Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-09-27
2003-02-11
Lefkowitz, Edward (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
C702S013000
Reexamination Certificate
active
06519531
ABSTRACT:
BACKGROUND OF THE INVENTION
Contrary to common belief, hydrocarbons do not occur in gigantic underground caves but are trapped in the tiny pore space of sedimentary rock. After an initial production period (primary production) when the reservoir is produced under its own pressure, additional oil can only be recovered by replacing the in situ volume of oil and gas with something else, such as water or solvent. The use of such secondary recovery techniques on oil fields can significantly increase the extraction of oil and gas. In waterfloods, for example, brine is pumped into the reservoir through injection wells and the displaced oil and gas is recovered at production wells. In tertiary recovery techniques, such as thermal recovery, gas injection, and chemical flooding the goal is to modify physical properties of the resident hydrocarbons, such as densities, viscosities, and interfacial tensions to recover hydrocarbons left behind by waterflooding.
It is has been well established that early implementation of secondary and tertiary recovery mechanisms can significantly increase the ultimate recovery of hydrocarbons versus a later implementation of such methods. These technologies have thereby led to significant energy reserve additions, improved recovery of a finite precious resource, and major environmental benefits by reducing the number of new wells required.
Improved recovery methods also require improved field management needs. As an example, the Alberta Energy Resources Conservation Board (ERCB) requires oil companies to balance their production patterns in order to maximize recovery from existing well patterns. Balancing patterns essentially means that for every barrel of water injected a barrel of fluid is recovered from the production wells surrounding the injector. A similar requirement is imposed by the Texas Railroad Commission.
The present invention relates to a method for the visual representation of the amount of flow between injection and production wells, i.e., the well rate allocation factor (WAF), for each well in an oil field. The invention displays the percentage of support each injector well is giving to each producer well or the percentage of support each production well receives from each injection well. The invention, for example, will help companies engineer balanced patterns, or to determine visually and quickly the effectiveness of injection techniques thereby helping to avoid devoting economic resources to those wells or patterns from which there is ineffective production. By visualizing the interaction between well pairs, the present invention allows engineers to design more efficient recovery schemes and thereby increase the ultimate recovery from current hydrocarbon reservoirs.
The system for implementing the present invention requires the use of a computing device with a display capable of depicting graphic data.
CURRENT TECHNOLOGY
An example of current technology in determining and visualizing well allocation factors is discussed in Amoco Production Company document entitled “Rate-Weighted Allocation—A New Method in Determining Waterflood Pattern Allocation Factors” by R. Koenig. This method centers on the assumption that patterns are predefined and all injection does not go beyond the immediate producers in the predefined pattern. In the five spot example used in the Amoco memo then, this would mean that all the water injected by well
55
is strictly allocated to the four surrounding producers
676
,
588
,
677
, and
566
.
A second example is the method of U.S. Pat. No. 6,128,579 issued to McCormack et al., which uses a genetic algorithm to compute the allocation factors between well pairs in injection patterns of a field. Like the Amoco approach, this method centers on the assumption that the patterns have been predefined. McCormack et al. predefine a pattern using a volume centered on the production well (col. 27, row 39) prior to applying the genetic algorithm to determine the proportional allocation of fluids.
There are three important drawbacks to the approaches used in the Amoco memo and McCormack et al., which comprised the then existing technology: 1) Real reservoirs are complex, three-dimensional objects which will lead to injected fluids going well beyond the immediate producers, reducing possible support to wells in the immediate pattern and at the same time supporting wells outside of the immediate pattern. 2) Many reservoirs are not developed in strict patterns, making an approach based on predefined patterns difficult, if not impossible to implement. 3) The visual representation of the allocation factors is a simple picture that assumes the flow from injectors is to the immediately surrounding producers.
The present invention, on the other hand, relies on determining which producers are supported by which injectors (well pairs) through a streamline-based flow simulation, thereby allowing a more accurate and realistic determination of well pairs independently of their physical proximity. The well patterns and well pairs are output results from the streamline-based flow simulation rather than being predefined as in the Amoco approach and in McCormack et al. As such, the present invention represents a significant and tangible improvement over the prior art. The simulation accounts for well rates, the 3D reservoir structure/geology, fluid distributions, fluid properties, and well location, when determining the allocation factors.
REFERENCES:
patent: 5459820 (1995-10-01), Schroeder et al.
patent: 6128579 (2000-10-01), McCormack et al.
patent: 6446721 (2002-09-01), Patel et al.
Koenig, Randall R., “Rate-Weighted Allocation—A New Method in Determining Waterflood Pattern Allocation Factors,” Dec. 17, 1991, Amoco Production Co., Houston, Texas.
Batycky Rod P.
Thiele Marco R.
Gutierrez Anthony
Lefkowitz Edward
Li James Yuanxin
Sedwick, Detert, Moran & Arnold
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