Modelling Steam-Assisted Gravity Drainage Process in the UTF Pilot Project

Siu, Alan; Nghiem, Long X.; Gittins, Simon; Nzekwu, Ben; Redford, D.A.

doi:10.2118/22895-ms

Cited by 12 publications

(5 citation statements)

References 3 publications

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“…The base relative permeability curves for each model were constructed using the in-program generator using the Generalized Corey Equations, based on data from the SAGD Underground Testing Facility (UTF) in Alberta, Canada (Siu et al 1991;Walls et al 2003). Relative permeability parameters were later varied during the history-matching study to develop the correct relative permeability curves for each sand-pack flood.…”

Section: Simulation and History Matchingmentioning

confidence: 99%

Organic bases as additives for steam-assisted gravity drainage

Brame

Mukherjee

et al. 2019

Pet. Sci.

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Steam-assisted gravity drainage (SAGD) is a mature technology for bitumen recovery from oil sands. However, it is an energy-intensive process that requires large amounts of steam to heat and mobilize bitumen. The purpose of this work is to develop ways to enhance SAGD performance through the use of organic base additives. The research is approached from three focus areas that supplement and guide each other: characterization tests, sand-pack floods, and computational simulation. A number of key mechanisms for enhancing oil recovery were identified, high-temperature additive characterization tests were developed, and promising alkalis were tested in porous media. Simulation was employed to history-match sandpack flood production data, in order to demonstrate the effect of an additive on the oil-water relative permeability. Based on these results, it was concluded that oxygenated organic bases had the most potential for improving bitumen recovery through reducing the oil-water interfacial tension (IFT) by increasing the pH of the system. These organic bases favorably modify the interfacial energies between the immiscible oil-water phases and enable them to flow easily through the porous media during production. Sand-pack flood tests have successfully demonstrated a 10%-15% improvement in bitumen recovery, over baseline, in the presence of IFT-reducing additives. Simulation results further showed that an IFT reduction had a positive impact on SAGD performance. This work demonstrates the potential of organic bases to improve not only SAGD, but other steam injection processes. Furthermore, a number of experimental methods were developed, tried, and tested during the course of this work. Keywords Heavy oil • Steam flood • Low interfacial tension • Wettability • Enhanced oil recovery • Organic bases List of symbols k rw Water relative permeability at S w k row Oil relative permeability at S w k rwro Water relative permeability at residual oil k rocw Oil relative permeability at connate water S w Water saturation S wc Connate water saturation S orw Residual oil saturation in the presence of water Z w Water Corey exponent Z ow Oil Corey exponent

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Section: Simulation and History Matchingmentioning

confidence: 99%

Organic bases as additives for steam-assisted gravity drainage

Brame

Mukherjee

et al. 2019

Pet. Sci.

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“…It would be concluded then that any process which can alter or impact the variation of permeability within the reservoir would have a dramatic effect on process. Both Edmunds, et al 5 and Siu, et al 6 discuss the process of history matching the SAGD process for the Phase A test. Edmunds, et al 5 suggest very good numerical history matches were obtained by adjusting only the permeability distribution in the reservoir.…”

Section: Effect Of Reservoir Depthmentioning

confidence: 99%

“…Edmunds, et al 5 suggest very good numerical history matches were obtained by adjusting only the permeability distribution in the reservoir. Although they did not specifiy their starting values for permeability,Siu, et al 6 also state that absolute perrneability was increased to improve their history match. 4 GEOMECHANICS ISSUES OF STEAM ASSISTED GRAVITY DRAINAGE SPE 30280 region exhibiting maximum dilatancy potential.…”

Section: Effect Of Reservoir Depthmentioning

confidence: 99%

“…The maximum of 2.5E-3 is less than half the maximum of 6.0E~3 found in the base analysis. SPE 30280 effective stress total stress pore pressure (fluid pressure) major principal effective stress minor principal effective stress volumetric strain shearstress at failure cohesion effective friction angle (1 +sin<j»/(1-sin<j» absolute permeability initial absolute permeability initial porosity ah/av =initial stress ratio SUMMARY 6 GEOMECHANICS ISSUES OF STEAM ASSISTED GRAVITY DRAINAGE reservoir properties from the base analysis, an NOMENCLA TURE analysis was conducted to assess the possibility of displacement or shear induced integrity issues arising cr' with the horizontal production or injection well. Figure 21 shows the horizontal displacement field from the limestone base at elevation 270 m up to elevation 350 m, the overburden.…”

Section: Effect On Wei/bore Integrity For Sac Wel/smentioning

confidence: 99%

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Geomechanics Issues of Steam Assisted Gravity Drainage

