pronounced the steam overlay phenomenon, and the large area ratio does not meet the development requirements of the steam chamber. The research closely combines theory with production, and the results of this study can help actual mines by providing theoretical support for the development of deep heavy oil reservoirs.

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Section: Introductionmentioning

confidence: 99%

Steam Cavity Expansion Model for Steam Flooding in Deep Heavy Oil Reservoirs

Zhang

et al. 2022

Energies

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“…Therefore, thermal technologies have become an effective means of heavy oil development. Multiple conventional thermal methods of enhancing oil recovery, such as in situ combustion, hot water flooding and steam injection, which include steam huff and puff [5][6][7], steam flooding [8,9] and chemical assisted steam flooding [10], are being used by the oil and gas industry [11]. In addition, new measures, such as electromagnetic heating [12][13][14] and catalytic modification [15], also have significant potential exploration value.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Adaptability of Nonhydrocarbon Gas-Assisted Steam Flooding to the Development of Heavy Oil Reservoirs

Huo

Xiao²,

Chen

et al. 2022

Energies

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In view of the serious heat loss in the process of steam injection for heavy oil recovery, nonhydrocarbon gas combined with steam has attracted much attention in recent years to realize the efficient development of heavy oil. Due to the wide variety of nonhydrocarbon gases, their performance in pressurization, dissolution, viscosity reduction, and heat loss decrease is changeable. In this paper, four groups of one-dimensional physical simulation experiments on different nonhydrocarbon gas-assisted steam flooding methods were carried out, and the effect on oil displacement characteristics under high temperature and pressure conditions was studied. Moreover, the differences in N2, CO2, and flue gas in energy supplementation, heat transfer, and oil recovery efficiency were also analyzed. The results showed that the three nonhydrocarbon gas-assisted steam flooding methods could significantly improve the oil displacement efficiency, which was specifically embodied as a faster oil production rate and longer production period. Compared with pure steam flooding, the recovery was increased by 12.13%, 16.71% and 13.01%, respectively. The effects of N2 in energy supplementation and heat transfer reinforcement were the greatest among the three nonhydrocarbon gases, followed by those of flue gas, and the CO2 effects were the worst. The temperature at the end of the sandpack model increased by 14.3 °C, 8.8 °C and 13.1 °C, respectively. In addition, CO2-assisted steam flooding had a prominent oil recovery effect, and the oil content of the sands in the front and middle of the model was significantly lower than that of other displacement methods. Most importantly, combined with the analysis of the remaining oil in the oil sands after displacement, we explained the contrasting contradictions of the three non-hydrocarbon gases in terms of recovery and energy supply/heat transfer, and further confirmed the gas properties and reservoir adaptability of the three non-hydrocarbon gases. The results may provide a theoretical basis for the selection of nonhydrocarbon gases for heavy oil reservoirs with different production requirements.

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“…Steam flooding is the oldest and most successful commercial enhanced oil recovery (EOR) technique for oil reservoirs that have been used since the 1960s, and it is recognized as one of the most efficient oil recovery techniques for depleting the oil in various types of reservoirs because steam flooding results in higher ultimate oil recovery compared to other EOR techniques. − …”

Section: Introductionmentioning

confidence: 99%

Pattern Recognition for Steam Flooding Field Applications Based on Hierarchical Clustering and Principal Component Analysis

et al. 2022

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Steam flooding is a complex process that has been considered as an effective enhanced oil recovery technique in both heavy oil and light oil reservoirs. Many studies have been conducted on different sets of steam flooding projects using the conventional data analysis methods, while the implementation of machine learning algorithms to find the hidden patterns is rarely found. In this study, a hierarchical clustering algorithm (HCA) coupled with principal component analysis is used to analyze the steam flooding projects worldwide. The goal of this research is to group similar steam flooding projects into the same cluster so that valuable operational design experiences and production performance from the analogue cases can be referenced for decision-making. Besides, hidden patterns embedded in steam flooding applications can be revealed based on data characteristics of each cluster for different reservoir/fluid conditions. In this research, principal component analysis is applied to project original data to a new feature space, which finds two principal components to represent the eight reservoir/fluid parameters (8D) but still retain about 90% of the variance. HCA is implemented with the optimized design of five clusters, Euclidean distance, and Ward’s linkage method. The results of the hierarchical clustering depict that each cluster detects a unique range of each property, and the analogue cases present that fields under similar reservoir/fluid conditions could share similar operational design and production performance.

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Steam chamber expanding processes and bottom water invading characteristics during steam flooding in heavy oil reservoirs

Cited by 35 publications

References 35 publications

Steam Cavity Expansion Model for Steam Flooding in Deep Heavy Oil Reservoirs

Steam Cavity Expansion Model for Steam Flooding in Deep Heavy Oil Reservoirs

A Study on the Adaptability of Nonhydrocarbon Gas-Assisted Steam Flooding to the Development of Heavy Oil Reservoirs

Pattern Recognition for Steam Flooding Field Applications Based on Hierarchical Clustering and Principal Component Analysis

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