Whole-time scenario optimization of steam-assisted gravity drainage (SAGD) with temperature, pressure, and rate control using an efficient hybrid optimization technique

Mir, Hamed; Siavashi, Majid

doi:10.1016/j.energy.2021.122149

Cited by 10 publications

(4 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The spacing between adjacent SAGD wells not only determines the individual well production performance, but also influences the duration of steam chamber interaction between adjacent wells. Siavashi et al [13,14] employed various optimization methods to investigate the impact of different well spacings (9, 14, 20, 27 m) on oil production. The computational results indicated that larger well spacings resulted in higher ultimate oil recovery.…”

Section: Introductionmentioning

confidence: 99%

Study on Characteristics of Steam Chamber and Factors Influencing Nitrogen-Assisted Vertical–Horizontal Steam Drainage Development

Zheng,

Yu,

Huang

et al. 2024

Processes

View full text Add to dashboard Cite

With the notable achievements attained through the implementation of steam-assisted gravity drainage (SAGD), the vertical–horizontal steam drive (VHSD) emerges as a pivotal technological advancement aimed at significantly enhancing the efficiency of thin reservoir heavy oil recovery subsequent to steam cyclic stimulation. The inclusion of nitrogen assistance has proven effective in enhancing the efficacy of gravity drainage techniques in reservoir development. However, it is noteworthy that this method has only led to improvements in approximately 50% of the well groups within the observed field. The comprehensive evaluation index of VHSD was proposed, and as the objective function, it was determined that the greatest contribution to the VHSD technique lies in oil saturation, accounting for 40% of the overall evaluations. This differs from conventional SAGD operations, where reservoir thickness serves as the primary determinant. Building upon an enhanced physical simulation similarity criterion, two comparative injection scheme experiments were conducted to explore the impact of nitrogen injection on the performance of VHSD and the characteristics of the steam chamber. Nitrogen is distributed in the vicinity of the steam chamber, leading to the formation of a dual mechanism characterized by ‘top heat insulation and lateral traction’ on the steam chamber. The lateral traction accounts for approximately 25% of the team chamber volume. Additionally, the inducement of nitrogen causes a downward displacement of crude oil, resulting in its accumulation within the high-temperature region of the steam chamber. This, in turn, enhances the contact area between the high-temperature steam and the crude oil, ultimately leading to improvement in production efficiency. Further validation of the impact of nitrogen on steam lateral traction and interlayer steam drainage within the reservoir was confirmed using Xinjiang oilfield testing. The well temperature increased from 75 °C to 130 °C.

show abstract

Section: Introductionmentioning

confidence: 99%

Study on Characteristics of Steam Chamber and Factors Influencing Nitrogen-Assisted Vertical–Horizontal Steam Drainage Development

Zheng,

Yu,

Huang

et al. 2024

Processes

View full text Add to dashboard Cite

show abstract

“…[ 11 ] In particular, many studies utilized a series of data‐driven models based on different techniques to analyze the SAGD process. Those studies paid much attention to the impact of reservoir heterogeneity, [ 12–18 ] optimization, [ 19–23 ] production performance prediction, [ 24–28 ] and clustering, [ 29–31 ] which have significantly improved the ability to predict a SAGD process. However, studies of a data‐driven model applied to infill wells in a SAGD process are still rare.…”

Section: Introductionmentioning

confidence: 99%

“…Those studies paid much attention to the impact of reservoir heterogeneity, [12][13][14][15][16][17][18] optimization, [19][20][21][22][23] production performance prediction, [24][25][26][27][28] and clustering, [29][30][31] which have significantly improved the ability to predict a SAGD process. However, studies of a data-driven model applied to infill wells in a SAGD process are still rare.…”

Section: Introductionmentioning

confidence: 99%

Integration of machine learning and data analysis for the SAGD production performance with infill wells