Chalaturnyk¹,

Scott²

1995

Proceedings of SPE International Heavy Oil Symposium

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After successful testing and full scale implementation of the steam assisted gravity drainage (SAGO) process at AoSTRA's (now Department of Energy, Oil Sands and Research Division) Underground Test Facility (UTF), many operating companies are applying this recovery process ( or variations thereof) in bitumen and heavy oil projects. The thermal SAGO process with adjacent sets of well pairs provides a process geometry where the geomechanical response of an unconsolidated sand reservoir may have an impact on the efficiency of the recovery process. This paper describes a series of numerical analyses which illustrate how fluid pressure increases and thermal loading combine to create an optimum stress environment for shear failure of unconsolidated sand formations. Shear failure in dense unconsolidated sands results in a volumetric increase in sand pore volume due to dilation of the sand grains. To date, bitumen production rates for the SAGO process have been history matched for the UTF Phase A and Phase B tests by increasing the absolute permeability within the formation to a veryReferences and illustrations at end of paper high value; typically to the maximum value within a range of possible values. It will be shown that for the UTF geometry, absolute permeability increases resulting from dilation in advance of the growing steam chamber is likely a factor in the SAGO process. Due to the nature of SAGD, however, reservoir modelling for UTF scenarios are not be significantly effected since dilation in advance of the steam chamber would create the same "absolute permeability" effect as selecting an initially high absolute permeability value. For different reservoir conditions, such as stress conditions, or wellpair spacings then at the UTF, not including geomechanical phenomena in process simulations may adversely affect the results.

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“…The heated crude oil then drains along the steam chamber edge into the production well by gravitational force. Evaluation of (SAGD) performance has been widely studied involving experiments (Sasaki et al 1996, Akin et al 2001, Bagci 2006, Shin et al 2006) and detailed compositional simulation (Siu et al 1991, Kisman et al 1995, Chow et al 1996, Egermann et al 2001, Li 2006, Xu et al 2008, Fatemi 2009, Shin et al 2012. However, it is often impossible to reproduce all conditions and heterogeneities at the field scale in lab-scale models, while numerical flow simulations usually provide only approximate solutions to recovery responses, as numerous simplifications and assumptions must be invoked.…”

Section: Introductionmentioning

confidence: 99%

Practical Implementation of Knowledge-Based Approaches for SAGD Production Analysis

Leung

Zanon

et al. 2014

Day 1 Tue, June 10, 2014

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Quantitative appraisal of different operating areas and assessment of uncertainty due to reservoir heterogeneities are crucial elements in optimization of production and development strategies in oil sands operations. Although detailed compositional simulators are available for recovery performance evaluation for SAGD, the simulation process is usually deterministic and computationally demanding, and it not quite practical for real-time decision-making and forecasting. Data mining and machine learning algorithms provide efficient modeling alternatives, particularly when the underlying physical relationships between system variables are highly complex, non-linear, and possibly uncertain.In this study, a comprehensive training set encompassing SAGD field data compiled from numerous publicly-available sources is studied. Exploratory data analysis is carried out to interpret and extract relevant attributes describing characteristics associated with reservoir heterogeneities and operating constraints. Because of their ease of implementation and computational efficiency, knowledge-based techniques including artificial neural networks (ANN) are employed to facilitate SAGD production performance prediction. Predicting (input) variables including porosity, net-to-gross ratio, saturation, gross pay, normalized shale barrier thickness and distance to well pair, and initial production rate are formulated. Measures such as cumulative production over discrete time intervals are considered as prediction (output) variables. Data records that are comprised of both input and output variables are assembled; the network is trained using the data set to identify all significant patterns and relationships that exist between the input and the output variables. The model is subsequently validated using a cross-verification procedure, during which records that have been excluded at the training stage are presented to the model. This paper demonstrates that knowledge-based techniques can be implemented in a practical manner to analyze large amount of competitor data efficiently. The approach can be integrated directly into most existing reservoir management routines. It can also be readily updated when new information has become available. Given that robust reservoir management and real-time decision-making are major challenges faced by the industry, the data-driven models presented in this paper has great potential to be applied in other recovery projects such as solvent-aided steam injection.

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Modelling Steam-Assisted Gravity Drainage Process in the UTF Pilot Project

Abstract: The Underground Test Facility is designed to test the application of the steam-assisted gravity drainage process for the in situ recovery of bitumen, using horizontal wells drilled from tunnels below the pay zone.

Cited by 12 publications

References 3 publications

Organic bases as additives for steam-assisted gravity drainage

Organic bases as additives for steam-assisted gravity drainage

Geomechanics Issues of Steam Assisted Gravity Drainage

Practical Implementation of Knowledge-Based Approaches for SAGD Production Analysis

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