Steamflood heat management

While always an implicit goal in steamflood processes, overall process heat management became a topic in the literature in the mid-1980s. The growth of the discipline has closely followed the development of the personal computer and computer applications. Heat management consists of data gathering, data monitoring and adjustments to the process as discussed in this page.

Heat balance

Fig. 1 is a graphical representation of the major components of a heat balance that must be performed to properly manage a steamflood process. Ziegler et al. published a very good summary of a method of implementing the principle. In essence, the operator must establish an iterative process that continues for the duration of the project and that continuously collects and analyzes pertinent data. Based on that analysis, the operator then makes appropriate midcourse adjustments to optimize the project. The process is actually a complete project optimization method but has adopted the name "heat management" because steam generating costs tower over any other cost and are even several times larger than the initial substantial capital investment in a steamflood. There are three basic parts of the method, as shown in Fig. 2, which are data gathering, data monitoring, and adjustments to the process.

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  Fig. 1 – Schematic diagram of the components of heat management for steamflood projects.

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  Fig. 2 – Heat management flowchart.

Data gathering

As its name implies, data gathering consists of compiling regular and typically large amounts of information on the operation. Data from producing wells, injection wells, observation wells, and surface facilities are compiled and stored in computer databases. Table 1 was derived from Ziegler and indicates the information currently considered necessary for California steamfloods. In addition to the types of data collected, the operator must also specify a regular schedule for collection.

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  Table 1 - Example steamflood monitoring data plan for heat management.

All of the data are from existing and necessary components of the system except for the observation wells. Although it is tempting to economize by eliminating them, that is false economy. Information they provide on the change in temperature and gas/oil saturation over time is critical in maintaining process efficiency. The data must be stored in computer databases that are accessible to desktop PCs.

Data monitoring

As with any oil production operation, there are daily and weekly tasks that must be done. However, in heat management, the operator must schedule formal project reviews on a much longer term such as a semiannual or annual basis. Table 2 is an example review schedule. During these reviews, the project performance data is compared to the original design, and adjustments are made accordingly.

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  Table 2 - Example data analysis schedule for steamflood heat management.

Key calculations are heat and mass balances to quantify the terms shown in Fig. 1.

....................(1)

and

....................(2)

Table 3 is an example of a list of metrics that should be established to aid in making heat management decisions. Note the use of the term "produced oil/fuel" ratio, F_of, in the metrics table. This is in place of the more common "produced oil/steam injected" ratio, F_os. The reason for using the former is that steamfloods often are operated at steam qualities that vary significantly from the normal 70 to 80%. In these cases, F_os would be a misleading indicator, and an in/out energy factor would be a better benchmark to use. Either of these is useful as a project metric, but the user must be aware of the limitations. Fig. 3 shows the F_of for three different steam injection schedules. Using only F_of as the criteria, The Neuman steam-injection schedule (Fig. 4) seems to be far superior to the other two. However, Fig. 5 shows that the linear steam rate reduction probably gives the best overall economic performance. The Neuman reduction rate is designed to optimize F_of, but severe early steam reduction results in lower oil rates and cumulative production.

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  Fig. 3 – Produced oil/fuel burned ratio for three steam-injection scenarios.

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  Table 3 - Example heat management metrics

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  Fig. 4 – Effect of steam injection schedule on oil production.

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  Fig. 5 – Typical steam-injection rate schedule for gravity-dominated steam displacement.

Adjustments to the process

Once the project has been reviewed and compared to the various benchmarks, it is either on or ahead of schedule, thus requiring no changes, or is not performing as expected and is in need of a midcourse correction. Table 2 lists common changes. There are only a few operational areas that can be changed.

Fig. 6 is an example of a Midway Sunset, California, steamflood that benefited from heat management. The operator determined that the wells were producing at their maximum rate but that steam injection was much higher than required. Based on this analysis, the steam rate was redirected and then reduced with improved oil production, thus greatly improving project economics and ultimate recovery.

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  Fig. 6 – Midway Sunset field example of heat management results on an in-progress steamflood.

Fig. 7 is another example of heat management techniques being used to improve an in-progress steamflood. This Kern River, California, project was found to be overinjected, and some producers were not completed in the proper zones. Steam rate was redirected in new injectors, and some producing wells were recompleted; later, steam rate was reduced, resulting in lower steam cost, increased oil production, and reduced water production. At the time of publication, the operator was faced with an apparent opportunity for another heat management study and adjustment to the process.

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  Fig. 7 – Kern River field example of heat management results on an in-progress steamflood.

Nomenclature

mcasing_blow	=	mass (gas) extracted from system, lbm [kg]
mi	=	mass injection, lbm [kg]
minflux	=	mass exiting system, lbm [kg]
ml	=	mass of liquid, lbm [kg]
m(o/w)influx	=	mass flowing into system, lbm [kg]
m(o/w)prod	=	mass (fluid) extracted from system, lbm [kg]
Q casing_blow	=	heat removed with produced gas, Btu [kJ]
Qi	=	total heat injected, Btu [kJ]
Q influx	=	heat leaving system, Btu [kJ]
Ql	=	heat lost in reservoir, Btu [kJ]
Qls	=	surface piping heat loss/unit length, Btu/ft [kJ/m]
Qot	=	cumulative oil recovery at time (t), B/D [m3/d]
Q (o/w)influx	=	heat flowing into system, Btu [kJ]
Q(o/w)prod	=	heat removed with produced liquids, Btu [kL]

Noteworthy papers in OnePetro

Use this section to list papers in OnePetro that a reader who wants to learn more should definitely read

External links

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See also

Steamflood design

Cyclic steam stimulation design

Thermal recovery by steam injection

Steam delivery systems for EOR

PEH:Thermal_Recovery_by_Steam_Injection