2023

View full text Add to dashboard Cite

There have been numerous studies on predicting the production performance of the steam assisted gravity drainage (SAGD) process by data‐driven models with different machine learning algorithms since their introduction into industry. Similar efforts on SAGD infill wells, nevertheless, remain rare for this advanced alteration in improving the classical SAGD performance. On the other hand, predictive tools to optimize an infill well start time is useful in maximizing bitumen production and minimizing its costs. In this paper, a series of SAGD infill well models are constructed with selected ranges of operational conditions. Three SAGD infill well production performance indicators, namely, an increased ratio (), a total steam–oil ratio (SORtotal), and a stolen ratio () for each SAGD infill well, are calculated based on simulated infill well cases and control models. Five different machine learning algorithms (an artificial neural network [ANN] algorithm, three gradient boosting decision tree [GBDT] algorithms, and a support vector machine [SVM] algorithm) are trained, tested, and evaluated for their effectiveness in predicting those three indicators as output parameters, given seven SAGD relevant parameters as input parameters. Comparisons of different data sets show that the ANN is the best in predicting all three performance indicators under different infill well start times among all the above machine learning algorithms, while the GBDT algorithms have a better ability to learn a variation trend in the SAGD infill well performance.

show abstract

“…technically feasible for bitumen deposits less than 100 m deep and has a limited future capacity, since 80% of the oil sand resources lie too deep underground to mine. In situ production primarily relies on such commercial thermal recovery methods as steam flooding, [5] cyclic steam stimulation (CSS), [6] steamassisted gravity drainage (SAGD), [7][8][9][10][11] and in-situ combustion. [12] All of these techniques take advantage of the super sensitivity of oil viscosity to temperature, in which heavy oil viscosity can be reduced by 4-5 orders if being heated to 250 C. [13] Among the above-mentioned thermal methods, SAGD has achieved great success for extra-heavy oil production.…”

mentioning

confidence: 99%

A new pressure control scheme on steam‐assisted gravity drainage for heavy oil production

Jia,

Wang,

Xiong

et al. 2024

Can J Chem Eng

View full text Add to dashboard Cite

As one the most important recovery mechanisms of steam‐assisted gravity drainage (SAGD), gravity drainage is largely dependent on the inclination angle of the steam chamber edge. The existence of solution‐gas causes an ellipsoid‐shaped chamber that has small inclination angle at the bottom, which leads to inefficient gravity drainage and slows down oil production. To address this problem, this study proposes a new scheme, variable‐pressure SAGD (VP‐SAGD). It is basically a SAGD process, at certain stages of which pressure surge is induced by controlling the operating conditions so that the shape of steam chamber can be altered. This leads to a larger slip angle in the steam chamber at the bottom and more efficient heat transport between hot steam and crude oil. Results show that VP‐SAGD is able to increase oil recovery by up to 20% and decrease cumulative steam–oil ratio (cSOR) by up to 7%. Its special oil extraction mechanisms include swabbing effect, enlarged inclination angle of steam chamber boundary at the bottom, and enhanced heat transfer. Particularly, the inclination angle is increased by up to 40%. In addition, a lower producer bottom‐hole pressure (BHP) during pressure drawdown leads to a better production incremental in later stages. The optimal timing for pressure surge is the middle stage of steam chamber growth. The lower the producer BHP decrease, the better the yield increase. Moreover, The VP‐SAGD strategy works better in heavy oil reservoirs with a permeability of k = 0.5–10 Darcy or solution gas content of greater than 2%.

show abstract

Whole-time scenario optimization of steam-assisted gravity drainage (SAGD) with temperature, pressure, and rate control using an efficient hybrid optimization technique

Cited by 10 publications

References 43 publications

Study on Characteristics of Steam Chamber and Factors Influencing Nitrogen-Assisted Vertical–Horizontal Steam Drainage Development

Study on Characteristics of Steam Chamber and Factors Influencing Nitrogen-Assisted Vertical–Horizontal Steam Drainage Development

Integration of machine learning and data analysis for the SAGD production performance with infill wells

A new pressure control scheme on steam‐assisted gravity drainage for heavy oil production

Contact Info

Product

Resources

About